Category: AI

AI SEO

Why AI-Generated Content Has an Even Shorter SEO Shelf Life Today

Post author By Jill Kocher Brown
Post date October 19, 2026

This post was originally published in April 2025 and significantly updated in September 2026 and October 2026.

The writing is on the wall for the efficacy of AI-generated content if you value your organic search and AI visibility. Google’s definition of low-quality, AI-generated content as spam, as well as its focus on Spam Updates in 2026, both point to major issues for sites that rely on AI-generated content.

Don’t miss our account of one site’s AI-assisted SEO crash after posting content generated by AI and modified by an expert.

Training Google’s Systems, Like SAFE and S-CTS

Almost two years ago, Google’s worldwide quality rating team received its first instructions on AI-generated content. Quality raters are real human beings who use the quality rater guidelines document that Google creates to help them manually rate the quality of pages that rank for specified search queries.

That quality assessment data is then used to train Google’s algorithms to produce better search results algorithmically.

There’s no way to be certain, but in the September 2026 Spam Update, Google may have included its latest spam-fighting system in the mix. The Scaled Abuse Forensics Examiner (SAFE) was designed to identify AI-generated content. The research paper describing SAFE mentions:

Synthetic content analysis;
AI-generated video;
Channel abuse (automated manipulation on media channels and publishing networks like YouTube);
Multimodal semantic embeddings (a mathematical translation layer allowing SAFE to analyze content across different mediums; and
Detecting “nonhuman engagement patterns.”

That’s in addition to the Scalable Cluster Termination System (S-CTS) research paper that Google released earlier this year to combat AI-generated video spam. That S-CTS paper refers to Sentence-BERT (S-BERT), a 2019 innovation built on Google’s original Bidirectional Encoder Representations from Transformers (BERT) system.

S-BERT can detect automated, AI-generated text — which leaves text embeddings as a mathematical footprint — that BERT previously did in a fraction of the time (think cutting hours of processing time down to a handful of seconds). Since S-BERT was developed in 2019, it has likely been in play in recent spam updates.

Trying to skate under the radar with AI-generated content now is like holding a ticking time bomb.

What the Quality Rater Guidelines Say About AI-Generated Content

Starting in January 2025, quality raters were instructed to give pages that use AI-generated content that contains little added value the “Lowest” quality rating. As you can see below, the bolding and capitalization are actually in the September 2025 quality rater guidelines (download them here, see page 29), further emphasizing Google’s stance.

While the guidance Google gives to its quality rating team doesn’t affect algorithmic performance today, what Google requires them to rate and how matters for your future algorithmic organic search performance in Google’s results.

Is Google already judging AI-generated content algorithmically? We have no way of knowing for sure, but the most recent Spam Update in September 2026 sure looks that way.

Google’s Spam-Fighting Quest

Since 2021, Google has released 13 confirmed Spam Updates. Four of them popped up in the first nine months of 2026. After several years of what felt like lackluster attention to spam, Google is suddenly very focused on it again.

In fact, Google’s vice president of engineering, Rajan Patel, backed that up with a one-word answer to an X post speculating on whether the spam team is still well-funded: “Yes.”

Veteran SEO professional Mordy Oberstein presented his findings using the SE Ranking platform: The number of URLs dropping out of the top 100 rankings with the August 2026 Spam Update was 82% above the baseline in July 2026.

Google’s scaled content abuse spam policy, a part of which refers to low-value AI-generated content, is frequently cited as causing a greater degree of shuffling within Google’s search results during this year’s August and September spam updates.

What Google’s Quality Rater Guidelines Say

So, how do Google’s quality rater guidelines address AI-generated content? They’re due to be updated soon, but the September 2025 guidelines include two instances in sections 4.5 Untrustworthy Webpages or Websites and 4.6 Spammy Webpages. The subsections that pertain to AI-generated content include:

4.5.3 Deceptive Page Purpose, Deceptive Information about the Website, Deceptive Design
- A webpage or website with “fake” owner or content creator profiles. For example, AI generated content with made up “author” profiles (AI generated images or deceptive creator descriptions) in order to make it appear that the content is written by people
4.6.5 Scaled Content Abuse
- Using automated tools (generative AI or otherwise) as a low-effort way to produce many pages that add little-to-no value for website visitors as compared to other pages on the web on the same topic
- Pages and websites made up of content created at scale with no original content or added value for users, should be rated Lowest, no matter how they are created. Even if you are unsure of the method of creation, e.g. whether or not the page is created using generative AI tools, you should still use the Lowest rating when you strongly suspect scaled content abuse after looking at several pages on the website.
4.6.6 MC Created with Little to No Effort, Little to No Originality, and Little to No Added Value for Website Visitors
- The Lowest rating applies if all or almost all of the MC on the page (including text, images, audio, videos, etc) is copied, paraphrased, embedded, auto or AI generated, or reposted from other sources with little to no effort, little to no originality, and little to no added value for visitors to the website. Such pages should be rated Lowest, even if the page assigns credit for the content to another source.
- Likewise, the use of Generative AI tools alone does not determine the level of effort or Page Quality rating. Generative AI tools may be used for high quality and low quality content creation. For example, a high level of effort may be involved in creating high quality original artwork using Generative AI tools. However, it’s also possible to use Generative AI tools to create Lowest quality content with little to no effort, little to no originality, and little to no added value for website visitors.

What Google Is Really After

Think about it: The last thing Google, or any search engine or AI platform, wants is to waste resources crawling through an internet littered with crummy, low-quality content. Generative AI tools are being used to pump it out by the billions.

If Google can spot those pages algorithmically and decline to index them from the start, that saves Google resources and prevents searchers from stumbling across low-quality sites in search results.

Short-Term Gain (Maybe) but Long-Term Pain

Site quality is one of the hardest search engine optimization (SEO) issues to detect and clean up. The worst part is that there are no tools that diagnose site quality to tell you that that’s the issue you’re facing. And no tools that will tell you which pages on your site are considered low quality.

You can assume you have quality issues if you’re hit by one of Google’s algorithms, specifically the Core Updates or Spam Updates. Those algorithms can determine quality as a sitewide marker. Posting low-quality pages in one area of your site, like a blog, can drag down the organic search performance for the entire site, not just for the low-quality pages.

Overcoming a spam or other content-quality issue is a long, painful process that can take six to 18 months or longer. The recovery process looks like this:

Day 0: Get hit by a Google core or spam algorithm update;
Day 14: Determine what the causes could be with no information besides what you can glean from your own analytics and the actions taken on your site;
Months 3-6: Fix the issue entirely;
Months 7-9: Wait 90 days for Google to crawl and recrawl your site repeatedly to determine that the issue is gone and isn’t coming back;
Months 10-15: Wait for another Google core or spam algorithm update to finish rolling out;
Month 16: Determine if the fix improved performance; and
Month 16.5: If not, try again.

After all of this work, there’s no guarantee of success. It’s far better to play it safe with Google’s algorithms.

So let’s put the pieces together:

Google instructs human quality raters to assign the “lowest” quality rating for content that provides low value-add, including AI-generated content;
Google uses human quality rater data to train its algorithms;
Google’s algorithms can punish sites at the whole-site level for content quality issues; and
It’s a long, difficult process to fix content quality issues across a site, and it takes months and months to rebound from algorithmic dampening.

Pasting AI-generated content on your site is not worth the risk to your organic search performance.

The Bottom Line

It’s just not worth trying to produce content automagically using AI for organic search benefit. Site quality issues can burn a domain’s organic search performance to the ground. Do you really have the ability to withstand decreased organic search leads or revenue over the months or years it can take to diagnose and fix site quality issues? If the answer is no, then you’ll need to future-proof your performance by saying “No” to low-value-add AI-generated content today.

AI in Online Advertising: 5 Key Trends from September 2026

Post author By Jeremy Quinones
Post date October 6, 2026

Microsoft put a 90-day feed-first shopping playbook on the table, TikTok doubled AI video length and references inside Symphony, and OpenAI shipped both a ChatGPT Ads Manager plugin and a click-to-chat Sponsored Agent pilot. I also took a second look at Grok Bot for content work, not campaign management. Here are the five most impactful stories for online advertisers.

1. Microsoft’s 90-Day Playbook: Feed First, Then Creatives

Source: Microsoft Advertising | August 21, 2026

Microsoft published Prepare for the Age of AI Shopping, a practical guide aimed at the holiday window. The purpose of this is to get discovered with an AI-ready Microsoft Merchant Center feed, get chosen with AI-native ads, Copilot Checkout, and a Brand Agent on your site, then measure with Clarity AI Visibility insights. According to Adobe data cited by Microsoft, AI was the fastest-growing retail traffic source last holiday season, up 693% year over year, and AI agents influenced about 20% of global retail sales, roughly $262 billion. A Microsoft survey of 1,028 U.S. consumers (Aug–Sep 2025) found 72% expect AI-assisted shopping from retailers within a year. Adobe’s Q1 2026 AI traffic report cites a 42% conversion lift on AI-referred visits. Agents do not give partial credit for incomplete product data.

JumpFly Takeaway

Agents, the robots… terms you will hear me say often, both personally and around the office. But these robots are doing more and more shopping as agentic experiences become more common. Those agents don’t shop your homepage; they shop a product feed. Microsoft put a 90-day checklist on that same idea. The first practical move is an audit: pull Microsoft Merchant Center next to Google Merchant Center and fix titles, prices, availability, and attributes on your SKUs, and see what might need cleaning up. If Clarity is already on the site, turn on AI Visibility and see which assistants cite you and which queries they attach to your brand. If you have not seen this yet, it is pretty cool to see the queries (as accurately as that is being tracked). The true takeaway in accepting an AI-first world is to clean your data first. Creative second. Measurement third. The agent does not care that an ad looks great; it cares about the data it receives.

2. TikTok Symphony Seedance 2.5: 30 Seconds and 50 References

Source: TikTok For Business Blog | August 3, 2026

TikTok integrated Dreamina Seedance 2.5 into Symphony Creative Studio and Symphony Automations in Ads Manager. Video generation length doubled from 15 to 30 seconds. Multi-modal references (image, video, and audio) jumped from 9 to 50 references, with timestamp-specific creative direction for sequence and pacing. TikTok also introduced sharper visuals and stronger consistency across lighting, motion, and characters. Safeguards include AI labels, invisible watermarking, C2PA Content Credentials, and blocks on real-face uploads. The rollout is available to select paid advertisers in select markets.

