Looking to take the next step in your search marketing career?

Below, you will find the latest SEO, PPC, and digital marketing jobs at brands and agencies. We also include positions from previous weeks that are still open.

Newest SEO Jobs

(Provided to Search Engine Land by SEOjobs.com)

• Digital Marketing Assistant — Remote
  May 21, 2026
  The Role We need someone who can handle the day-to-day execution of our marketing operations across multiple clients. This is not a strategy role — it’s hands-on work. You’ll be publishing content, managing prospect lists, keeping local listings accurate, and making things run on time. You’ll work directly with the founder. Communication is in English, […]
• Growth Marketer, Pipeline Development
  May 21, 2026
  Job Description Job Description Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands […]
• SEO/AEO Specialist
  May 21, 2026
  I’m the owner of Jaclyn Hope Design, a small web and SEO agency based near Seattle, WA. We produce high-quality, converting websites and solutions, with detailed SEO work on every site. Our clients are both service and product-based businesses. The majority are women entrepreneurs and business owners. We have a small team of designers and […]
• Director, SEO (AI Engine Optimization)
  May 18, 2026
  Who we are At CarGurus (NASDAQ: CARG), our mission is to give people the power to reach their destination. We started as a small team of developers determined to bring trust and transparency to car shopping. Since then, our history of innovation and go-to-market acceleration has driven industry-leading growth. In fact, we’re the largest and […]
• SEO Specialist
  May 18, 2026
  We are seeking a skilled and experienced Remote SEO Specialist to join our digital marketing team. In this role, you will be responsible for improving our website’s organic search rankings, driving increased traffic, and enhancing online visibility. The ideal candidate will have a deep understanding of SEO best practices, keyword research, on-page and off-page optimization, […]
• Senior Data Analyst, SEO
  May 17, 2026
  About Us Scorpion is the leading provider of technology and services helping local businesses thrive. We do this by helping customers understand local market dynamics, make the most of their marketing, and deliver experiences their customers will love. We offer tools to know what’s going on with marketing, competitors, and customers. We offer a unique […]
• Digital SEO Manager
  May 17, 2026
  Job Description Digital SEO Manager COMPANY BACKGROUNDOur client is successful eCommerce company with a large range of consumer good and brands that are recognised and sold across most of the world’s leading online platforms (Amazon, Google Shopping, eBay etc) JOB RESPONSIBILITIESTo manage all of their international website SEO campaigns, they wish to recruit a Digital […]
• SEO Content Writer
  May 17, 2026
  About Inspira Education Inspira Education Group is one of the fastest-growing edtech startups in the US. We started with a simple mission to democratize access to high-quality coaching so that every student in the world has an equal opportunity to access the best opportunities.  As the world’s leading network of top admissions coaches in medical, […]
• SEO Manager
  May 17, 2026
  Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, […]
• Digital Product Specialist
  May 17, 2026
  Description What we need:  The Digital Solutions Specialist is responsible for the coordination and execution of several items relating to the successful launch and ongoing maintenance of features and capabilities of Cetera’s digital platform, AdviceWorks. Reporting to the Managing Director, Digital Solutions, this role facilitates key deliverables relating to user acceptance testing, go to market planning, and ongoing platform support.  […]

Newest PPC and paid media jobs

(Provided to Search Engine Land by PPCjobs.com)

• iCloud Growth Marketing Manager
  May 22, 2026
  Join the team that brings iCloud to life for millions of people every day. We’re looking for a Growth Marketing Manager to lead customer acquisition, engagement, and retention initiatives that improve the customer experience and drive business growth. In this role, you will partner with teams across marketing, product, engineering, analytics, design, business development, operations, […]
• Senior Analyst, SEO & Paid Search
  May 22, 2026
  No detailed job description available from the API. View Original Job Posting
• Paid Media Manager (Richmond)
  May 22, 2026
  About the role Our Paid Media Managers are responsible for developing and executing handcrafted digital marketing strategies on paid search, display, and paid social advertising channels. While much of your work will be independent, there are also plenty of opportunities to collaborate with fellow analysts, mentor junior team members, and receive ongoing training. We need […]
• Growth Marketing Lead
  May 22, 2026
  Description Role: Growth Marketing LeadLocation: London (Oxford Circus)    Hybrid: 2 days per week  Reports to: Director of Brand & Marketing About Monument​We’re building something genuinely rare: a financial brand designed for the mass affluent – the professionals, entrepreneurs and ambitious savers that traditional banks have systematically underserved for decades. We exist to make managing wealth simpler, smarter and more […]
• Account Coordinator – SEM (Paid Search)
  May 22, 2026
  Company Description GroupM is the leading global media investment management operation serving as the parent company to WPP media agencies including Mindshare, Wavemaker, and Mediacom – each global operations in their own right with leading market positions. GroupM’s primary purpose is to maximize performance of WPP’s media agencies by operating as leader and collaborator in […]

Other roles you may be interested in

Senior Manager, Paid Search, Talkiatry (Hybrid, New York, NY)

• Salary: $150,000 – $180,000
• Own and scale Talkiatry’s paid search program end-to-end, including forecasting, budgeting, pacing, bidding strategies, account structure, and creative testing for Google, Bing, and ZocDoc.
• Develop and execute a rigorous testing roadmap, including ad copy, keyword strategy, landing page variants, and automation/algorithmic controls; quantify impact using sound experimental design.

Paid Digital Marketing Manager, Pei Wei (Irving, Texas)

• Salary: $75,000 – $110,000
• Develop and manage paid digital marketing strategies across multiple channels, including: Paid Search, Performance Max (PMAX), Meta Ads (Facebook & Instagram)
• Monitor, optimize, and scale campaigns based on performance KPIs including ROAS,CPA, conversions, traffic, impressions, engagement, and sales.

Paid Ads Manager, Wiley (Remote)

• Salary: $81,200
• Plan, schedule, and execute paid ads campaigns across platforms (e.g., Meta, LinkedIn, YouTube, Google, Bing), ensuring alignment with campaign objectives and budget allocations
• Manage paid ads budgets, monitor performance, and optimize campaigns to meet cost-efficiency and revenue contribution targets

Senior Search Marketing Manager, Acadaca (Remote)

• Salary: $75,000 – $85,000
• Strategize & Execute: Develop, launch, and manage comprehensive paid search, display, shopping, pmax, demand gen, youtube and ctv campaigns from conception to optimization, ensuring alignment with client business objectives.
• Performance Optimization: Proactively manage bids, budgets, and targeting to achieve and exceed key performance indicators (KPIs) such as Revenue and ROAS.

Senior Manager, SEO/AEO, ActiveCampaign (Remote)

• Salary: $140,500 – $193,200
• Identify opportunities for technical improvements across the ActiveCampaign website, prioritize them based on their potential business impact, and collaborate with cross-functional stakeholders to implement them.
• Pioneer LLM optimization and Answer Engine Optimization (AEO) by developing content strategies that ensure ActiveCampaign is the authoritative source material used by LLMs.

SEO Marketing Manager, Care.com (Hybrid, Dallas, TX)

• Salary: $85,000 – $95,000
• Organic Growth: Build and execute the SEO roadmap across technical, content, and off-page. Own the numbers: traffic, rankings, conversions. No handoffs, no excuses.
• AI-Optimized Search (AIO): Define and drive CARE.com’s strategy for visibility in AI-generated results — Google AI Overviews, ChatGPT, Perplexity, and whatever comes next. Optimize entity coverage, content structure, and schema to ensure we’re the answer, not just a result.

SEO Manager, Veracity Insurance Solutions, LLC, (Remote)

• Salary: $100,000 – $135,000
• Lead, coach, and develop a high-performing team of SEO Specialists
• Set clear expectations, quality standards, workflows, and growth paths across the team

Marketing, Social Media & PR Manager, PARTNERS Staffing (Fort Myers, FL)

• Salary: $75,000 – $85,000
• Develop and execute integrated marketing campaigns for shows, content releases, events, and brand initiatives
• Identify target audiences and create strategies to grow reach and engagement

Senior Paid Media Manager, Brightly Media Lab (Remote)

• Salary: $70,000 – $100,000
• Directly build, manage, and optimize campaigns within Google Ads, Microsoft Ads, and Facebook Ads (Meta).
• Serve as the lead point of contact for your book of clients, taking full ownership of their success and growth.