JumpFly Takeaway

Another month, another creative tool. I have not used Seedance myself. For smaller marketing teams that need more cuts without a full production day, 50 reference files is the interesting part. In theory, that is enough product detail to ground a scene instead of hoping the model creates your SKU correctly. If Symphony is in the account, generate one 30-second cut from existing stills. Trust but verify still applies. AI labels and watermarks do not replace a human review. AI video generation has come a long way, keeps improving, and really makes a creative specialist’s workflow much quicker. It is now that much easier to create the same ad catered to a different audience on the fly. Have fun, creatives!

3. Grok Bot for Content Creation: A Marketer’s Second Look

Source: xAI | August 11, 2026

xAI launched Grok Bot on August 11 as an always-on teammate with its own computer. Grok Bot signs into the tools you already use, finishes multi-step jobs, and comes back when something needs approval. The pitch covers parallel specialists, routines learned by watching a workflow once, and beta access for SuperGrok and Cursor subscribers, with usage separate from existing Grok and Cursor plans. Inside SpaceXAI, early examples include sales CRM updates, ops invoice handling, and marketing campaign work. This is the content and ops lane, not a paid-media-manager recap.

JumpFly Takeaway

Yes, another content creation point to talk about in this post. Of course I must test all AI tools that are available at my disposal. I am high on my buddy Grok Bot (let’s call him Jimothy). How might this relate to content creation? Think about having an always-on creative specialist or a team of specialists. One that pings YOU; you do not need to start the chat all the time. Give Jimothy access to the tools you work with, and give him (or her) the workflow. Have a thought for a campaign? Drop that into the chat or a Google Sheet Jimothy is following. He will take care of the concepts and get back to you with fleshed-out ideas. I know this sounds easy in theory, and it really is, but I still think there is value in crafting great skill files, having grounded instructions, and having a well-defined workflow. Grok Bot is one of those things you need to try to fully understand how cool an agent can be. Oh, and Grok helped me win my fantasy football Week 1 matchup.

4. ChatGPT Ads Manager Plugin: Build and Analyze from ChatGPT or Codex

Source: PPC Land | September 3, 2026 (OpenAI Ads product update email, week of August 31)

OpenAI’s ChatGPT Ads product update leads with an Ads Manager plugin inside ChatGPT or Codex. Advertisers can create, manage, and analyze campaigns in plain language: turn a brief or site into ads, generate variants, update live campaigns, troubleshoot delivery, review performance, and return prioritized recommendations. Recommended changes appear as previews and need confirmation before they are applied. The same update also covers custom-audience exclusions under 25,000 matched users, richer conversion matching fields, carousel card reporting (separate from billable impressions), total-budget pacing, and a forthcoming impression-billed view-through optimization model. Geographic expansion is in the email. It is not the lead here.

JumpFly Takeaway

Why talk about a plugin? What does this have to do with digital marketing? First, plugins extend the capabilities of an LLM and just make life easier (no more spreadsheet downloads and uploads). I love the ChatGPT Ads Manager plugin because it just works, pulling data in any manner I wish to see. It can help draft concepts and create variations on the fly. Exactly what I would expect this type of plugin to do for me. Before I get too far, if this plugin is creating the ads within your chat, be sure to Trust but Verify. The last thing you need is an unrelated ad or false claim going live.

Think of this from a workflow perspective — you can create an agent within ChatGPT, give it access to the plugin, give that agent memory, and lastly give it access to skills YOU craft. Not a generic marketing skill, but a skill that you have refined over time based on REAL experience. Now when I pull metrics using this plugin or ask for ad variations, this is all done the JumpFly way. ChatGPT Ads are still so new that we are also learning like everyone else, but there is one thing we have over the general population, and that is 20+ years in the digital marketing space.

5. OpenAI Sponsored Agent: Click to Chat, Not to Site

Source: Digiday | September 14, 2026

OpenAI is testing a new ChatGPT ad format called Sponsored Agent. When someone clicks the ad’s call to action (something like “Chat with us”), ChatGPT opens a branded chat with the advertiser’s own AI agent instead of sending them to a website. The shopper asks that agent questions about products, and it can hand them off to customer service or point them to a purchase when they need it. OpenAI calls this AI-native advertising, and it goes a step further than the sponsored card that shows up under ChatGPT answers today. Right now only select advertisers have it, in a limited pilot built around product accuracy, transparency, and clean handoffs to a person. OpenAI’s Ad Tools Terms already define Sponsored Agents and make the advertiser responsible for what their agent says and does, and no one has published performance numbers yet.

JumpFly Takeaway

This is one I am excited about. Agents are all the rage these days, so this is not a surprising pilot. Having control over your agent is the way I would have also gone about this vs. letting the LLM determine my brand. Keeping the shopper inside ChatGPT is useful for discovery and Q&A. It also means your agent is now the landing page, the FAQ, and part of the sales desk. Wrong product answers or a broken handoff to a human will burn trust faster than a bad RSA. I have not seen this roll out yet to any accounts I manage but am eager to begin testing. What I like is that this goes beyond a traditional text ad and brings something new. Time will tell how competitive this is, how many agents are shown at the same time, and if this is going to be CPC or CPM-based. I will report back once we have been able to test this and how it compares vs. the standard ad types.

Looking Ahead

September’s stack is feed readiness, creative volume, content ops, and ChatGPT Ads growing a real product surface beyond the sponsored card under an answer. Microsoft wants your Merchant Center clean before the holidays. OpenAI wants the ad to open a conversation. TikTok wants more seconds and more references in the generator.

None of that replaces the fundamentals. Clean product data, someone reviewing AI output before it ships, and a clear line between what you have tested and what you have only read about are still what separate useful experiments from expensive demos.

Questions about how these AI trends affect your campaigns? Let’s talk.

Stay tuned for next month’s update on AI in Online Advertising.

AI in Online Advertising: 5 Key Trends from August 2026

Post author By Jeremy Quinones
Post date September 1, 2026

The highlights of August’s AI trends are new bid strategies, a strong earnings quarter, an image model worth testing, a new AI agent, and an early look at holiday shopping behavior. Here are the five most impactful stories for online advertisers.

1. OpenAI’s New “Maximize Results” Bid Strategy Won’t Guarantee a CPA

Source: OpenAI Help Center | August 13, 2026

OpenAI added a new Maximize Results bid strategy to ChatGPT Ads Manager, letting the platform automatically set and adjust bids on an advertiser’s behalf to pursue whichever campaign goal they’ve selected. It’s now the default bid strategy for new, qualifying ad groups, meaning advertisers may be opted into automated bidding without taking any action themselves. OpenAI’s own documentation is direct about what the strategy doesn’t do: it does not guarantee delivery against a specific CPA, CPC, or ROAS target, only that it will optimize spend toward the stated goal within budget. Read the fine print before you turn it loose on a live account.

JumpFly Takeaway

Another month, another Google Ads…I mean ChatGPT Ads feature. OpenAI has a proven model in Google Ads, and it seems they continue to try to mirror elements of that platform, which is not a bad thing. Maximize Results is the latest one. This strategy doesn’t guarantee a CPA, a CPC, or a ROAS; it just chases volume within your budget. So basically, it’s similar to Maximize Conversions in Google Ads. Test it against a manually managed ad group for a few weeks before you trust it as the default, especially since it’s now selected automatically for new ad groups whether you noticed or not. Watch daily spend, watch your click volume, and watch your conversions closely during that test window, because bidding without a performance guarantee can drift in either direction before anyone catches it. If it’s underperforming after a few weeks, turn it off. Default doesn’t mean required.

2. Pinterest’s Second Straight Quarter of AI-Powered Growth Comes With a Reason Why

Source: CNBC | August 4, 2026

Pinterest posted Q2 2026 revenue growth of 18% in its largest market (UCAN), with monthly active users climbing to 640 million. That’s its 12th consecutive quarter of record user growth, and the company issued Q3 guidance of 13 to 15% growth on top of it. Management pointed to Performance+, its automated campaign product now absorbing measurement capabilities from newly acquired tvScientific, and a new AI Assistant designed to move users from browsing to research, as the drivers behind the momentum. The most advertiser-relevant number in the release: 96% of text-based searches on Pinterest are unbranded, meaning most of what people search for isn’t a company name; it’s a category, a style, or an idea.

JumpFly Takeaway

Pinterest keeps surprising me. Get the right AI tools plugged into the right plan, and this platform can add real incremental growth to a business, not just brand awareness. That 96% unbranded search stat is the one to build a strategy around: if almost nobody searching on Pinterest is typing a brand name, the platform is a discovery surface for categories you don’t yet own, not a place to defend ones you do. I tested this on a sample size of one: my wife is on Pinterest often, so I asked her what she actually searches for. Every single one was unbranded: an idea, a style, a project, never a company name. Small sample, but it matches the data, and it points to what Pinterest is actually good for: idea generation, and being there to answer the question someone’s still forming in their head. That’s exactly where the AI part comes in. Performance+ and the new AI Assistant are built to catch that intent while it’s still vague, before it’s a branded search, and turn it into something an advertiser can target and measure. Shift budget toward broad category and interest targeting inside Performance+ instead of treating Pinterest like a smaller version of your branded search campaigns, and let the AI connect that early, fuzzy intent to your product. If you have the budget, give Pinterest a try this Q4; I know my team can help get this off the ground if needed.

3. Grok Imagine Image 2.0: The Layers Feature That Makes Ad Creative Easier To Iterate On

Source: xAI | August 7, 2026

On August 7, xAI released Grok Imagine Image 2.0, its latest image generation and editing model, positioned as a designer-grade tool that plans typography and layout the way a designer would. xAI claims a #2 world ranking on Arena leaderboards for both text-to-image generation and editing. The model supports multi-reference editing across up to five images, nine aspect ratios, and 15 built-in templates covering product shots and merchandise design. The feature that matters most for ad creative work: it generates each element of a design, including the headline, background, product shot, and icons, as its own separate, editable piece instead of one flattened image.

JumpFly Takeaway

The layers are what stood out to me. The image attached is for a fun, personal project just to test this out. Getting each element back as its own editable piece means I can go in and adjust just the headline or just the phone mockup without regenerating the whole image. That’s a real time saver for anyone doing ad creative, where you’re rarely happy with everything on the first pass. Based on my testing, Grok Imagine Image 2.0 is a genuinely good tool, but there’s one thing worth checking closely before you rely on it: the text. Notice in my one example that the background text and text within the phone are not even a language. The concept, though, was good, so not the end of the world, as I can clean that up. My go-to for ad images is still ChatGPT Images 2.0, mostly because I trust its text rendering more in one shot, but Grok’s layers are worth having in the toolkit, especially for iterative work where swapping one piece without touching the rest saves real time. If you’re evaluating image models for ad creative, test a few on your own product and see which fits how your team actually works. The right tool depends more on your workflow than any leaderboard ranking.

4. xAI’s Grok Bot Will Manage Your Paid Media Autonomously, but Will It Really?

Source: xAI | beta launch ~August 11-12, 2026

xAI launched Grok Bot in early beta, an “always-on” AI agent that gets its own dedicated cloud computer and can log into an advertiser’s tools and websites to complete tasks independently, 24/7, even when the user’s own device is offline. xAI’s own product page lists paid media management among the flagship use cases, alongside sales prospecting and account management, with bots able to save a demonstrated task as a repeatable routine and run it going forward without further input. Pricing runs through Cursor and SuperGrok tiers, from $120 to $300 per seat per month, and the pitch is minimal setup: show it once, and it handles the rest. xAI doesn’t say much about approval workflows, audit trails, or guardrails beyond a general reference to “user control.”

JumpFly Takeaway

Trust but verify. I keep coming back to that phrase in this blog series, and it applies directly here. An AI agent that logs into your ad accounts and manages paid media isn’t something I’d hand my budget to. xAI’s page being thin on guardrails is the part to be cautious about, not the AI itself. I do think a tool like this can genuinely help with campaign management: pulling data, spotting patterns, doing the grunt work faster than any person could. I mean, outside of paid management, I will definitely be using Grok Bot for other initiatives (I’d like to introduce you all to my Fantasy Football GM for a season). Where I draw the line is letting it be the manager instead of helping the manager. JumpFly’s own internal AI tool works the same way. It helps us pull data points quickly, build reports, and surface what needs attention, but it is not making the final call on your account. Spreadsheets weren’t any different decades ago. They changed how the work got done, and people still checked numbers by hand while they learned to trust the tool. That’s how I use AI now. I would be crazy not to use something this capable, but I still verify what it gives me before I decide my course of action.

5. 2026 Holiday Shoppers Aren’t Just Trying AI, They’re Relying on It

Source: Google I/O 2026 keynote | May 19, 2026; eMarketer/Similarweb | May 6, 2026

At Google I/O 2026, Google disclosed that AI Overviews has surpassed 2.5 billion monthly active users and that AI Mode, introduced roughly a year earlier, has already crossed one billion monthly users, figures Google repeated again in a June follow-up post. Heading into the 2026 holiday season, eMarketer and Similarweb data show 37.1% of consumers plan to lean on AI more for holiday shopping this year, primarily for product comparison, price hunting, and gift idea generation. Perhaps most notable for advertisers: ChatGPT’s conversion rate on shopping-related queries has climbed to 7.1%, nearly matching paid search’s 7.8%, a gap that was far wider a year ago. Consumers are also starting their holiday research earlier and comparing more retailers than in past years, stretching the window between first browse and final purchase.

JumpFly Takeaway

Crunch time, in my opinion, has already started. Skip past the billions of users for a second. The number that matters is the 7.1% conversion rate on ChatGPT shopping queries, close enough to paid search’s 7.8% to indicate this is a channel converting today, not one to watch for later. I’ve already started my own holiday shopping this year, and I’m using AI to do it, mostly because it gathers information faster than I can dig through ten browser tabs myself. If I’m doing that already, plenty of your customers are too. That means product visibility inside AI platforms needs a real budget line this quarter, not a wait-and-see experiment. Clean, detailed product feed data and accurate pricing need to be in place now, not scrambled together in November. Shoppers are also starting research earlier and comparing more retailers than in past years, so the window between first browse and purchase is longer, which argues for a longer nurture sequence instead of dumping spend into one promotional peak. AI isn’t going away, and the accounts that build a strategy to be seen inside it now, while there’s still time before Q4 budgets lock, are the ones that benefit when the crunch fully hits.

Looking Ahead

AI isn’t going away (one of my recent 10 catch phrases), and it’s already good enough to change how you find customers, build creative, and run campaigns. It just isn’t good enough yet to run unsupervised on highly sensitive projects, but it can for smaller, more defined workflows. OpenAI’s bid strategy won’t guarantee a CPA even as it becomes the default. Grok Bot will manage your paid media if you let it, with little built-in oversight. Grok Imagine 2.0’s layers are a real time saver, but the text still needs a second look. None of that means slow down. Pinterest’s growth and the holiday shopping data both say the opposite: the crunch has already started, and the accounts that do well this fall will be the ones that built a strategy to be seen now.

Questions about how these AI trends affect your campaigns? Let’s talk.

For more AI insights, see our previous post, AI in Online Advertising: 5 Key Trends From July 2026, and others in this series.

AI in Online Advertising: 5 Key Trends From July 2026

Post author By Jeremy Quinones
Post date August 4, 2026

This month, we learned some real numbers about AI search instead of relying on guesses, including how often ads actually show up and which platforms cite you when they do. OpenAI stayed busy too, adding a stack of features to its ad platform and putting Codex on every desktop for free. Here are the five most impactful stories for online advertisers in July.

1. Ads Now Appear on Nearly 30% of AI Mode Commercial Queries, But Paying Doesn’t Buy a Citation

Source: SE Ranking | July 15, 2026

SE Ranking looked at just over 50,000 commercial keywords and found ads inside Google’s AI Mode answers on nearly 30% of them. The more a keyword costs, the more likely an ad is to appear. Ads showed up on about a quarter of the cheap keywords and on more than half of the terms running $10 and up. It swings hard by industry, too, from 72% of pet searches down to under 3% in healthcare. But what I found most interesting was about citations. When an advertiser’s ad appeared in an AI Mode answer, that same advertiser’s site was named as a source only 11.5% of the time, and their page ranked organically for the query in just 2.3% of cases. Buying the ad slot and getting cited in the answer turn out to be two completely different things.

JumpFly Takeaway
There’s been a quiet assumption that buying your way into AI Mode would help you show up in the answer itself, that the two systems somehow talk to each other. They don’t. Paying for the slot buys the slot, and nothing else comes with it. What that means practically is you need two separate plans: a paid strategy for the placement and a content strategy for the citation. Neither one covers for the other, just as it has always been. The CPC correlation is worth noting. If your keywords are already expensive, ads are showing on more than half your AI Mode queries right now, whether or not anyone on your team has thought about it. So that is a win, assuming you are leveraging AI Max or Performance Max. You do not need to do anything special to qualify for this placement. I am still holding out hope that we will get to see this breakout in the future: traditional search placement vs AI Mode/AI Overview placement.

2. Semrush Studied 126 Million AI Prompts: ChatGPT Cites 15 Sources per Answer, Gemini Cites 3

Source: Semrush | June 26, 2026

Semrush released an expanded AI Visibility Index built on 126 million US AI search prompts collected between January and April 2026, covering ChatGPT, Gemini, Google AI Mode, and AI Overviews across more than 1,200 brands in 22 verticals. The headline finding is how differently these platforms behave when they answer: ChatGPT averages 15.4 sources per response while Gemini averages just 3.3. Only 36 brands held top-100 visibility across all four platforms every month of the study, a list dominated by YouTube, Google, Reddit, Amazon, Facebook, and Apple. Overlap between being mentioned and being cited ranges from 64% on AI Overviews down to 30% on Gemini, meaning a brand can be discussed in an answer without ever being linked in it. Semrush also found that 45% of marketing leaders cannot accurately measure their brand’s visibility in AI answers, and only 9% can track every metric that matters.

JumpFly Takeaway
The big five-to-one gap in how often ChatGPT and Gemini cite sources reveals a simple truth: there is no “one-size-fits-all” approach to winning in AI search.
When a platform like ChatGPT pulls 15 sources into an answer, your goal is visibility. You need to show up in as many credible places as possible. But when Gemini pulls only three, you’re in a high-stakes authority game where the most trusted voices win. If you try to use the same strategy for both, you’re likely setting yourself up to fail.
The data backs this up: companies that treat SEO and AI visibility as one unified effort see an 81% success rate, compared to just 36% for those that keep them separate. As I have stated in my past posts, SEO is the engine that drives AI visibility (GEO). If you have two different teams chasing these goals, you’re paying twice for work that should be a single, coordinated mission.

3. ChatGPT Images 2.0 in Practice: On-Brand Creative, Sized for Every Platform

Source: OpenAI | April 21, 2026

OpenAI released ChatGPT Images 2.0 in late April, and it’s the first image model that reasons before it generates. It can search the web for real-time reference, produce up to eight images from a single prompt, and check its own output before handing it back. For advertisers, two capabilities matter more than the rest. The model handles any aspect ratio from 3:1 ultra-wide to 1:3 ultra-tall natively, at resolutions up to 3,840 pixels on the long edge, with no post-processing and no manual cropping. And the edit endpoint accepts multiple reference images in one call, so you can feed it several real product shots and get back a composed scene without masking anything. Text rendering improved substantially, including non-Latin scripts, which means ad mockups come back with actual headlines instead of placeholder text. It’s available to every ChatGPT user and through the API as gpt-image-2, costing roughly half a cent to 21 cents per image, depending on quality.