Paid Search Specialist, Maui Jim Sunglasses (Peoria, IL)

• Salary: $65,000 – $70,000
• Plan, set up, and manage paid search, display, and shopping campaigns on Google Ads.
• Manage and optimize advertising budgets to achieve revenue and efficiency targets.

Note: We update this post weekly. So make sure to bookmark this page and check back.

OpenAI is rolling out a fresh set of updates to its Ads Manager Beta, giving advertisers more control over campaign pacing, targeting, and reporting — while also quietly testing new ad experiences inside ChatGPT.

The latest updates signal continued investment in building out the platform’s advertising capabilities as OpenAI looks to make ChatGPT a more viable performance and brand advertising channel.

What’s new in Ads Manager Beta:

Daily budgets arrive. Advertisers can now choose between a daily or lifetime budget when creating new campaigns.

For now, daily budgets are limited to newly created campaigns, but the addition gives marketers more flexibility over pacing and spend management — particularly useful for advertisers running always-on activity or testing campaigns with tighter controls.

Expanded geo targeting. OpenAI is also introducing more granular location targeting options across the U.S.

Advertisers can now target campaigns by state, designated market area (DMA) and zip code

Targeting can be configured during campaign setup or adjusted later within campaign settings.

The update brings ChatGPT’s ad tools closer to the location controls advertisers are accustomed to on established platforms like Google and Meta, particularly for regional campaigns and local business targeting.

Aggregate totals in reporting views. Ads Manager table views now display aggregate totals for key metrics including impressions, clicks and spend

Totals are available across campaign, ad group, and ad-level reporting views, making it easier for advertisers to quickly assess performance without exporting data.

OpenAI begins testing new ChatGPT ad experiences. Alongside the Ads Manager updates, OpenAI confirmed it is beginning an early test of new ad experiences within ChatGPT.

A small subset of ads may now display dynamic calls-to-action (CTAs), including:

• “Shop Now”
• “Book Now”
• “Sign Up”
• “Learn More”

According to OpenAI, CTAs are automatically selected based on the ad creative and destination experience.

The company said advertiser controls for CTA selection could be explored in the future.

OpenAI described the feature as a lightweight enhancement intended to help users better understand and engage with ads appearing in ChatGPT.

Why we care. These updates signal that OpenAI is steadily building a more sophisticated and performance-oriented ad platform inside ChatGPT. Features like daily budgets and granular geo targeting give marketers greater control over spend and audience reach — capabilities that are considered essential on more mature advertising platforms.

The introduction of dynamic CTAs also suggests OpenAI is beginning to optimize ads for engagement and conversion actions, potentially opening the door to more performance-driven ad formats in the future. For brands experimenting with AI-native advertising, these updates indicate the platform is evolving beyond early-stage testing into a more viable media channel..

For a first-time attendee, Google I/O’s energetic, optimistic atmosphere felt almost like a coronation.

Last year’s bets are now growth pillars because they worked. Ask Maps became the playbook for rolling out Ask YouTube. Gemini 3.5 Flash powers Antigravity — think Claude Code, but Google — and Googlers are already using it to build the features demoed on stage.

Everything shipped fast, and everything felt confident.

There was something for everyone.

• Gemini Omni, which was compared to Nano Banana but for video (I have bizarre proof).
• Smart glasses are making a comeback.
• Video game-like experiences that can be prompted and played in real time.
• Workspace can now talk documents into existence.
• Google Maps images can be turned into surrealistic fever dreams via prompting (I asked what the use case was, and it sounded more like a solution looking for a problem: Hollywood studios could forgo shooting on location?).
• I even have Gemma running on my phone so I can converse with a smaller model on an airplane. (P.S. American Airlines now has free Wi-Fi, so I’m good.)

But I haven’t even gotten to the part that’s most curious.

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Gemini is becoming more like Search. Search is becoming more like Gemini.

There are now features across both products that serve the same intent: monitoring the web and proactively notifying you when something relevant appears.

In Search, it’s information agents. In Gemini, it’s Spark or Daily Brief. The overlap is obvious.

So I asked one of the product managers directly: “How are you thinking about long-term feature management and the bloat of utilities that largely overlap?”

The answer: “Right now, it’s all about velocity.”

They’re shipping relentlessly. Three other PMs behind flagship I/O features said the same thing. Every one of those features was started and shipped this year, in 2026. That was mind-blowing.

The PM added: “The way velocity is achieved is less managerial overhead.”

I took that to mean: get on the board now and figure it out later.

Once you see it, you can’t unsee it

With that framing, the rest of the day looked different. I saw plenty of impressive demos, but kept wondering: what do I actually do with these next?

I now have Gemma on my phone, but one of the developers couldn’t offer much of a day-to-day use case. I got a demo of AI Mode’s monitoring capabilities by prompting “keep me updated” and saw how the pieces connected. But when I asked a follow-up — “How will I manage these alerts alongside everything else? What happens when they go stale?” — there wasn’t an answer. Granted, it’s still a demo, but the non-answer was telling.

The second-order effects of many of these features don’t seem fully considered. It gave me the sense that engineers dogfood these models from the command line, not the front end.

One small but revealing example: as of this writing, I still can’t delete old Gemini chats in the web browser, even though I can in the Mac app.

Universal Cart: The feature that got everyone talking

One feature that came up repeatedly in conversations with both engineers and users was Universal Cart, Google’s new cross-surface shopping protocol.

When people asked what I thought, I said: “If you’re Google, you should be very excited, because if this gets adopted, you own more of the end-to-end experience. If you’re everyone else, you’re probably worried.”

That didn’t seem to concern the group I spoke with, many of whom felt oddly detached from the growing anti-AI sentiment in the U.S.

Later, I spoke with an SEO professional at a large ecommerce brand already implementing Universal Cart. When I mentioned the velocity comment, they said: “That sounds like what we experienced during implementation. It feels rushed.”

The AI content guidelines paradox

The velocity-over-oversight mindset also helps explain why Google’s AI content guidelines have been so controversial.

Four days before I/O, Google’s Search quality team told publishers to “write for humans, not AI.” Then the AI agent team took the stage and demonstrated a future where Google’s own agents browse, interpret, transact on, and generate content across the web.

If the future is increasingly AI Mode — with agents building, fetching, and acting on users’ behalf — the guidance to publishers starts to ring hollow.

Why this matters for the web ecosystem

I don’t want to diminish the work these engineers are doing. I told them that directly. As someone building products for search and for our clients, I empathize. You mostly hear criticism, not praise.

But I can’t help wondering what happens when all these overlapping features — the bloat, the inability to delete, manage, or reconcile things cleanly — become technical debt that has to be unwound. Right now, the AI playbook seems to be: feature utilization first, fix it later.

Still, I honestly respect that a company as large and established as Google is moving this fast, and I’m genuinely excited to see how some of this plays out. With their cash flow and their ability to manufacture their own TPU chips, they can afford to place multiple bets and see what sticks.

I wanted to keep talking with that PM, but we were unceremoniously kicked out of the area.

The bright spots are real

Google reported that last quarter saw an all-time high in search queries. They’re taking authentication and provenance seriously, with SynthID expanding into Search and Chrome, new adoption partners like OpenAI, and C2PA content credential verification for crawl.

Those are meaningful steps forward.

But this pace will likely create unintended consequences. My hope is that the rush to move fast doesn’t further destabilize an already-rattled web ecosystem by breaking too many things along the way.

All of this is to say: it’s an exciting time to be in search.

Dig deeper.

• Google’s new intelligent Search box – its biggest change to the search box in 25 years
• Google Search now powered by Gemini 3.5 Flash
• Google Search gains information agents and improved agentic experiences
• Google lets you build your own app within Google Search with agentic coding

Every time Google ships a new Search Central document, two camps in our industry move at the speed of light. The first camp screenshots their favorite paragraph, posts it to LinkedIn with “SEE? IT’S JUST SEO” in the caption, and goes back to doing exactly what they were already doing. The second camp screenshots a different paragraph and posts it with “see, here’s the proof they’re lying to us.” Both camps treat Google’s guidance like scripture, depending on which verse confirms what they already believed.