JumpFly Takeaway
I am a big fan of Images 2.0. Its results are consistent, and it follows instructions much better. Exactly what OpenAI said it would do. From personal use to professional workflow, I’ve been using this one heavily. It definitely solves a problem that has quietly eaten more hours than anyone wants to admit: making one idea work across every platform’s specs. A square for the feed, a 9:16 for Stories, a wide banner for display, a 4:5 for Meta. That used to be a designer’s afternoon or a compromise where you crop the hero image badly and hope nobody notices. Images 2.0 generates the ratio natively instead of cropping into it, so the composition is built for the frame rather than squeezed into it. And I do not like the look of a squeeze. Feeding it your real product photography as reference is what makes it usable for actual brand work. The biggest unlock has been taking a produced image and having it resized. In fact, there are preset settings available to have it resized to 1:1, 9:16, 4:5, 16:9, etc. Very rarely does any content actually change, and it truly does resize in a matter of minutes. This saves me a few emails and saves the designer time to resize the images. But as always, review everything before it ships.

4. OpenAI Ad Platform Updates – The Weekly Norm

Source: Email received from OpenAI on Jul 24, 2026

OpenAI pushed eight updates to ChatGPT Ads in a single release, announced directly to advertisers by email. Advertisers can now build conversion-optimized campaigns by selecting a Conversions objective, which shifts delivery toward clicks more likely to convert while still billing on valid clicks. Daily budgets are moving from a fixed daily cap to an average daily budget calculated across a rolling seven days, with automatic pacing throughout the day. The release also added geographic exclusions, Automatic Advanced Matching that improves web conversion measurement using hashed customer information, a bulk API for creating and updating campaigns and ad groups asynchronously, and a refreshed product feed card showing price and star ratings.

JumpFly Takeaway
Back in January, when ads in ChatGPT were first announced, we wrote that the platforms that deliver results are the ones with mature targeting, measurement, and optimization capabilities, and that ChatGPT ads wouldn’t have them at launch. The advice then was to be patient, watch what ad formats emerged, and be ready to test. This is the release worth testing on. Look at the list again: conversion bidding, average daily budgets, spend pacing, geo exclusions, enhanced conversions, a bulk API, and shopping cards with star ratings. That’s Google Ads. OpenAI has rebuilt the platform every advertiser already knows how to use and has done it in about seven months. Two things are worth acting on this week. The budget change happens automatically with no action required, so expect daily spend to fluctuate where it used to sit flat. Automatic Advanced Matching does not turn itself on, so go to Tools, then Conversions, then Data Source, and select “Enable for all Web data sources.” Better conversion matching is the difference between a channel you can optimize and one you’re guessing at. Being patient was the right call in January. And I think being patient even now with more capabilities is still the right call. This ad platform is so young that we are all still learning what it takes to be successful here.

5. Codex Moved to Every Desktop, and the Skill File Is What Makes It Useful for Ad Copy

Source: 9to5Mac | July 9, 2026

On July 9, OpenAI released GPT-5.6 and folded Codex into a unified ChatGPT desktop app, free on Mac and Windows to every tier, including the free plan. Existing Codex installations updated into it automatically. The app added Computer Use, which lets it work across your local files, applications, and websites, along with a built-in browser and scheduled tasks. The piece that matters most for marketing work is skills. OpenAI documents them as a SKILL.md manifest plus optional scripts, references, and assets, saved in an .agents/skills folder, alongside AGENTS.md files that hold persistent rules the agent follows every time. OpenAI’s own framing is that this delivers deterministic reliability and consistent routing. The model handles interpretation and judgment, while the saved instructions handle everything that shouldn’t vary from one run to the next.

JumpFly Takeaway
The interesting part isn’t that Codex writes code. It’s that a saved instruction file turns a general-purpose model into something that reliably produces work you can actually use. The most useful one I have built is a simple ad copy skill that knows the formats, character limits, what works in a responsive search ad headline versus a Performance Max asset, and the conventions each platform expects. It isn’t complicated to build, and that’s rather the point. The difference between that and a one-off chat is consistency. In a chat, you’re re-explaining the same context every time, and the output shifts depending on how you happen to phrase things in the moment. With the skill file, the constraints are already in place, so you get on-brand, format-correct variations on the first pass instead of the fourth. This is the same argument we made back in February: if every advertiser is running the same AI tools with the same default settings, differentiation has to come from somewhere else. Skill files are one of the clearest places it can come from. The model everyone has access to is identical. What you’ve taught it about your brand and your formats isn’t. And if I don’t mention this often, review the work before you ship!

Looking Ahead

There’s a lot happening, but the useful takeaways this month are pretty simple: Ads and citations in AI Mode don’t come as a package, so you need a plan for each. Every AI platform picks its sources differently, which means one visibility strategy won’t work everywhere. And the creative tools got fast enough that production isn’t the reason a campaign sits stuck anymore.

None of that changes the fundamentals. Clean data, good content, and someone actually reviewing the work before it goes live are still what separate the accounts that do well from the ones that don’t.

Questions about how these AI trends affect your campaigns? Let’s talk.

AI in Online Advertising: 5 Key Trends from June 2026

Post author By Jeremy Quinones
Post date July 7, 2026

AI-referred traffic is now converting at measurably higher rates than traditional web traffic, and the data is solid enough to act on. Add to that ChatGPT Ads getting product feed infrastructure as they continue to expand their platform, Facebook rewriting how discovery works inside the app, and six ad platforms connecting to AI agents through Model Context Protocols (MCPs). Here are the five most impactful stories from the month of June for online advertisers.

1. AI-Referred Traffic Is Converting at Higher Rates

Source: Reuters | June 15, 2026

The performance gap between AI-referred traffic and traditional web traffic is now measurable, and the numbers are significant. A Reuters analysis of retail and e-commerce conversion data found that shoppers arriving via AI sources (ChatGPT, Perplexity, Google’s AI Mode, and similar platforms) convert at rates approximately 42% higher than average web visitors and spend 48% more time on-site. Adobe Digital Insights’ Q2 2026 report states that AI-referred site traffic has grown 393% year-over-year across its retail client network. First Page Sage’s research on ChatGPT conversion rates by industry adds further detail: B2B software categories are seeing the highest lift, followed by financial services and home improvement. The explanation behind the data makes intuitive sense: users ask an AI assistant a specific question, receive a recommendation, and then click through with their intent already refined. They’re not browsing. They’re completing.

JumpFly Takeaway
A 42% higher conversion rate is not a rounding error. The first practical move is getting visibility into LLM traffic to your site. If you’re not already segmenting AI-referred traffic separately from your organic and paid channels in Google Analytics, you should start now (organic might be automatic, but paid ads need to be sourced). You can’t optimize what you can’t see. Beyond measurement, this reinforces why SEO still matters, and matters more than ever. Strong SEO is the foundation for strong GEO. Google itself even stated this at Google Marketing Live last month during their keynote. The AI systems recommending your brand are reading the same signals as search engines: structured product data, clear service descriptions, real reviews, and authoritative content. SEO is what truly drives GEO. The brands that have done the SEO work are the ones winning the AI organic results right now. And with the wild conversion rate numbers, you definitely need to be there. Get your SEO right. We can help.

2. Facebook Adds an AI Mode To Bring Conversational Search Into the App

Source: Meta Newsroom | June 15, 2026

Meta announced a significant expansion of AI capabilities within the Facebook app on June 15, with the most notable addition being an “AI Mode,” a dedicated conversational AI experience built directly into the platform’s search and discovery layer. Rather than returning traditional links, Facebook’s AI Mode surfaces answers drawn from the platform’s own content: public Groups, Reels, and community posts, synthesized and delivered in a conversational format powered by Meta AI. The announcement also included tools to help users manage events, coordinate group activities, and get local recommendations, all through a conversational interface that keeps users inside the app rather than routing them to external sites. Meta is positioning this as a direct response to the way users are already using AI assistants as their default discovery tool and as a way to deepen engagement with Facebook’s existing content ecosystem. This is a meaningful shift in how the platform routes discovery, and it has direct implications for how brand content surfaces.

JumpFly Takeaway
The part worth paying attention to isn’t the feature itself; it’s what it signals about where discovery is heading on every platform. Facebook is training its users to expect conversational answers instead of scroll-and-find. I, for one, am a doom scroller, so my need for AI Mode in Facebook means nothing as of today (but I’m sure that will change in the future). For advertisers, the near-term impact is that your brand’s presence in public Facebook Groups and your organic content on Reels isn’t just a community play anymore; it’s input data for the AI answering people’s questions inside the app. That also makes it yet another location where your brand content needs to be monitored for consistency. What’s showing up in Groups and Reels can surface in AI Mode responses, so if that content doesn’t reflect your brand accurately, it’s a problem. Whether Facebook eventually layers paid inventory into this experience is a question of when, not if; Meta always monetizes. This only means more potential for us advertisers in the foreseeable future. What form that takes, and what kind of results it delivers, we’ll have to wait and see. The practical move now is treating your Facebook organic content strategy as AI-readiness work and making sure what’s already out there actually reflects your brand well.

3. OpenAI Adds E-Commerce Infrastructure With Product Feeds to Its ChatGPT Ad Platform

Source: OpenAI Ads Developer Portal | June 2026

OpenAI expanded its advertising platform with product feed capabilities in June 2026. The company announced this update directly to advertisers via email and shared details on the OpenAI Ads developer portal. The update adds three meaningful capabilities: advertisers can now upload a product catalog directly into Ads Manager, build campaigns from that feed rather than creating individual ads manually, and benefit from improved conversion matching through “user objects,” a new attribution mechanism that connects purchase signals back to ad exposures more accurately than click-based tracking alone. The product feed infrastructure is a significant step toward making ChatGPT Ads a viable e-commerce performance channel rather than a brand awareness play. For context, ChatGPT processes an estimated 50 million shopping queries daily, and the platform’s existing ad inventory had been limited primarily to contextual text placements; the feed capability moves it meaningfully closer to the performance channel model advertisers are already running on Google and Meta.

JumpFly Takeaway
We covered ChatGPT Ads in our previous blog, AI in Online Advertising: 5 Key Trends from May 2026, and watching OpenAI build out the platform has been instructive. No conversion tracking, then conversion tracking, and soon the ability to optimize for conversions, and now product feed support. OpenAI has been systematically adding the infrastructure that performance advertisers need, and doing it fast. Product feeds are significant because they move ChatGPT Ads from a text placement to something that can actually compete as an e-commerce performance channel. The 50 million daily shopping queries flowing through ChatGPT now have a direct path to your catalog. Making it easier for users to purchase is the right call in my opinion. I love e-commerce. I love optimizing Shopping and Performance Max campaigns, and this is absolutely something I will be testing in the very near future.