Google’s recently updated guide on Optimizing your website for generative AI features on Google Search was a feast for the first camp. The “it’s just SEO” folks ate well that week. AEO and GEO got declared “still SEO.” Chunking got dismissed. llms.txt got dissed. Rewriting for AI got nullified. If you’ve spent the last two years on LinkedIn telling everyone that nothing has changed, Google handed you a gold star and a victory lap.

But I want to remind everyone of something the first camp likes to forget: two years ago, we held thousands of pages of Google’s internal Search ranking documentation in our hands. The leaked Content Warehouse documents showed, in Google’s own words, how the public guidance and the internal reality diverge. The same company that publicly insisted certain signals didn’t exist had them named, weighted, and documented inside their own engineering wiki. That wasn’t a leak from an enemy of search. That was Google’s own engineering documentation, and it showed exactly how much we should trust public guidance about what is and isn’t important.

I’m not saying every line of Google’s new guide is a lie. I am saying that Google has a long, well-documented history of nudging the industry in directions that benefit Google first and the open web maybe. It’s to Google’s benefit for SEOs to remain the janitors of the web cleaning up technical debt, formatting structured data, and politely waiting for the next algorithm update rather than evolving into a discipline that operates across multiple platforms and influences how content is engineered for systems Google does not control.

As I argued in my refutation of the misinformation about chunking, the influence Google has spent two decades accumulating is finally fragmenting. Competitive AI platforms are stealing attention. Referral traffic is shrinking. Investment is moving to channels Google doesn’t own. The leverage Google had to define what “good content” means is weaker than it has been in twenty years — and you can hear it in how protective the language has gotten.

Meanwhile, in Redmond

For a clean contrast, look at what’s been coming out of Bing.

Krishna Madhavan and his team have spent the last several months publishing posts that read like the opposite of Google’s guide. Keep in mind that there is near parity in both platforms’ offerings.

Where Google’s posture is “trust us, keep doing what you were doing,” Bing has been publicly explaining how their index is changing, what grounding actually requires, and giving publishers tools to measure how their content participates in AI answers.

In Elevating the Role of Grounding on the AI Web, Jordi Ribas openly names what’s happening: agents are doing the browsing now, they’re drawn to structured and verifiable content, and a new optimization discipline called Generative Engine Optimization is emerging in response. No dismissive air quotes. No “it’s all still SEO.” They just call it what it is.

Introducing AI Performance in Bing Webmaster Tools goes further. It is, in Microsoft’s own words, “an early step toward Generative Engine Optimization (GEO) tooling in Bing Webmaster Tools.” Citations across Copilot and Bing’s AI summaries. Page-level citation activity and  Grounding queries, you know, the actual phrases AI used when retrieving your content. The thing every working AI Search practitioner has been asking for, Bing shipped it.

Then, in Evolving role of the index: From ranking pages to supporting answers, Krishna’s team explains in plain detail that “the unit of value shifts from documents to groundable information — discrete, supportable facts with clear provenance.” They state directly that “chunking/transformations must preserve meaning and claims used in the answer.” They acknowledge that the metrics, the unit of analysis, and the responsibility of the system have all changed.

Read those three posts in order, then go re-read Google’s “mythbusting” section. You will struggle to believe you’re reading documents about the same technology.

Going point by point

With that framing, let’s walk through Google’s claims.

“Is SEO still relevant for generative AI search?”

“What about ‘AEO’ and ‘GEO’? ‘AEO’ stands for ‘answer engine optimization’ and ‘GEO’ for ‘generative engine optimization’. These are both terms you may see used to describe work specifically focused on improving visibility in AI search experiences. From Google Search’s perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO.”

“It’s just SEO” is naive, and it’s naive for the same reason it has been naive every previous time someone trotted it out.

SEO as a discipline is not a list of tactics. It’s a mindset, a set of organizational expectations, a budget line, and a reporting structure. SEOs have been trying to expand that mindset for years to bring in content engineering, to influence product, to own technical architecture, to participate in video, brand, and design. We mostly haven’t won those fights, because the org charts in most companies treat SEO as a downstream cleanup function.

This is also the same trick the industry has played on us for fifteen years. Mobile was “just SEO.” Voice was “just SEO.” Schema was “just SEO.” AMP was “just SEO,” and we ate years of implementation work for a system Google quietly deprecated. Every time a new surface appears, the discipline absorbs the work, and every time, the line item that pays for it doesn’t grow proportionally. Folding AI Search into “SEO” isn’t a clarification. It’s the continuation of a pattern that has been excellent for Google and lousy for the people doing the work.

• The skill set has diverged whether the title has or not. The traditional SEO toolkit is keyword research, technical auditing, internal linking, structured data, content optimization tools, link building, and rank tracking. The work of AI Search adds information retrieval theory, vector distance measurement, RAG pipeline analysis, content engineering at the passage level, agent and protocol design (MCP, A2A, UCP, ACP), brand citation tracking across LLM platforms, and synthesis evaluation. There is overlap. There is also vast surface area that has never appeared in any SEO job description ever written. Pretending the skill set is the same is how organizations underhire for the actual problem.
• The audience changed, too. Traditional SEO optimizes for one machine and the humans clicking its results. AI Search optimizes for a retrieval system, a synthesis pipeline, possibly an agentic browser, and a human reading an answer that may not contain a link to your site at all. Those are different consumers with different criteria, different measurement, and different reporting. Pretending the audience hasn’t changed is how you end up running the wrong tactics against the wrong KPIs for the wrong stakeholders.
• The strategic cost of “just SEO” is concrete. When a brand asks “how do we show up in ChatGPT?” and you treat that as an SEO problem, you start optimizing pages and chasing indexing. The actual answer often has very little to do with your website. It involves your presence in Wikipedia, Reddit, third-party publications, and the licensed data partners that feed model training and grounding. That isn’t on-page work. That is brand, PR, third-party data, and information architecture across the open web. An SEO budget rarely funds that work. A GEO or AEO budget can.

When AI Search lands in an organization with a different name, it gets different expectations and a different budget. It gets cross-functional sponsorship. It gets executive attention. It gets the cross-discipline collaboration SEOs have been requesting since I started in this industry two decades ago. “AEO” and “GEO” are not magical incantations, but the labels create the room SEO has not been able to create for itself.

Meanwhile, the practitioners doing this work keep getting handed more responsibility. More platforms to optimize for. More systems to understand. More research papers to read. More tooling to build. None of that comes with new headcount or higher salaries when leadership sees it as “still SEO.” Google reframing this work as the same old discipline isn’t a neutral observation. It is the rhetorical move that keeps the work uncompensated.

And note: Google itself doesn’t actually run on “it’s just Search.” AI Mode, AI Overviews, and classic ranking are different systems run by different teams on different infrastructure with different evaluation criteria. The leaked Content Warehouse docs made those distinctions visible. Their public posture flattens the inside of their own org for the benefit of the outside narrative. We don’t have to accept the flattening.

That’s what “it’s just SEO” actually delivers to organizations: more scope, same budget, no new authority. That’s a fantastic outcome for the platforms that benefit from our unpaid labor. It is a terrible outcome for the people doing the work.

Non-commodity content

“Create valuable, non-commodity content for your audience”

This part is fine. Make good, unique content with a real point of view. Nobody serious disagrees. Moving on.

llms.txt files and other ‘special’ markup

“You don’t need to create new machine readable files, AI text files, markup, or Markdown to appear in generative AI search.”

True for Google. Also missing the point.

llms.txt is genuinely useful for Claude and a handful of other systems that have explicitly committed to reading it. Anthropic has documentation suggesting it. There are observable benefits to publishing it in environments where it’s actually consumed. Telling people to ignore it because Google doesn’t read it is exactly the kind of single-platform myopia I keep pointing at. Google’s guide describes one ecosystem. Your strategy needs to account for several.