4. Gemini Omni in the Real World: My Tests Over the Last Month

Source: Google Blog | May 19, 2026 (real-world testing: June 2026)

Google introduced Gemini Omni at Google I/O 2026, a video generation and editing model that takes input from any combination of text, images, audio, and existing video and then responds through natural conversational language. The defining capability is multi-turn editing: each prompt builds on the last, characters stay consistent across changes, and the scene retains context throughout the session. This allows users to change environments, add or remove elements, shift visual style, or alter what’s happening in a clip without returning to a production set. The model also includes improved physics reasoning, handling realistic movement, gravity, and fluid dynamics. Gemini Omni Flash is rolling out now to Google AI Plus, Pro, and Ultra subscribers through the Gemini app and Google Flow, with free access on YouTube Shorts and YouTube Create. All outputs carry Google’s SynthID watermark.

JumpFly Takeaway
I tested Gemini Omni inside Google Flow using the Gemini agent, and the results are worth sharing in detail. For b-roll content and bringing still product images to life, the output was genuinely good: quality was strong, style was controllable, and the speed was real. It did take some tweaking and multiple iterations, but the result was usable. The gap showed up when we introduced people. Characters looked great on the first pass, but minor inconsistencies appeared, like character consistency within the same scene it generated. There was also an instance where users were holding red wine, and then suddenly it became white wine. When we prompted the model to fix a specific inconsistency, it addressed some issues while introducing others. The fix wasn’t reliable. The trust-but-verify rule applies here: review everything before it goes live, especially anything with people in it. For b-roll, product animation, and environmental scenes, it’s worth getting into now. Just don’t skip the review step.

5. Six Ad Platforms Now Have Official MCP Servers

Source: Pinterest Newsroom + Microsoft Advertising Blog | June 17, 2026

Pinterest and Microsoft Advertising each launched official Model Context Protocol (MCP) servers on June 17, 2026, bringing the total number of major ad platforms with first-party MCP servers to six, alongside Google Ads, Amazon Ads, Yahoo DSP, Meta, and TikTok. MCP, originally developed by Anthropic and now governed by the Linux Foundation, is a standardized connection layer that lets any compatible LLM/AI agent connect directly to a platform and read live campaign data without custom API development for each model. Both Pinterest and Microsoft launched as read-only, meaning AI agents can pull performance data, account health signals, and optimization insights, but cannot change bids, budgets, or campaign settings. Google, Amazon, and Yahoo took the same read-only-first approach; Meta and TikTok are the exceptions with full read/write capability.

JumpFly Takeaway
So how can an MCP help? Instead of manually logging into six dashboards to pull reports, an MCP-enabled agent can read across Pinterest, Microsoft, Google, Amazon, and others in a single session and surface what needs attention. It provides quick analysis and recommendations through whatever LLM you’re working with, which is very useful. But the LLM doesn’t know your client history, your account nuances, or whether a flagged budget pacing issue is actually worth acting on. That’s where the marketer has to stay in the loop. Trust but verify. The speed of AI analysis is real, and it does allow for quicker review and faster identification of opportunities, but so is the expertise required to evaluate what the AI is actually telling you. At JumpFly, we have our own proprietary tool to help with analysis and recommendations, but we do not blindly accept what the LLM tells us. It is very good and surely helps all of us out on a day-to-day basis. Knowing what to do with an AI recommendation is still a marketing skill learned through experience.

Looking Ahead

The common thread in June isn’t the technology; it’s the judgment required to use it well. Knowing when AI video output is good enough versus when it needs another pass. Knowing whether an MCP recommendation is worth acting on or just plausible-sounding. Knowing that SEO isn’t less important in the age of AI, it’s actually more important. The tools are genuinely useful, and the speed gains are real. None of that removes the need for someone who knows what they’re looking at. That’s been true through every platform shift for the past 20 years, and it’s still true now.

Questions about how these AI trends affect your campaigns? Let’s talk.

AI in Online Advertising: 5 Key Trends from May 2026

Post author By Jeremy Quinones
Post date May 28, 2026

Google I/O and Google Marketing Live (GML) both landed this month, and they arrived with tons of new AI innovations. Between a new video model that lets you edit footage through conversation, a Universal Cart that turns Google into a checkout layer, and ChatGPT officially becoming accessible to more advertisers, May 2026 is one of the more active months in the space of AI in digital marketing. Here are the five most impactful stories for online advertisers.

1. Google Marketing Live 2026: Ads Move Inside the AI Conversation

Source: Google Blog | May 20, 2026

Google Marketing Live 2026 delivered on its framing: Gemini is no longer a layer on top of Google’s ad products; it is the operating system underneath all of them. The most consequential announcements for advertisers were a new generation of ad formats built for AI Mode and conversational search. Conversational Discovery ads and Highlighted Answers are now in U.S. testing on mobile and desktop, embedding ads directly into AI-generated search experiences rather than running alongside them. Business Agent for Leads, now in open beta for U.S. advertisers, puts a Gemini-powered chat agent inside your search ad. Instead of clicking through to a form or a landing page, a user researching a complex purchase can get product questions answered by your brand in real time from within the search result. Google also expanded its Direct Offers pilot with AI-generated bundles and native checkout. On the tooling side, Google launched Ask Advisor, a unified Gemini assistant that connects Google Ads, Analytics, Merchant Center, and the Google Marketing Platform into a single conversational interface for campaign planning and optimization. The Universal Commerce Protocol (UCP) was integrated into Demand Gen campaigns, YouTube Shopping, and AI Mode, with new Merchant Center “Conversational Attributes” designed to help products surface in AI-driven search.

JumpFly Takeaway
One line from the keynote has stayed with me: “The only way to win in the age of AI, is with AI.” I’ve been using AI tools across my work and personal life long enough to know that’s less of a slogan and more of a description of what’s already happening. Business Agent for Leads puts a Gemini-powered version of your brand inside the search result; the user never leaves to fill out a form. Conversational Discovery ads embed inside AI Mode responses. The ad isn’t running next to the answer anymore. It is the answer. The brands that start feeding quality inputs into Performance Max and AI Max now, and get in early on the new formats, are the ones who will have 12 months of learning data while everyone else is just getting started. I will be testing nearly every new format from GML. I want that advantage within AI Mode and AI Overviews, especially with Google expanding conversation search at Google I/O (larger text box, more AI-forward vs traditional search).

2. OpenAI Opens Its Ad Platform: ChatGPT Is Now a Real Advertising Channel

Source: OpenAI | February 2026, expanding through May 2026

OpenAI officially began testing ads inside ChatGPT in February 2026, and the rollout has continued expanding through May with the launch of an Ads Manager platform that moves the channel from invite-only testing toward self-serve buying for a wider set of advertisers. OpenAI is targeting $2.5 billion in advertising revenue for 2026. Retail and consumer goods brands have dominated early inventory, with excluded categories including health, financial services, and political advertising. ChatGPT handles an estimated 50 million daily shopping queries, and the platform is the first major AI assistant to move from ad concept to a commercially available, self-serve ad product.

JumpFly Takeaway
ChatGPT has a massive user base; who does not want to advertise on such a large platform? As a marketer, this is a place that naturally makes sense for many, if not all, businesses to advertise on. You do need to apply and get approved (sometimes waiting up to a week to get approved; check those spam folders), and the limited interface is not overly exciting, but this will only improve and create more opportunity to expand revenue and/or leads. Approach it the way you’d approach any new channel, with a contained test budget and clear KPIs. Be an early adopter, start learning the platform, get ahead. The advertisers who have already run a few campaigns when the channel fully opens up will have a meaningful head start on everyone who waited to see how it played out.

3. Google Launches Gemini Omni: Conversational Video Editing That Could Change How Advertisers Produce Creative

Source: Google Blog | May 19, 2026

Google introduced Gemini Omni at Google I/O 2026, a new model that can generate and edit video from any combination of inputs: text, images, audio, and existing video, using natural conversational language. The first model in the family, Gemini Omni Flash, is rolling out now to Google AI Plus, Pro, and Ultra subscribers through the Gemini app and Google Flow, and at no cost to users on YouTube Shorts and YouTube Create. The core capability that sets Omni apart from earlier video tools is multi-turn editing: Each instruction builds on the last, characters stay consistent across changes, and the scene retains context throughout the conversation. You can change the environment, add or remove elements, shift the visual style, or alter what’s happening in the video, all through natural language prompts, without going back to a production set. The model also brings improved physics reasoning, handling realistic movement, gravity, and fluid dynamics. All outputs carry Google’s SynthID watermark. API access for developers and enterprise customers is rolling out in the coming weeks.

JumpFly Takeaway
The specific capability worth paying attention to here is the multi-turn editing. Video ad creative has always had a production problem; once you’ve shot a spot, updating it for a new season, a new product variant, or a new market means going back to set or paying an editor. Omni changes that dramatically. The ability to type “change the background to a winter scene” or “swap the product color to red” and have the model carry that change through the clip consistently is genuinely new. Check out the videos; it is wild to see video editing made so simple.For advertisers managing high-volume creative across multiple SKUs or seasonal campaigns, this is a meaningful compression of production time and cost. But as we like to say over here, “Trust, but verify.” Don’t accept every output without checking it carefully, especially for brand consistency. But as a way to refresh existing creative quickly, test new seasonal variants before committing to a full production, or produce platform-specific cuts from a single hero asset, Gemini Omni is worth checking out today.

4. Pinterest Posts Its Best Quarter in Years: AI Ad Tools Are Moving the Numbers

Source: LinkedIn News, CNBC | May 4, 2026

Pinterest reported Q1 2026 results that beat Wall Street estimates on every major metric, posting $1.01 billion in revenue, an 18% year-over-year increase that surpassed analyst projections of $966 million. Global monthly active users grew 11% to 631 million, and the company’s Q2 guidance also came in above expectations. The growth is being directly attributed to Pinterest’s investments in AI-powered ad targeting and performance tools, which have improved return on ad spend enough to pull incremental budget from advertisers who had previously treated the platform as an afterthought. The results come against real headwinds: Pinterest cut 15% of its workforce earlier this year, and activist investor Elliott Management took a $1 billion stake in the company. Against that backdrop, Q1 showed that AI-driven ad improvements are producing results measurable enough to change how advertisers allocate budget.

JumpFly Takeaway
Don’t sleep on Pinterest Ads. It’s a platform that JumpFly works with and has seen success on. An 18% revenue jump and 631 million monthly active users is not a platform in decline, it’s a platform that got its product right enough to start winning back advertiser confidence. But since I am focused on the AI spin of this, the specific driver worth paying attention to is the AI targeting improvement. Pinterest’s inventory has always had strong purchase intent baked in because users are actively planning purchases when they use it. Better AI targeting means better matching between that intent and the right ad at the right moment. If you’re in e-commerce, home, fashion, food, or any category where visual discovery drives decisions, Pinterest deserves a real performance test right now, not the leftover allocation it usually gets. Run it with proper conversion tracking, treat it like a performance channel, and see what the AI tools actually do to help with incremental growth.

5. Google Launches a Universal Cart, and It Works Across Every Store at Once

Source: Google Blog | May 19, 2026

Google announced Universal Cart at Google I/O 2026, a single intelligent shopping cart that works across Search, Gemini, YouTube, Gmail, and other Google surfaces, letting shoppers browse and buy from multiple merchants in one transaction without leaving Google’s ecosystem. The cart is powered by Gemini models that actively surface deals, track price drops, and retrieve purchase history to help users make decisions. Checkout is built on the UCP. Payments run through a new Agent Payments Protocol with built-in spending limits and authorization controls. Merchants remain the merchant of record for every transaction. The cart is rolling out to U.S. shoppers this summer.

JumpFly Takeaway
I feel like Google tried this in the past, but this is different. You can buy from numerous stores in one view vs navigating to multiple sites to complete the purchase. That is the win that Google is trying to push. For advertisers and retailers, the implication is straightforward: if your products aren’t surfacing inside Google’s AI-powered discovery experience, you’re not in the cart. And the way products get surfaced is the same as it’s always been, feed quality. Gemini isn’t browsing your website to decide what to recommend. It’s reading your product data: titles, descriptions, pricing, availability, and merchant ratings. Even adding in the new “conversational attributes” will be important. The merchants who show up in this cart will be the ones whose data is clean, complete, and structured correctly in Merchant Center. I’ve said this before: The feed is that much more important in the age of AI. The robot is out shopping on behalf of the user, so clean data is imperative. This is why the JumpFly Feed Management service exists.
A shopper who adds your product to the universal cart doesn’t need to go to your website, compare alternatives, or reconsider at checkout; that can happen conversationally now. Adopting UCP is important to allow your products to be purchased via the Universal Cart. These concepts are all new to everyone navigating the ongoing changes with AI. I encourage you to learn about this and adopt what might be the new future.

Looking Ahead

The shift happening across May’s stories is the same one: AI is moving from “just a chat” to the transaction layer itself. Google is becoming a checkout surface. ChatGPT is a real media buy. Pinterest’s AI tools are moving ROAS numbers. Gemini Omni is compressing video production timelines that used to take weeks. We’ve been positioning our team and our clients to be AI-ready and AI-fluent, not because it sounds good, but because the gap between the advertisers who are and the ones who aren’t is widening faster than most people realize.

Questions about how these trends affect your campaigns? Let’s talk.

AI PPC

ChatGPT Ads Are Here: Why Brands Should Move Early on AI Advertising

Post author By Miranda Schirmer
Post date May 21, 2026

The next major shift in digital advertising has already started.

OpenAI’s rollout of ChatGPT ads signals the beginning of a new advertising channel centered around conversational AI, and brands that move early may have a significant advantage as adoption grows.

For years, advertisers competed for visibility across search engines and social platforms. Now, consumers are increasingly turning to AI tools like ChatGPT to research products, compare solutions, discover brands, and make purchasing decisions. That shift is creating entirely new opportunities for advertisers to reach customers during high-intent discovery moments.

At JumpFly, we’re actively preparing brands for this next phase of digital advertising and will be managing ChatGPT advertising strategies for clients as the platform continues expanding its advertising capabilities.

While ChatGPT advertising is still in the early stages, history shows that early adopters on emerging ad platforms often gain advantages before competition increases and inventory becomes more crowded. Businesses that begin learning, testing, and adapting now may be better positioned as conversational AI advertising evolves.

In this post, we’ll break down what ChatGPT ads are, how they currently work, why they matter, and what advertisers should be paying attention to right now.

What Are ChatGPT Ads?

OpenAI recently confirmed it is testing ads inside ChatGPT for users on its Free and Go subscription tiers in the United States. According to OpenAI, the ads are intended to support broader access to ChatGPT while maintaining a strong focus on user trust and privacy. Paid tiers including Plus, Pro, Business, Enterprise, and Education remain ad-free.

ChatGPT ads currently appear as clearly labeled sponsored placements positioned alongside AI-generated responses rather than embedded directly within them. OpenAI has stated that ads do not influence chatbot responses and are visually separated from organic answers.

The rollout remains in an early testing phase, though advertisers and users are already beginning to see sponsored placements appear across expanding ChatGPT experiences. While the current format is still relatively limited, the launch signals growing momentum around conversational AI monetization and emerging advertising opportunities.

Why ChatGPT Ads Matter for Digital Marketers

The introduction of ads into ChatGPT represents more than another media placement opportunity. It points to a broader shift in how users can engage with brands online.

Traditional search advertising has long centered around keywords, landing pages, and search engine results pages. Conversational AI changes that experience significantly.

Instead of typing fragmented search terms like:

“best CRM software for small business”

Users are increasingly asking complete, conversational questions such as:

“What’s the best CRM for a growing company with remote sales reps?”

This creates opportunities for brands to appear during highly contextual conversations where user intent may be more specific and detailed than in traditional keyword searches.

As AI adoption continues to grow, marketers should prepare for a future where discovery increasingly happens inside conversational interfaces alongside traditional search engines.

ChatGPT has become one of the fastest-growing consumer technology platforms in recent years, and continued platform growth will likely accelerate advertiser interest as OpenAI expands monetization efforts.

Why Early Adoption Could Matter

Digital advertising history tends to reward brands that adapt early.

Companies that invested early in Google Ads, Facebook Ads, Amazon Ads, YouTube advertising, and TikTok advertising often benefited from lower competition, lower costs, and stronger visibility before those platforms became saturated.

Conversational AI may follow a similar pattern.

As more consumers use AI tools to research products and services, advertisers that establish a presence early will likely gain valuable insights into performance, audience behavior, and emerging advertising formats before the market becomes more competitive.

This doesn’t mean businesses should shift budgets recklessly into unproven channels. It does mean marketers should begin paying close attention to how AI-driven discovery is changing customer behavior.

How ChatGPT Advertising Could Evolve

Although the current rollout remains limited, marketers should expect ongoing changes as OpenAI continues testing and refining the platform.

Potential developments may include:

1. Conversational Sponsored Recommendations

Future ChatGPT ad experiences may evolve beyond static sponsored placements into more contextually relevant recommendations based on user prompts and intent.

For example:

Travel brands appearing in trip-planning conversations
SaaS platforms recommended during software research
Ecommerce products surfaced during buying-related queries

This type of contextual alignment could create new opportunities for advertisers focused on reaching users during high-intent research moments.

2. AI-Powered Audience Targeting

OpenAI has stated that ad personalization settings will remain under user control and that conversations will stay private. As the platform evolves, contextual targeting tied to conversation topics may become an important differentiator for advertisers.

This could allow brands to reach users based on active interests and research behavior rather than relying exclusively on traditional keyword targeting models.

3. New Attribution Challenges

One of the biggest questions surrounding AI advertising is attribution.

Unlike traditional search ads that drive clicks directly from search engine results pages, conversational AI interactions may involve:

Longer research journeys
Fewer direct clicks
More assisted conversions
Multi-step recommendation paths

As AI-assisted discovery grows, marketers will likely need updated attribution models that better account for cross-channel influence and longer decision-making cycles.

Challenges and Concerns Around ChatGPT Ads

Like any emerging platform, ChatGPT advertising raises important questions for advertisers, users, and the broader digital marketing industry.

User Trust

OpenAI has repeatedly stated that ads will not affect response quality or objectivity. Maintaining user trust will remain critical as advertising expands across conversational AI platforms.

If sponsored experiences become overly intrusive or reduce perceived credibility, user engagement could be affected over time.

Privacy Considerations

AI conversations can contain highly personal or sensitive information. OpenAI says users will have controls around personalization and data usage, and ads will be excluded from sensitive categories.

Privacy and transparency will remain major areas of focus as AI advertising platforms continue developing.

Platform Uncertainty

The advertising ecosystem inside ChatGPT is still in the early testing phase. Features, targeting capabilities, reporting tools, and ad formats will likely evolve significantly over time.

For marketers, this means balancing curiosity and experimentation with realistic expectations about platform maturity.

Conversational AI Is Becoming Part of the Digital Advertising Landscape

The launch of ChatGPT ads marks an important development in the evolution of digital advertising.

While the platform is still developing, conversational AI is already influencing how consumers research products, discover brands, and make purchasing decisions online.

For businesses willing to adapt early, this creates opportunities to understand emerging consumer behavior better and prepare for future advertising environments shaped by AI-driven discovery.

At JumpFly, we’re actively tracking developments across AI advertising, paid media, search, and emerging digital platforms. As ChatGPT advertising evolves, JumpFly will be helping clients navigate this emerging channel with strategies designed around visibility, performance, and long-term growth.

As conversational AI becomes more integrated into everyday search and research behavior, marketers who understand intent, content relevance, and evolving user journeys will be better positioned for long-term success.

AI in Online Advertising: 5 Key Trends from April 2026

Post author By Jeremy Quinones
Post date May 6, 2026

The last month was a big month for AI tools inside the platforms you’re already using. Google is retiring Dynamic Search Ads (DSA) and pushing everyone to AI Max. Amazon turned on ads inside Rufus. And TikTok, Meta, and Google all shipped AI video and creative tools directly into their ad interfaces. These tools are live right now and available to any advertiser. Here are the five most impactful stories.