The honest version of this guidance would be: “Google doesn’t process llms.txt in any special way. Other systems may. Make your own call.” Instead, Google quietly conflates “we don’t use it” with “you don’t need it.”

‘Chunking’ content

“There’s no requirement to break your content into tiny pieces for AI to better understand it. Google systems are able to understand the nuance of multiple topics on a page and show the relevant piece to users.”

I wrote 4,500 words on this in January and I’d rather not relitigate the whole thing here. The short version is this: chunking is what RAG systems do to your content, whether you optimize for it or not. The question is whether your content survives the chunking process with its meaning intact, or whether it shatters into incoherent fragments. The vector math doesn’t care about Google’s preferences. A passage that focuses on one idea will, in nearly every measurable case, retrieve better than a passage that tries to cover three.

Bing acknowledges this directly: “chunking/transformations must preserve meaning and claims used in the answer.” Google’s own MUVERA research, their work on passage indexing, their patents on pairwise passage selection — none of it is consistent with the guidance that chunking doesn’t matter. The systems retrieve passages. Treat your passages like they matter, because the systems do.

Rewriting content just for AI systems

“You don’t need to write in a specific way just for generative AI search. AI systems can understand synonyms and general meanings of what someone is seeking, in order to connect them with content that might not use the same precise words. This means you don’t have to worry that you don’t have enough ‘long-tail’ keywords or haven’t captured every variation of how someone might seek content like yours.”

This is the line that bothers me most, because it is antithetical to how these systems actually decide what to use.

A retrieval system selects passages by computing vector distance against the query embedding. A synthesis pipeline then performs pairwise comparisons between candidate passages to decide which ones get sent to the model. The system is not “understanding” your content in the human sense — it’s computing a similarity score, ranking by it, and making committed selections. Specificity, entity salience, semantic coherence, and structural clarity all show up in those scores. Write loose, generic, multi-topic prose and your passages lose those comparisons to passages that are tight, specific, and self-contained.

“Just write naturally for humans” sounds like good advice until you realize the systems have a measurable preference, and you can win or lose on the margins by writing for both. We have empirical evidence that adjusting passages improves their retrieval scores. We have access to public APIs that let us verify this on the content we publish. The guidance to ignore all of that and trust the systems to figure it out is asking you to compete with one hand tied behind your back.

SEO best practices still help. They just don’t cover the whole map.

I want to be careful here because this discourse gets reduced to extremes:

• SEO best practices help.
• Technical structure matters.
• Crawlability matters.
• Page experience matters.
• Unique, non-commodity content matters.
• None of that is going anywhere.

But “SEO best practices” was always shorthand for “what Google likes.” That was a fine proxy when Google was 90% of the traffic, and the rest didn’t matter. It is not a fine proxy in a world where ChatGPT, Perplexity, Claude, Copilot, Gemini, and a long tail of vertical agents are all making their own retrieval decisions on different infrastructure with different priorities. Some of those systems use Bing as their grounding layer. Some build their own indices. Some lean on llms.txt. Some don’t. Some are shipping webmaster tooling. Some are publishing the math behind their retrieval. The shared layer is shrinking, and the surface area you have to actually optimize is growing.

The thing Google’s guide doesn’t say — because it can’t — is that the systems competing with Google have different opinions, different infrastructure, and different incentives. Optimizing for all of them at once requires a broader practice than what’s described in any Search Central document. That practice is being built right now, in public, by people who refuse to accept that the only opinion that counts is Google’s.

A new world, a lot of opinions

Google’s guidance on AI Search is one opinion. It is the opinion of the company with the most to lose from a multi-platform world. Read it. Take what is useful. Apply it where it applies. Don’t mistake it for the truth.

The truth is that we are in a new world. The infrastructure for how information is retrieved and presented is being rewritten across multiple platforms simultaneously, and the consensus we once had about how to optimize it no longer exists. Bing is publishing what they’re doing. Anthropic is publishing what they’re doing. The research community is publishing what they’re doing. Google is publishing what it wants you to do.

That last one is not the same as the others. Treat it accordingly.

This article was originally published on the iPullRank blog and is republished with permission.

I’ve attended many AI conferences and training events over the past few years. I’ve seen people doing innovative work, but I’ve also seen many spinning their wheels.

After working hands-on with AI automation across multiple businesses, I’ve done both. So I want to share what I’ve learned to help you avoid wasting time, energy, and money — and instead use AI strategically to increase revenue and reduce expenses.

Many AI projects never create real value

More often than not, I see entrepreneurs reinventing the wheel with AI. I’ve lost count of how many people I’ve seen brag about using AI to build a new CRM when hundreds of solid platforms already exist. It makes no sense to build a new CRM when existing platforms already offer nearly every feature you need — and have full development teams keeping them updated and running smoothly.

The same goes for apps and software that are just clones of existing tools. I’ve made that mistake myself, but the reality is no one needs another version of the same tool that already exists a hundred times over.

Now, there are a few rare cases where building an app or software platform makes sense — mainly when you can launch it quickly and offer a proprietary approach. That could include a unique formula or algorithm, a specific process, or access to exclusive data. In other words, it needs to be something core to how you do business.

Otherwise, you risk spending time and money on technology that doesn’t materially improve the business.

Strategic AI is the real competitive advantage

The businesses seeing the strongest results from AI are using it to solve measurable operational problems.

The key is to apply it in ways that directly improve revenue and productivity.

How AI can directly increase revenue

For example, you might use AI to build a highly targeted prospect list and automate outreach to move leads into your marketing funnel. You can even take it further by using AI for part — or all — of the sales process. Many companies are already doing this and generating fresh, targeted leads on autopilot every day.

This is a highly effective, scalable way to increase revenue at a fraction of the cost of hiring people to do the work. There’s one caveat: you need to be certain your company can handle the increase in business. While this creates an opportunity to scale, it also means more people will be affected if you drop the ball — and that can damage your reputation quickly.

Implementation still requires oversight, testing, and operational discipline. Poorly implemented AI can create just as many problems as it solves.

AI can reduce time and operational costs

Another approach is to use AI to handle your workload more efficiently, reducing both time and costs. One way I’ve used it is to quickly analyze market conditions so I can make more accurate pricing decisions when buying and selling properties.

This is where AI really shines. It can compile, analyze, and generate insights from large datasets far faster than a person can manually, while surfacing patterns and opportunities that might otherwise be missed.

Using AI this way helps me identify the deals that make the most sense and make accurate offers faster than my competitors, which can be the difference between winning a deal and losing it.

One simple AI workflow that saves hours

Another smart approach I’ve seen came from the PR firm I work with. They use AI to monitor their clients’ media interview calendars, and once an interview is completed, the system automatically finds the Zoom recording, sends it for transcription, and queues an email with the video and transcript to the journalist.

This saves the firm roughly 30 minutes per interview and delivers everything within minutes, rather than waiting for an employee to handle it. Beyond the time and cost savings, it also makes the publicity far more valuable to journalists by making their job faster and easier.

Other high-impact ways to use AI

There are many other strategic ways to use AI to measurably improve revenue and productivity. Some of the ways I’ve helped entrepreneurs do this include:

• AI virtual phone assistants answering calls 24/7.
• Smart website widgets/chat assistants trained specifically on your business.
• Appointment booking.
• Missed call recovery.
• Other implementations that improve response time and customer experience.

AI is only effective when used strategically

One of the biggest opportunities I see right now is helping service businesses stop losing revenue from missed opportunities.

Most small businesses don’t need another complicated platform or custom AI app. What they need is a system that responds faster than they can manually. That might be an AI-powered phone assistant answering calls and booking appointments 24/7, or a website assistant trained on the business that can answer questions and capture leads instantly. Used strategically, AI becomes less about replacing people and more about making sure opportunities stop slipping through the cracks.

Businesses that implement AI effectively will likely outperform competitors that are slower to improve operational efficiency and response times.

The most effective AI implementations are usually the least flashy. They solve specific operational problems: reducing missed calls, improving response times, accelerating analysis, qualifying leads faster, or eliminating repetitive administrative work.

If an AI system doesn’t measurably improve revenue, efficiency, customer experience, or decision-making, it’s worth questioning whether it needs to exist at all.

Using AI this way creates a major opportunity to get ahead and outperform slower-moving competitors.

So the only question is: will you invest the time to use AI strategically?

Google released the May 2026 core update today, the company announced.

This is Google’s second core update of 2026. It follows the March 2026 core update, the March 2026 spam update, and the February 2026 Discover update.

What Google is saying. Google updated its Search Status Dashboard to state:

• Released the May 2026 core update. The rollout may take up to 2 weeks to complete.

Google posted on LinkedIn saying:

• “This is a regular update designed to better surface relevant, satisfying content for searchers from all types of sites. The rollout may take up to 2 weeks to complete.”

About core updates. Core updates typically roll out multiple times each year. They introduce broad, significant changes to Google’s search algorithms and systems, which is why Google announces them.

• Google also releases some smaller, unannounced core updates.
• It has been a long time since the last core update. Many expected Google to roll out core updates more frequently, but that didn’t happen.

What to do if you are hit. Google didn’t share new guidance specific to the May 2026 core update. However, Google has previously offered advice on what to consider if a core update negatively impacts your site:

• There aren’t specific actions you can take to recover. A negative rankings impact may not mean anything is wrong with your pages.
• Google provided a list of questions to consider if your site is hit by a core update.
• You may see some recovery between core updates, but the biggest changes tend to follow another core update.

In short: write helpful content for people, not for search engines.

• “There’s nothing new or special that creators need to do for this update as long as they’ve been making satisfying content meant for people. For those that might not be ranking as well, we strongly encourage reading our creating helpful, reliable, people-first content help page,” Google said previously.

For more details on Google core updates, you can read Google’s documentation.

Previous core updates. Here’s a timeline and our coverage of recent core updates:

• The March 2026 core update was on March 27 and ended on April 8.
• The December 2025 core update was on Dec 11 and ended on Dec. 29.
• The June 2025 core update was on June 30 and ended on July 17.
• The March 2025 core update was on Mar. 13 and ended on Mar. 27.

Why we care. With any core update, you often see significant volatility in Google search results and rankings. These updates may improve visibility for your site or your clients’ sites, but you may also see fluctuations or declines in rankings and organic traffic. We hope this update rewards your efforts and drives strong traffic and conversions.

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AI adoption appears to be diverging between professional and consumer audiences, according to Rand Fishkin’s new analysis of Datos desktop-panel data and SparkToro audience comparisons.

The data highlights a sharp divide in how people talk about AI use: broader consumer adoption may be slowing, while professional and B2B audiences appear far more likely to use tools like Claude, ChatGPT, and Gemini.

Why we care. There’s no one-size-fits-all AI strategy. Your audience may behave very differently from broader AI trends, so you need to understand whether your audience is actually using these tools — and which ones.

ChatGPT desktop growth slowed. Fishkin, SparkToro’s cofounder and CEO, said Datos’ U.S. desktop data showed ChatGPT and OpenAI usage had largely plateaued over the past six to seven months, even as Claude and Gemini continued to grow.

• At its peak, about 37% of U.S. desktop users visited OpenAI or ChatGPT in September 2025, according to the data Fishkin cited. That figure fell to 34% by March.
• Fishkin said the same general pattern appeared in the EU and U.K., though desktop usage there was roughly 10% higher than in the U.S.

Claude gained with professionals. Claude showed the strongest recent momentum in the Datos data, with four straight months of growth from December through March. Fishkin said the trend supports his theory that consumer AI adoption may be plateauing while professional and business use continues to grow.

• To test that idea, Fishkin used SparkToro audience comparisons to analyze business professionals and, separately, a broad consumer audience centered on retail shopping behavior.
• The business-oriented audience showed substantially higher overall AI tool usage. Claude usage overindexed especially strongly among B2B professionals, with SparkToro showing a 373% lift versus the average U.S. population, according to Fishkin’s analysis.

Consumer audiences look different. Fishkin said ChatGPT was 15% less likely to be used by the retail-shopping consumer audience than by the average American. Claude didn’t rank among the top four AI tools for that group.

• This may help explain why AI usage can feel far more dominant in professional online communities like LinkedIn than in broader consumer behavior, according to Fishkin.

The research. Watch Fishkin’s LinkedIn video here.

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Google’s new Lighthouse “Agentic Browsing” audits now check for the presence of an llms.txt file. The new experimental Lighthouse documentation frames llms.txt as a discoverability and efficiency signal for AI agents, not a traditional crawling directive.

• The audits are part of Chrome’s emerging “Agentic Browsing” category, which evaluates whether sites are structured for machine interaction.
• This document comes less than a week after Google published new guidance on optimizing for AI search features like AI Overviews and AI Mode, in which it said you don’t need llms.txt files in a mythbusting section of its new guide on optimizing for generative AI features.

What Lighthouse now checks. Lighthouse’s Agentic Browsing category evaluates “how well your site is constructed for machine interaction” using deterministic audits, according to Google’s documentation. Among the checks:

• WebMCP integration.
• Accessibility tree integrity.
• Layout stability through CLS.
• Presence of an llms.txt file.

Lighthouse checks for “the presence of a machine-readable summary at the domain root.” Google also explained why the file matters for agents:

“Without llms.txt, agents may spend more time crawling the site to understand its high-level structure and primary content.”

The audit category doesn’t produce a traditional Lighthouse score (0-100). Instead, Google surfaces a fractional pass ratio along with pass/fail checks tied to agentic readiness signals.

The tension. The new Lighthouse documentation doesn’t directly conflict with Google’s advice on optimizing your website for generative AI features because these audits focus on AI agents and browser tools, not Google Search rankings. Still, seeing llms.txt mentioned in Chrome’s own readiness checks may cause some SEOs to rethink earlier doubts about the file.

Agentic engine optimization. The Lighthouse audits also align with ideas Google Cloud AI engineering director Addy Osmani outlined in April around Agentic Engine Optimization. Osmani said AI agents with limited context windows may cut off long pages or miss important information buried too deep in content. Among his recommendations:

• Cleaner semantic structure.
• Token-efficient content.
• Markdown delivery.
• llms.txt discovery layers.
• Capability signaling files like AGENTS.md.

SEO vs. llms.txt. Here’s exactly what Google recommends in Mythbusting generative AI search: what you don’t need to do:

• LLMS.txt files and other “special” markup: You don’t need to create new machine readable files, AI text files, markup, or Markdown to appear in generative AI search. Note that Google may discover, crawl, and index many kinds of files in addition to HTML on a website: this doesn’t mean that the file is treated in a special way.

Here’s what Google’s John Mueller said about Google using llms.txt, in response to Lily Ray asking him on Bluesky “Hey @johnmu.com – if you can answer, many folks are pointing out the irony that Google uses LLMs.txt files, plus markdown pages, despite also saying these things are not needed for performance in search. Could you share why Google might publish these files, if not to make crawling those pages/sites easier for agents? (I’m sure I’ll be getting this question a ton soon!)”:

The short answer is that it’s not done for search. There’s more to websites than just SEO :-).

The longer & nuanced version is that it’s worth separating “discovery” (finding the website or pages with a global search engine) vs “functionality” (there’s probably a more accurate term for this, but basically: once someone has found the page, helping them to best do the task they want to do).

Perhaps that’s similar to CTA’s on traditional pages? You don’t “do them” for SEO (to be found), but if you’re responsible for the website overall, ensuring a high “discovery rate” (SEO) together with a high conversion rate is useful to justify your work.

To get back to the developers.google.com site, AI coding has gotten very popular, and these coding systems can be (I think) efficient and accurate with the code they produce if they can easily read / parse reference material, such as developer documentation.

In those cases, it can help to give them a way to understand the context of the documentation they’re looking at, as well as a simplified version of the reference page (eg, in markdown). OF COURSE they can read HTML just fine, so this is imo more of a temporary crutch, perhaps to save some tokens.

For non-developer sites, I don’t think this makes much sense, even with more agentic traffic in the future (and if you check your logs, you’re not getting a lot of that at the moment). Making a markdown version of a shoe’s specs is not going to get you more sales (competitors appreciate it tho).