1. Google Is Retiring Dynamic Search Ads and Automigrating to AI Max in September

Source: Google Blog | April 15, 2026

Google announced this week that it will retire Dynamic Search Ads and automatically migrate eligible campaigns to AI Max for Search starting in September. AI Max combines broader search term matching, AI-generated text customization, and final URL expansion, and has been adopted by hundreds of thousands of advertisers since exiting beta this month. Google’s internal data shows an average 7% lift in conversions or conversion value at similar CPA/ROAS when advertisers use the full feature suite. The migration covers campaigns running DSA, automatically created assets (ACA), and campaign-level broad match settings, with all upgrades expected to be completed by the end of September. Once the automatic upgrades begin, new DSA campaigns can no longer be created through Google Ads, Ads Editor, or the API.

JumpFly Takeaway
In my own testing, AI Max has been generally positive. CPCs have frequently dropped, and conversions have been flat to incrementally better, which is a solid outcome when you’re also paying less per click. If you’re still on DSA, the play isn’t to wait and flip a switch in August. Start testing now so you’re familiar with the setup and have months of performance data accrued before the forced migration. Going into Q4 cold on a brand-new campaign type is a risk you don’t need to take. Get the reps in now.

2. Amazon Launches a New AI Ad Format Inside Rufus

Source: Ad Age | March 25, 2026

Amazon launched Sponsored Products Prompts and Sponsored Brands Prompts in the U.S. on March 25, making paid placements inside Rufus, its AI shopping assistant, generally available to all advertisers. The format places ads directly within Rufus conversations when shoppers ask product-related questions, billed at standard CPC rates. Advertisers running existing Sponsored Products or Sponsored Brands campaigns were automatically enrolled with no setup required. Rufus handles an estimated 274 million daily queries, and Amazon’s data shows sessions involving Rufus are twice as likely to result in a purchase. Full reporting is available in the Ads Console, including impressions, CTR, spend, ACOS, ROAS, and 7-day orders.

JumpFly Takeaway
I had a chat with our Director of Amazon, and he has not yet seen Sponsored Products Prompts or Sponsored Brands Prompts appear in accounts, which suggests the rollout is moving more slowly than the announcement made it sound. So don’t panic if you’re not seeing it yet. What’s more immediately interesting is the data angle. Rufus is an AI-powered shopping assistant that has real conversations with shoppers, and now you can start to see what questions those shoppers are actually asking. That data is genuinely valuable, just like it is for any keyword-based campaign that we can mine for additional keywords or add in negatives. The questions are not just for understanding the placement, but for informing how you write your PDPs. If you know what questions buyers are asking Rufus in your category, you can answer those questions directly in your product listings and (hopefully) get surfaced more frequently. That work pays off regardless of when the ad format and data fully roll out.

3. TikTok Integrates Seedance 2.0 Into Symphony

Source: MediaPost | April 15, 2026

TikTok announced that it has integrated Dreamina, powered by ByteDance’s Seedance 2.0 video model, directly into its Symphony Creative Studio, expanding the suite from script and concept generation into full branded video automation. Advertisers can now input text prompts, product images, or reference clips and receive a finished video with synchronized audio in a single pass. The update is available globally to all paid TikTok advertisers and requires no additional setup beyond what’s already in TikTok Ads Manager. TikTok says the model was built to maintain product consistency across video segments, an important factor for brand recognition in short-form content. Every output is automatically labeled with AI disclosures, invisible watermarking, and C2PA Content Credentials. Advertisers can reject any generated video before it goes live.

JumpFly Takeaway
If you have strong product photography but no video pipeline, that gap just got a lot cheaper to close. The Seedance 2.0 model is the same underlying technology we covered in our recent post, AI in Online Advertising: 5 Key Trends From February 2026, when it was announced, but the difference now is that it’s baked directly into TikTok’s ad tools, with no third-party workflow required. Teams that have been limited by video production bandwidth can now generate and test multiple creative variants from a single image. The caveat worth keeping in mind: AI-generated video still tends to work best for product-forward content rather than brand storytelling that requires emotional nuance. But Seedance 2.0 is definitely a level up in quality. Start with your highest-volume SKUs, test a few outputs before committing budget, and use the rejection option; the model isn’t perfect on every pass.

4. Meta Launches AI Video Creation Tools Inside Ads Manager

Source: MediaPost | March 30, 2026

At IAB NewFronts, Meta unveiled a significant expansion of its AI creative capabilities inside the Ads Manager interface. Advertisers can now apply AI-generated voiceovers to existing video assets, create UGC-style videos using AI avatars from a product image, and automatically generate Reels video ads for every product in a catalog, without shooting a single piece of footage. Meta also announced AI-powered translation tools that apply voiceover and text overlay translations to existing video, making multilingual creative production significantly faster. Separately, on April 15, Meta announced an AI-assisted upgrade to the Meta Pixel and a one-click setup path for the Conversions API with changes designed to reduce the technical overhead that has historically separated well-resourced advertisers from leaner teams. Meta has stated its goal is to reach fully automated end-to-end ad creation by the end of 2026.

JumpFly Takeaway
Yes, more tools. But more tools for us to leverage with the help of AI, which, to me, is not a bad thing. All of Meta’s creative announcements are about speed: the ability to scale video and creative faster than was possible before, including voiceovers from existing assets, product videos from a catalog, and UGC-style content from a single image. Each of these removes a production step that used to require time, budget, or a vendor. You should absolutely take advantage of them. The one rule that applies to all of it: don’t accept the first output blindly. Review everything before it goes into a campaign. But as a way to test creative directions quickly and generate more variants than you could otherwise afford to produce, these tools are exactly what they should be. We technically do not all need to be masters of every domain, or suddenly be the greatest ad creators, but at least knowing these tools exist is important for prototyping.

5. Google Veo 3.1 Is Now Inside Google Ads

Source: JumpFly Blog | April 15, 2026

Google has integrated Veo 3.1, its AI video generation model, directly into the Google Ads interface. Advertisers can now generate video assets from a text prompt or animate a static image already in use across their campaigns, and no production team or external tool is required. The feature sits alongside Nano Banana, Google’s AI image generation tool, which is also now built into Google Ads and available for use across campaigns and image extensions. Together, they give advertisers the ability to produce both image and video creative from within the platform. Veo 3.1 generates up to 8-second clips and is designed for product showcases, social ads, and short-form brand content. Google Ads limits some of the fine-tuning options available when building inside the interface. The full model with more control is accessible through Google Vids and Google Flow.

JumpFly Takeaway
We recently did a webinar walking through Veo in action, and the honest takeaway is that we really like it, but with the right expectations. It’s excellent for prototyping, great for b-roll, and a genuinely fast way to animate a static image into something usable. However, you cannot accept outputs without thoroughly reviewing them first. There’s often some wonkiness – motion that looks slightly off, details that don’t hold up on close watch. So review everything. But here’s the bigger point: Veo can help any advertiser get a project off the ground in minutes. Not a polished final spot, but a workable starting point that would have previously taken days and a production budget to achieve. That’s the value. If you’ve been putting off video because of the lift involved, Veo removes most of that barrier. We are happy to help with some of this prototyping to get the content you actually want.

Looking Ahead

The common thread this month isn’t any single platform; it’s that AI creative tools have moved from external experiments into the ad interfaces you’re already logged into every day. Video generation, image generation, voiceovers, and catalog automation are no longer things you need a separate tool or a production budget to access. They’re in Google Ads, in TikTok Ads Manager, in Meta’s Ads Manager, available right now. The advertisers building that process now will have a meaningful head start as these tools mature and the volume advantage compounds. We’d love to help navigate these conversations. AI does not sleep, and AI is not going away, so we want to help make it accessible to everyone!

Questions about how these trends affect your campaigns? Let’s talk.

Stay tuned for more of the latest AI trends in paid advertising each month. Read my previous post, AI in Online Advertising: 5 Key Trends from March 2026.

AI in Online Advertising: 5 Key Trends from March 2026

Post author By Jeremy Quinones
Post date March 30, 2026

March was a busy month for AI in advertising. AI shopping agents moved from conference demos into real consumer behavior, Google shipped new image generation tools and gave a candid interview about the future of ads in Gemini, and the data on AI Overviews’ effect on search clicks kept piling up. Here are the five developments online advertisers should be paying attention to.

1. AI Shopping Agents Are Here, and They’re Already Changing How People Buy

Sources: TechCrunch | March 16, 2026; NVIDIA | March 16, 2026

Agentic shopping moved from theory to practice this month. Shopify president Harley Finkelstein told an audience at the Upfront Summit that the company is going all in on AI shopping agents, calling them the future “personal shoppers” that will serve as a new front door for e-commerce. Shopify is building protocols so agents can understand merchant product data and act on behalf of consumers. Meanwhile, NVIDIA announced NemoClaw at GTC 2026, an enterprise-grade runtime that adds security and privacy guardrails to open-source AI agents like OpenClaw. The platform, which has racked up over 135,000 GitHub stars, lets users automate tasks through messaging apps like Telegram, WhatsApp, and Slack. At the retail level, Target is collaborating with OpenAI, and Walmart has partnered with Google’s Gemini on agentic commerce initiatives.

JumpFly Takeaway for Marketers
This is something I’ve been testing personally. Recently, I used an OpenClaw-style agent through Telegram while I was driving. I sent a message asking it to find a specific board game at my local Target. Within minutes, the agent browsed available inventory at that store, identified the exact aisle location, pulled up pricing and customer ratings, and even flagged a current sale. I never opened Target’s app, never visited Target.com, and never saw a single ad. The entire shopping journey happened inside a messaging app. Agentic shopping is only going to evolve from here. The practical move for advertisers is to focus on what these agents actually consume: structured data. A well-organized product feed, accurate Merchant Center data, and an easy-to-navigate site are what put you in front of an AI agent’s recommendation. As more consumers let agents do the browsing for them, the brands with clean data will be the ones that get surfaced.