And (I know, nobody reads this far), if you think this is important to prepare for when agents are everywhere: your site (all sites) have much more important things to do for SEO than to prepare for a potential future situation that may or may not come. Prioritize needs before dreams.

What Google says agents rely on. Beyond llms.txt, Google’s new Lighthouse category strongly emphasizes accessibility and interface stability. The documentation says agents rely on the accessibility tree as their “primary data model.” Lighthouse specifically evaluates:

• Programmatic labels for interactive elements.
• Valid accessibility tree structure.
• Whether interactive content is hidden from assistive systems.
• Layout stability through CLS.

Google also warns that dynamically registered WebMCP tools and large DOM changes can affect audit results.

Why we care. Google says you don’t need llms.txt for Search, but Chrome is now checking whether the file exists. At the same time, Google’s agentic tools appear to favor sites that are easier for machines to read and use, especially sites with strong accessibility, stable layouts, and clear agent access.

Google’s help document. Lighthouse agentic browsing scoring

Dig deeper.

• Meet llms.txt, a proposed standard for AI website content crawling
• llms.txt isn’t robots.txt: It’s a treasure map for AI
• Does llms.txt matter? We tracked 10 sites to find out

Google is introducing new Merchant Center tools designed to help retailers improve visibility across AI-powered shopping experiences as announced today at Google Marketing Live 2026.

Driving the news. The company announced AI Performance Insights, a new reporting feature that helps merchants understand how their brand performs across AI surfaces.

The tool compares a brand’s share of voice against similar competitors and provides visibility into AI-driven discovery performance.

Google is also rolling out Conversational Attributes, a new product data capability that helps retailers optimize listings for more natural, conversational search behavior.

How it works. Retailers can add conversational product attributes and updated descriptions directly inside Merchant Center. Google’s AI systems then use that structured data to better match products with conversational shopping queries across AI Mode, Gemini and other AI-powered surfaces.

The updates are designed to help brands improve discoverability as shopping experiences become increasingly AI-driven.

Google also confirmed that Ask Advisor integrations are coming directly into Merchant Center.

Why we care. Structured product data is becoming more important as AI-powered shopping experiences expand across Search, Gemini and Maps.

Retailers that adapt product descriptions and feeds for conversational discovery may be better positioned to surface products in AI-generated recommendations and shopping flows.

The new reporting tools also provide advertisers with early visibility into how brands perform inside AI-powered experiences.

What to watch. As conversational search behavior grows, product feed optimization may become increasingly important for AI visibility. Retailers should also monitor how Google defines and measures “share of voice” across AI-powered shopping experiences.

Availability. AI Performance Insights is expected to roll out in Australia, Canada, India, New Zealand and the U.S. in the coming months. Conversational Attributes are rolling out globally.

Dig deeper. More Google Marketing Live 2026 news from today:

• Google tests new conversational ad formats in AI Mode and Search
• Google expands Direct Offers with AI-generated bundles, native checkout and travel deals
• Google brings Meridian marketing mix modeling into Analytics 360
• Google expands Demand Gen with YouTube creator tools
• Google upgrades Asset Studio with Gemini-powered creative generation and video tools
• Google expands Universal Commerce Protocol and launches new agentic shopping tools
• Google launches Ask Advisor across Ads, Analytics and Merchant Center

Google is expanding its Direct Offers pilot with new AI-powered promotion formats, native checkout integrations and travel-focused deal experiences as announced today at Google Marketing Live 2026.

Driving the news. The company announced several updates designed to make promotional offers more discoverable inside AI-powered Search experiences.

Brands will soon be able to upload:

• Discounts
• Giveaways
• Local coupons
• Product bundles

Google says Gemini will help dynamically construct personalized offers based on search intent.

How it works. Advertisers upload eligible promotions, products and campaign guardrails into Google Ads. Gemini then assembles contextual offers — such as bundles, coupons or discounts — based on a shopper’s query and browsing behavior inside AI-powered Search experiences.

The company is also adding native checkout support for merchants using Universal Commerce Protocol (UCP), allowing users to complete purchases directly from AI-assisted shopping flows.

Travel partners including Booking and Expedia will also soon be able to surface travel offers directly inside AI-assisted trip planning experiences.

Why we care. Google is turning promotions into a more integrated part of conversational shopping experiences.

Instead of relying on traditional deal extensions or static offers, advertisers may increasingly need to optimize promotions for AI-assisted discovery and contextual recommendation engines.

The native checkout integrations could also reduce friction between product discovery and conversion.

What to watch. Google appears to be moving promotional commerce experiences closer to AI-assisted discovery flows. Advertisers should watch how native checkout and AI-generated deal recommendations affect conversion rates and shopping behavior.

Availability. Direct Offers remains in pilot for U.S. advertisers.

Dig deeper. More Google Marketing Live 2026 news from today:

• Google tests new conversational ad formats in AI Mode and Search
• Google launches AI Performance Insights and Conversational Attributes in Merchant Center
• Google brings Meridian marketing mix modeling into Analytics 360
• Google expands Demand Gen with YouTube creator tools
• Google upgrades Asset Studio with Gemini-powered creative generation and video tools
• Google expands Universal Commerce Protocol and launches new agentic shopping tools
• Google launches Ask Advisor across Ads, Analytics and Merchant Center

Google is expanding its measurement capabilities with new integrations between Google Analytics 360, Meridian and predictive AI reporting tools as announced today at Google Marketing Live 2026.

Driving the news. Meridian, Google’s open-source marketing mix modeling platform, will be integrated directly into Google Analytics 360.

The integration is designed to help advertisers:

• Unify first-party and cross-channel data
• Measure incremental performance
• Forecast campaign outcomes
• Optimize media mix investments

Google is also introducing Qualified Future Conversions (QFCs), a predictive reporting metric powered by Gemini.

QFCs connect current ad activity with future sales signals such as branded search behavior.

How it works. Meridian combines first-party data, media signals and cross-channel performance metrics inside Google Analytics 360 to model incremental impact and forecast outcomes. Qualified Future Conversions uses Gemini-powered predictive signals to estimate how current ad engagement may influence future purchasing behavior.

Over time, Google plans to integrate QFC insights directly into Meridian to improve predictive modeling accuracy.

The updates are part of Google’s broader push to simplify measurement and improve ROI forecasting in an increasingly fragmented media environment.

Why we care. Measurement and attribution continue to grow more difficult as customer journeys become less linear and privacy restrictions expand.

Google’s latest updates show the company investing heavily in predictive modeling, incrementality and AI-assisted forecasting to help advertisers better understand long-term performance.

The combination of Meridian and QFCs could also help marketers make stronger budgeting decisions by linking current campaign activity to future business outcomes.

What to watch. Predictive measurement and incrementality modeling are becoming more important as attribution grows more fragmented. Advertisers will likely test whether Meridian and QFCs provide more actionable forecasting compared to existing attribution and MMM solutions.

Availability. Meridian integrations are coming to Google Analytics 360 globally across all languages. QFCs are currently available in a restricted global pilot with broader beta access expected later this year.

Dig deeper. More Google Marketing Live 2026 news from today:

• Google tests new conversational ad formats in AI Mode and Search
• Google launches AI Performance Insights and Conversational Attributes in Merchant Center
• Google expands Direct Offers with AI-generated bundles, native checkout and travel deals
• Google expands Demand Gen with YouTube creator tools
• Google upgrades Asset Studio with Gemini-powered creative generation and video tools
• Google expands Universal Commerce Protocol and launches new agentic shopping tools
• Google launches Ask Advisor across Ads, Analytics and Merchant Center

Google is adding new creator, video and measurement capabilities to Demand Gen campaigns as it pushes YouTube further into performance advertising as announced today at Google Marketing Live 2026.

Driving the news. The company announced several new Demand Gen updates focused on creator partnerships, product discovery and cross-platform campaign optimization.

Advertisers will soon be able to:

• Use multimodal video creation inside Asset Studio
• Promote creator partnership videos directly within campaign setup
• Upload Merchant Center product videos for dynamic distribution
• Extend Demand Gen campaigns into Google Maps inventory

Google is also expanding checkout links into additional markets and extending product feed support into new verticals including automotive.

According to Google, advertisers with large product selections typically see a 33% increase in conversions when adopting product feeds in Demand Gen campaigns.

Additional measurement updates include:

• Campaign Type Attribution
• Uplift Experiments
• Expanded third-party integrations with companies like TransUnion

Google is also introducing AI-assisted Demand Gen campaign creation, allowing advertisers to use settings from existing campaigns like Performance Max to streamline setup.

How it works. Demand Gen uses AI signals from YouTube, Discover, Maps and Shopping activity to dynamically distribute creative and product feeds across Google surfaces. Advertisers can also use creator videos and Merchant Center product assets to personalize campaigns based on user interest and engagement patterns.

Why we care. Google is increasingly positioning YouTube and Demand Gen as full-funnel performance channels rather than upper-funnel awareness products.

The integration of creator content, Maps inventory and dynamic product experiences reflects how discovery and commerce behaviors are converging across Google properties.

For advertisers, the updates could create new opportunities to connect creator-driven content with measurable conversion outcomes.

What to watch. Google’s continued investment in creator tools and Demand Gen suggests YouTube will play a larger role in performance advertising strategies. Advertisers should also monitor how Maps inventory and creator-led commerce campaigns impact conversion performance.

Availability. Many Demand Gen updates are rolling out globally in open beta.

Dig deeper. More Google Marketing Live 2026 news from today:

• Google tests new conversational ad formats in AI Mode and Search
• Google launches AI Performance Insights and Conversational Attributes in Merchant Center
• Google expands Direct Offers with AI-generated bundles, native checkout and travel deals
• Google brings Meridian marketing mix modeling into Analytics 360
• Google upgrades Asset Studio with Gemini-powered creative generation and video tools
• Google expands Universal Commerce Protocol and launches new agentic shopping tools
• Google launches Ask Advisor across Ads, Analytics and Merchant Center

Google is rolling out major updates to Asset Studio aimed at helping advertisers generate creative assets faster using Gemini as announced today at Google Marketing Live 2026.

Driving the news. Asset Studio will now support AI-powered generation across text, images and video using natural language prompts.

According to Google, the platform can understand:

• Marketing briefs
• Brand guidelines
• Website content
• Campaign goals

The system then generates creative assets across multiple themes and formats.

Google is also integrating Gemini Omni, its multimodal model, into Asset Studio to support video creation workflows.

Advertisers will additionally gain access to 1-Click Creative Testing, which helps identify high-performing assets based on campaign objectives.

How it works. Asset Studio uses Gemini models to interpret a marketer’s brief, brand guidelines, website content and goals. Advertisers can generate and refine assets using natural language prompts while Gemini Omni supports multimodal video creation workflows inside the same interface.

The company says the goal is to centralize creative production and reduce friction for advertisers building campaigns across Google and YouTube.

Why we care. Creative production remains one of the biggest operational bottlenecks for advertisers.

Google’s updates show how generative AI is increasingly becoming embedded directly into campaign production workflows rather than functioning as a standalone creative assistant.

For marketers managing campaigns across multiple surfaces, the ability to rapidly generate and test creative assets at scale could become a significant competitive advantage.

What to watch. As creative generation becomes more automated, advertisers will likely evaluate how AI-generated assets perform compared to traditional creative workflows. Brands may also need to rethink approval processes, governance and brand safety as AI production scales.

Availability. The new Asset Studio features are expected to roll out globally in English this summer.

Dig deeper. More Google Marketing Live 2026 news from today:

• Google tests new conversational ad formats in AI Mode and Search
• Google launches AI Performance Insights and Conversational Attributes in Merchant Center
• Google expands Direct Offers with AI-generated bundles, native checkout and travel deals
• Google brings Meridian marketing mix modeling into Analytics 360
• Google expands Demand Gen with YouTube creator tools
• Google expands Universal Commerce Protocol and launches new agentic shopping tools
• Google launches Ask Advisor across Ads, Analytics and Merchant Center

Google is expanding its Universal Commerce Protocol (UCP) initiative with new checkout features, AI shopping integrations and support for additional industries as announced today at Google Marketing Live 2026.

Driving the news. The company announced several new UCP-powered commerce capabilities designed to support what it calls the “agentic commerce era.”

A key update is the expansion of Universal Cart, which allows shoppers to save products across retailers and complete purchases using Google Pay or retailer checkout experiences.

Google says the experience will soon support brands including Nike, Sephora, Target, Walmart, Wayfair and Shopify merchants such as Fenty and Steve Madden.

The company is also integrating UCP into:

• Direct Offers
• Demand Gen campaigns
• AI Mode shopping experiences
• Shopping ads on YouTube

Google additionally announced buy-now-pay-later integrations with Affirm and Klarna directly inside Google Pay.

How it works. Universal Commerce Protocol (UCP) allows retailers to connect product catalogs, checkout and payment experiences across Google surfaces including Search, AI Mode and Gemini. Users can add products to a shared Universal Cart and complete purchases either through Google Pay or directly on the retailer’s website.

The company is also expanding UCP into additional verticals including hotel booking and food delivery.

Future experiences will allow users to book hotels directly from AI Mode or order food from conversations inside Google Maps.

To help brands improve discoverability across AI experiences, Google is introducing:

• AI Performance Insights in Merchant Center
• Conversational Attributes for product descriptions
• Merchant Center integrations with Ask Advisor

Why we care. Google is laying the infrastructure for AI-assisted shopping and commerce discovery.

As conversational shopping experiences expand across Search, Gemini and Maps, brands may need to rethink how they structure product feeds, descriptions and commerce data.

The update also signals that AI-driven commerce is moving beyond discovery and into transaction workflows, with checkout, financing and promotions increasingly embedded directly into Google experiences.

What to watch. Retailers should pay close attention to how Google integrates checkout, financing and shopping actions directly into AI-powered experiences. The expansion into hotel booking and food delivery also suggests Google is preparing for broader transaction capabilities across Search and Maps.

Availability. Many UCP-powered features are rolling out in the U.S. first, with expansions planned for Canada, Australia and later the U.K. Additional vertical integrations are expected in the coming months.

Dig deeper. More Google Marketing Live 2026 news from today:

• Google tests new conversational ad formats in AI Mode and Search
• Google launches AI Performance Insights and Conversational Attributes in Merchant Center
• Google expands Direct Offers with AI-generated bundles, native checkout and travel deals
• Google brings Meridian marketing mix modeling into Analytics 360
• Google expands Demand Gen with YouTube creator tools
• Google upgrades Asset Studio with Gemini-powered creative generation and video tools
• Google launches Ask Advisor across Ads, Analytics and Merchant Center

Google is introducing a new generation of Gemini-powered ad formats across AI Mode and Search designed to make ads feel more conversational, contextual and helpful as unveiled today at Google Marketing Live 2026.

Driving the news. The company announced several new ad experiences for AI-powered Search, including Conversational Discovery ads, Highlighted Answers, AI-powered Shopping ads and Business Agent for Leads. The updates are part of Google’s broader push to integrate Gemini deeper into Search and advertising experiences.

Conversational Discovery ads are designed to answer a person’s specific question directly inside AI Mode. For example, someone searching for ways to make their home smell like a spa could see tailored creative generated with Gemini that highlights relevant product features.

How it works. Google’s Gemini models analyze the intent behind a user’s query and dynamically generate ad creative tailored to that specific conversation. The ads also include an independent AI explainer that evaluates and summarizes product or service information alongside the advertiser’s messaging.

Highlighted Answers will allow highly relevant ads to appear directly within AI-generated recommendation lists.

Google is also launching AI-powered Shopping ads for high-consideration purchases like TVs and appliances. Gemini will generate custom explainers highlighting why a product may fit a shopper’s needs.

Business Agent for Leads introduces an AI-powered chat experience directly within lead generation ads. Instead of filling out static forms, users can interact with a Gemini-powered brand agent trained on an advertiser’s website.