2. Google Rolls Out Nano Banana Pro, Its Most Advanced AI Image Generator, Directly in Google Ads

Source: Google Business | March 2026

Google has made Nano Banana Pro available to all active Google Ads users through Asset Studio. The model lets advertisers generate photorealistic product images using conversational editing, meaning you describe the changes you want in plain language and the AI delivers them. Google says Nano Banana Pro can render fine details like text on product labels and packaging, maintain product fidelity from original assets, and compose scenes featuring up to five products in a single lifestyle image. The tool also supports creating seasonal ad variations from existing top-performing creatives without rebuilding from scratch. Early adopters report using it to rapidly test creative hypotheses that would previously have required a full design cycle.

JumpFly Takeaway for Marketers
Having Nano Banana Pro directly in Google Ads is a potential game-changer (this is my catchphrase). With the Pro version of Nano Banana, you can iterate on creative quickly, stay within one platform, and there’s no extra cost to use it. We run a lot of Performance Max and Demand Gen campaigns, which are creative-heavy by nature, so anything that speeds up asset production without sacrificing quality gets our attention. Being able to describe the image you want in plain language and getting a usable result is a step beyond what previous AI image tools have offered. We’d still recommend reviewing every generated image before it goes live, but blend this into what you’re already doing, and let it shorten your testing cycles.

3. AI Overviews Are Quietly Eating Search Clicks

Source: Semrush | Updated March 2026

The data on AI Overviews is getting harder to ignore. When AI Overviews appear on a search results page, click-through rates on the listings below drop by roughly 42%, according to Semrush research. AI Overviews now show up for about 13% of all Google queries, and ads appear alongside 25.5% of those AI Overview results, up from just 5.17% earlier in 2025, a 394% increase. At the same time, Google VP of Ads Dan Taylor confirmed that ads within AI Overviews are now monetizing at the same rate as traditional search ads, and Q4 2025 search revenue climbed 17% year over year. The zero-click trend is accelerating: users are getting answers directly from the AI-generated summary and never scrolling down. For advertisers and SEO-driven brands alike, the math on organic traffic is changing.

JumpFly Takeaway for Marketers
I’ve personally seen numerous accounts drop in organic search sessions year over year. It’s hard to look at that data and blame poor management when the timing lines up so neatly with AI Overviews rolling out. Users are getting their answers right there in the AI summary and never clicking through. Having the right SEO and AEO (AI Engine Optimization) strategy is no longer optional. This is not going away. If your content is structured to answer questions directly, with clean product data and authoritative information, you have a much better shot at being the source an AI Overview pulls from. If your SEO strategy has been focused purely on traditional blue-link rankings, it’s time to broaden your thinking to include how your content appears inside AI-generated answers, not just below them.

4. Google Is Not Ruling Out Ads in Gemini

Source: WIRED | March 2026

In an interview with WIRED, Google SVP Nick Fox said the company is “not ruling out” ads in the Gemini app. Fox noted that learnings from the company’s ongoing ad experiments in AI Mode would “likely carry over” to Gemini down the road. Google is currently testing ads in AI Mode, its search experience powered by Gemini, but the Gemini standalone app remains ad-free for now. Fox described a three-part approach to AI and advertising: better measurement (understanding how AI is already driving value), better advertiser tools (AI helping small businesses build campaigns), and ads in new experiences, which he called “the most nascent” of the three. Separately, Google confirmed that users who enable Personal Intelligence, a feature that connects Gmail, Photos, and YouTube to AI Mode, will not see ads in that experience.

JumpFly Takeaway for Marketers
My gut says it’s only a matter of time before ads show up in Gemini. Google has too much incentive and too much infrastructure not to go there eventually. The Personal Intelligence detail is interesting, though. Google is creating two tiers within AI Mode: one with ads, one without. That mirrors what we’ve seen with ad-supported vs. premium tiers on streaming platforms. For now, there’s nothing to change in your campaigns. But we’ll be here waiting to capitalize on marketing within the platform the moment it opens up.

5. 63% of U.S. Adults Say Ads in AI Search Make Them Trust Results Less

Sources: eMarketer | March 2026; Ipsos | 2026

An Ipsos survey found that 63% of U.S. adults say ads in AI search results make them trust the results less. Fewer than a quarter said ads had the opposite effect. This data sits behind one of the bigger strategic splits in the AI industry right now. Perplexity, the AI search startup valued at $18 billion, has effectively abandoned its advertising program, with its ad chief departing within nine months and the company saying it may never need ad revenue given its subscription growth. Meanwhile, OpenAI is moving in the opposite direction, actively building out an ad infrastructure for ChatGPT. Google is threading the needle with its Personal Intelligence play, offering an ad-free AI experience for users who connect their data. The question the industry is wrestling with: can ads coexist with trust in AI-generated answers?

JumpFly Takeaway for Marketers
I must fall in the other 37%. Here’s the reality: most people can’t afford to pay for every AI platform they use. Ads are what keep these tools free. And personally, I’d rather see ads that are relevant to me than pay another subscription fee. It’s not like the ad is going to be blatantly dropped in the middle of an AI response, because if it were, users would stop using the tool. These companies know that. The ones that get the ad experience right, where it feels helpful instead of intrusive, will keep their users. For advertisers, the takeaway is to keep testing these placements where/when they’re available. ChatGPT Ads are just getting started, and Google is already showing ads in AI Overviews; we just cannot see the attributed data (yet). The platforms that maintain user trust will be the ones worth investing in long-term.

Looking Ahead

The through-line this month is that the surface area where traditional ads work is shifting. AI agents are finding products through messaging apps. AI Overviews are answering questions before users click, and this number continues to grow. And consumers are telling pollsters they don’t trust ads mixed into AI results. The core principles haven’t changed, though. Clean data, strong product information, and real authority still win. How those signals get delivered to buyers is just evolving faster than it has in a long time.

Follow along each month as we share our insights into the latest AI trends. You can read our previous blogs: 5 Key Trends from January 2026 and 5 Key Trends from February 2026.

If you missed last month’s post, read our article, AI in Online Advertising: 5 Key Trends from January 2026.

Questions about how these trends affect your campaigns? Let’s talk.

AI Social

Beyond the Super Bowl: The Strategic Role of AI in Social Ads

Post author By Clo Johnson
Post date March 10, 2026

Technological advances typically leave viewers in awe; however, during Super Bowl LX, the latest tech strides left mixed reactions among viewers, prompting questions about whether the biggest stage in marketing is the right place for it.

When Innovation Steals the Spotlight

Beyond watching the action on the field and dancing to the halftime entertainment, the commercials tend to have a lasting impact. For years, they’ve been deemed the cultural centerpiece of storytelling, originality, and emotional resonance. This year, the formula was disrupted. Early into the program, viewers quickly caught onto a trend within the first quarter. The innovation began to feel repetitive. “It felt as if every commercial break featured some kind of advertisement for AI,” Karl Rasmussen of Sports Illustrated writes.

According to iSpot data, 15 out of 66 commercials, approximately 23%, were AI-related. It soon became no secret that the big corporations turned to using generative AI this year since it provides a cheaper and quicker production timeline. With 30-second Super Bowl ad placements ranging from $8 to $10 million, the pressure to streamline creative development is understandable.

From Behind the Scenes to Center Stage

What was once used for improving efficiency and optimization behind the scenes has now broken the fourth wall by coming to the center of the largest advertising stage. With mixed responses from viewers, it suggests that AI does have a powerful role in modern marketing, but its placement and execution matter and need to be considered by the marketer. Ironing out those finer details showcases AI’s positive impact.

So, is there a time and a place for AI in advertising?

Time and Place: Where AI Makes the Most Impact

Just like any new tool and resource, it appears that AI-generated content may not inherently be the problem. Instead, it’s about time and place. While the Super Bowl remains a stage that is still undergoing as an AI testing ground, social media and interactive media channels are built for this type of iteration.

In the different social environments, we’ve seen speed, testing, and optimization being rewarded. As of late, AI content has become a strategic advantage because it has the ability to generate creative variations at large. In social media, this type of efficiency is valuable in a performance-driven channel, where experimentation fuels results.

Perception Matters: Big Brands vs. Small Businesses

Placement and perspective both play an important role in how AI-generated content is perceived. While it can be difficult to sympathize with large corporations using AI primarily as a cost-cutting measure, the conversation often feels different when it comes from small and mid-sized businesses.

For many smaller brands, AI is not about replacing creativity. It is about maximizing limited resources. These business owners typically operate with tighter budgets, leaner teams, and less bandwidth. They are looking for ways to work smarter, move faster, and compete in increasingly crowded digital spaces.

When viewed through that lens, AI feels less like a shortcut and more like a strategic advantage. For smaller businesses trying to break through the noise and reach new audiences, using AI as a resourceful tool can be practical, necessary, and even empowering.

The Creative Bottleneck in Social Advertising

We see firsthand that one of the biggest challenges clients face is consistently producing high-quality creative for social advertising. Whether it is static imagery or platform-optimized video assets, developing strong creative requires time, strategy, and the right talent. Many brands simply do not have the internal bandwidth to produce the volume of assets needed to test, iterate, and scale effectively. Creative is not just a deliverable. It is a core driver of performance and a major factor in justifying ad spend. Without a steady pipeline of thoughtful, well-developed assets, even the most strategic media plan can struggle to perform.

A Human-First, AI-Supported Approach

That is why our approach is human-first, supported by machine learning and AI.

When we talk with clients about what will most directly impact their growth trajectory, creative is always at the top of the list. In a recent blog outlining the five areas that deserve the most budget attention this year, creative is ranked number one. Strong creative fuels testing. Testing drives performance. And performance drives sustainable growth.

For example, one of our e-commerce clients enrolled in our Creative Package, where we develop paid social assets using AI platforms like Veo and Nano Banana alongside design tools such as Canva and other creative software. This combination allows us to produce platform-specific content efficiently while maintaining brand integrity. The goal was to create a performance-driven creative built for testing and iteration. The assets increased engagement and contributed to revenue growth, and the client’s organic social team even requested to repurpose them for their own channels.

The Takeaway: Strategy Over Tools

The takeaway is simple. When creative is strategic and data-informed, the tools used to create it matter less than the results it delivers.

When you consider the team behind the AI-generated content, it becomes clear that the technology does not remove the soul of advertising. Instead, it expands what is possible. AI helps open doors by making the creative process more efficient and more informed by data, while allowing teams to focus on the high-impact human elements that technology cannot replicate, such as strategy, storytelling, and emotional connection.

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