Google is also expanding its Direct Offers pilot with:

• Promotion bundling
• Native checkout for UCP merchants
• Travel deal integrations
• AI-generated offer recommendations

The updates will roll into AI Mode responses to help shoppers discover deals more naturally.

Why we care. Google is fundamentally changing how ads appear in AI-powered Search experiences.

Instead of relying on static creative and keyword matching alone, advertisers will increasingly need to optimize for conversational discovery, AI-generated explainers and intent-rich interactions.

The announcement also signals that AI Mode is becoming a larger monetization surface for Google. Advertisers that adapt early to conversational ad formats and AI-assisted shopping experiences may gain a competitive advantage as Search behavior evolves.

What to watch. Advertisers should closely monitor how AI-generated explainers and conversational ad placements affect click-through rates, conversion behavior and attribution. The rollout could also signal broader changes in how Search inventory is monetized as AI Mode usage continues growing.

Availability. Conversational Discovery ads and Highlighted Answers are currently being tested in the U.S. on mobile and desktop. AI-powered Shopping ads are expected to roll out later this year in the U.S. Business Agent for Leads is launching in open beta for U.S. advertisers.

Dig deeper. More Google Marketing Live 2026 news from today:

• Google launches AI Performance Insights and Conversational Attributes in Merchant Center
• Google expands Direct Offers with AI-generated bundles, native checkout and travel deals
• Google brings Meridian marketing mix modeling into Analytics 360
• Google expands Demand Gen with YouTube creator tools
• Google upgrades Asset Studio with Gemini-powered creative generation and video tools
• Google expands Universal Commerce Protocol and launches new agentic shopping tools
• Google launches Ask Advisor across Ads, Analytics and Merchant Center

Google Marketing Live 2026 made one thing clear: Gemini is no longer just powering features — it’s becoming the operating system behind Google’s advertising, commerce and measurement ecosystem.

This year’s event focused heavily on agentic AI, conversational Search, automated creative production and AI-assisted shopping experiences. Across Search, YouTube, Merchant Center and Analytics, Google introduced new tools designed to make campaigns more autonomous, predictive and interconnected.

Here’s a recap of the biggest announcements from Google Marketing Live 2026.

Google introduces a new generation of AI-powered Search ads

Google announced several new Gemini-powered ad formats designed for AI Mode and conversational Search experiences.

The updates include:

• Conversational Discovery ads
• Highlighted Answers
• AI-powered Shopping ads
• Business Agent for Leads

These formats are designed to make ads feel more contextual and interactive by embedding AI-generated explainers and conversational experiences directly into Search journeys.

Google also expanded its Direct Offers pilot with AI-generated bundles, native checkout and travel promotions integrated into AI-assisted Search experiences.

Full story: Google tests new conversational ad formats in AI Mode and Search

Google launches Ask Advisor across Ads, Analytics and Merchant Center

Google unveiled Ask Advisor, a new Gemini-powered AI collaborator that connects Google Ads, Analytics, Merchant Center and Google Marketing Platform.

The system acts as a unified assistant capable of helping marketers:

• Build campaigns
• Analyze performance
• Surface recommendations
• Automate operational tasks

Google says Ask Advisor can pull insights across platforms to help marketers move from planning to optimization more quickly.

Full story: Google launches Ask Advisor across Ads, Analytics and Merchant Center

Google expands Universal Commerce Protocol and AI shopping experiences

Google announced major updates to its Universal Commerce Protocol (UCP), Universal Cart and AI-powered checkout experiences.

New capabilities include:

• AI-assisted checkout flows
• Buy-now-pay-later integrations with Klarna and Affirm
• Cross-retailer shopping experiences
• AI-powered travel and food ordering integrations

Google is also expanding UCP integrations into Demand Gen campaigns, YouTube Shopping ads and AI Mode experiences.

Full story: Google expands Universal Commerce Protocol and launches new agentic shopping tools

Asset Studio gets Gemini-powered creative and video tools

Google upgraded Asset Studio with multimodal Gemini-powered creative generation capabilities.

Advertisers can now use natural language prompts to generate:

• Images
• Video assets
• Text variations
• Creative themes

Google also integrated Gemini Omni into Asset Studio to support video workflows and introduced 1-Click Creative Testing for asset optimization.

Full story: Google upgrades Asset Studio with Gemini-powered creative generation and video tools

Demand Gen expands with creator tools, Maps inventory and AI optimization

Google announced several Demand Gen updates focused on YouTube creators, AI-assisted optimization and cross-platform discovery.

The updates include:

• Creator partnership tools
• Google Maps inventory
• Dynamic product video distribution
• AI-assisted campaign setup
• Expanded measurement integrations

Google says advertisers with large product feeds continue seeing stronger conversion performance inside Demand Gen campaigns.

Full story: Google expands Demand Gen with YouTube creator tools

Google upgrades measurement with Meridian and predictive AI tools

Google also announced new measurement and forecasting capabilities for Google Analytics 360.

The company is integrating Meridian, its open-source marketing mix model, directly into Analytics 360 while introducing Qualified Future Conversions (QFCs), a new predictive reporting metric powered by Gemini.

The tools are designed to help advertisers:

• Improve media mix modeling
• Forecast campaign outcomes
• Measure incrementality
• Connect current ad activity with future revenue signals

Full story: Google brings Meridian marketing mix modeling into Analytics 360

Merchant Center gets AI visibility and conversational commerce updates

Google announced new Merchant Center features designed to help retailers improve discoverability across AI-powered shopping experiences.

New tools include:

• AI Performance Insights
• Conversational Attributes
• Merchant Center integrations with Ask Advisor

The updates aim to help retailers optimize product feeds and descriptions for conversational shopping behavior across Search, Gemini and AI Mode.

Full story: Google expands Direct Offers with AI-generated bundles, native checkout and travel deals

Google is introducing Ask Advisor, a new Gemini-powered AI collaborator designed to work across Google Ads, Google Analytics, Merchant Center and Google Marketing Platform as announced today at Google Marketing Live 2026.

Driving the news. Ask Advisor acts as a unified agent that connects insights, workflows and recommendations across Google’s marketing ecosystem.

According to Google, the tool can help marketers launch campaigns, analyze performance and surface optimization recommendations without needing to switch between products.

For example, a marketer could ask Ask Advisor to “find new customers for my hair care products,” and the system would automatically pull product details from Merchant Center and help build a campaign in Google Ads.

How it works. Ask Advisor connects Google Ads, Analytics, Merchant Center and Marketing Platform through a shared Gemini-powered interface. The system can access campaign, audience and product data across products to generate recommendations, automate setup tasks and surface insights based on a marketer’s goals.

Ask Advisor also integrates reporting insights from both Google Ads and Google Analytics to explain campaign performance and recommend next steps.

Google says the goal is to make advanced campaign management and analysis more accessible, even for marketers without deep technical or analytics expertise.

The launch expands Google’s growing portfolio of in-product AI agents and positions Gemini as a central operating layer across advertising and measurement tools.

Why we care. Ask Advisor represents one of Google’s clearest moves yet toward agentic advertising workflows.

Instead of manually navigating between reporting dashboards, campaign tools and optimization settings, marketers may increasingly rely on AI agents to execute operational tasks and surface strategic insights.

The bigger shift is structural: Google is positioning Gemini as the connective layer across its ad stack, which could reshape how campaigns are built, optimized and measured.

What to watch. The biggest question will be how much operational control advertisers are willing to hand over to AI agents. Marketers will also likely watch closely for transparency around recommendations, automation decisions and reporting accuracy as Ask Advisor expands.

Availability. Ask Advisor is currently available in beta for English-language accounts, with additional capabilities expected to roll out later this year.

Dig deeper. More Google Marketing Live 2026 news from today:

• Google tests new conversational ad formats in AI Mode and Search
• Google launches AI Performance Insights and Conversational Attributes in Merchant Center
• Google expands Direct Offers with AI-generated bundles, native checkout and travel deals
• Google brings Meridian marketing mix modeling into Analytics 360
• Google expands Demand Gen with YouTube creator tools
• Google upgrades Asset Studio with Gemini-powered creative generation and video tools
• Google expands Universal Commerce Protocol and launches new agentic shopping tools