Recently, I’ve been exploring the fascinating divergence in AI adoption between professional circles and general consumers. According to Datos and SparkToro’s latest data, this trend is becoming increasingly apparent.
It was intriguing to see how AI usage is starting to plateau among consumers while remaining on the rise in professional environments. Tools like Claude, ChatGPT, and Gemini are seemingly more popular in the B2B landscape.
Why we care. As I delve deeper into AI’s impact, it’s becoming clear that a universal AI strategy won’t work for everyone. It’s essential to identify whether my audience aligns with these broader trends or if their AI engagement habits are entirely different.
ChatGPT desktop growth slowed. From Fishkin’s analysis, it appears that ChatGPT’s usage in the U.S. has stagnated over recent months while Claude and Gemini continue their growth trajectories. It seems that professionals are continually finding value in these tools.
At its zenith, 37% of U.S. desktop users engaged with OpenAI or ChatGPT back in September 2025. This number dipped slightly to 34% by March, a trend mirrored, albeit with higher numbers, in the EU and U.K.
Claude gained with professionals. I noticed Claude is particularly gaining traction among professional users. Fishkin’s data suggests a significant rise in usage among business professionals, resonating with the notion that AI adoption is stronger in B2B contexts.
The analysis even revealed that Claude’s use among B2B professionals was 373% higher than the U.S. average, reinforcing the tool’s growing popularity in business circles.
Consumer audiences look different. Interestingly, when it comes to the retail-shopping consumer audience, ChatGPT isn’t as prevalent, being 15% less likely to be used compared to the typical American consumer. For this group, Claude isn’t even in the top four AI tools.
This might explain why AI seems so prevalent in professional networks like LinkedIn, while its visibility is not as pronounced among general consumers.
The research. You can view Rand Fishkin’s detailed insights on LinkedIn by watching his video here.
When I attended Google Marketing Live 2026, I witnessed firsthand how Gemini is reshaping the world of Search, advertising, commerce, and measurement. The event highlighted the move towards a more conversational, AI-driven ecosystem.
This year, the focus was on agentic AI, conversational Search, automated creative production, and AI-assisted shopping. Google rolled out tools across Search, YouTube, Merchant Center, and Analytics aimed at making campaigns more autonomous, predictive, and interconnected.
Let me take you through the biggest announcements from Google Marketing Live 2026.
Google Introduces a New Generation of AI-Powered Search Ads
Google rolled out new Gemini-powered ad formats that enhance AI Mode and conversational Search experiences.
The updates include:
Conversational Discovery ads
Highlighted Answers
AI-powered Shopping ads
Business Agent for Leads
These innovative formats are crafted to be more contextual and interactive by embedding AI-generated explanations and conversational experiences directly into Search journeys.
Plus, Google expanded its Direct Offers pilot with AI-generated bundles, native checkout, and travel promotions seamlessly integrated into AI-assisted Search experiences.
Google Launches Ask Advisor Across Ads, Analytics, and Merchant Center
At the event, Google introduced Ask Advisor, a Gemini-powered AI collaborator that bridges Google Ads, Analytics, Merchant Center, and the Google Marketing Platform.
It functions as a unified assistant to help marketers:
Build campaigns
Analyze performance
Receive recommendations
Automate operational tasks
Google assures that Ask Advisor expedites the process from planning to optimization by pulling insights across platforms.
Google Upgrades Measurement with Meridian and Predictive AI Tools
Google announced new tools for measurement and forecasting within Google Analytics 360.
Meridian, an open-source marketing mix model, is being integrated directly into Analytics 360, along with Qualified Future Conversions (QFCs), a predictive reporting metric powered by Gemini.
These tools will assist advertisers in:
Improving media mix modeling
Forecasting campaign outcomes
Measuring incrementality
Linking current ad activity with future revenue signals
Today, I’m excited to share that Google is taking a significant leap forward in the world of online shopping by expanding its Universal Commerce Protocol (UCP). This comes with a host of AI-powered checkout and payment features designed to enhance conversational commerce experiences.
At the recent Google Marketing Live 2026 event, they unveiled these exciting new features. One of the highlights is the Universal Cart. It lets me save products from multiple retailers and complete my purchases effortlessly using Google Pay or the retailer’s own checkout system.
It’s thrilling to see major brands like Nike, Sephora, Target, and more jumping on board. They’re also integrating UCP into AI Mode shopping experiences and their ads on platforms like YouTube.
Furthermore, Google’s new partnerships with Affirm and Klarna for buy-now-pay-later options integrated into Google Pay bring a fresh breath of convenience to shoppers like me.
Universal Commerce Protocol connects product catalogs, checkout, and payment experiences seamlessly across Google’s surfaces, including Search and Maps. Soon, I can expect it to support hotel bookings and food deliveries, which means even more convenience for us end-users.
As an avid online shopper, I appreciate how Google is making strides towards enhancing AI-driven commerce. They’re set to reshape how brands like mine will structure product feeds and promotional strategies.
Currently, these new UCP-powered features are rolling out in the U.S., and I’m eagerly waiting for their expansion to more countries, including Canada and the U.K.
To delve deeper into what unfolded at Google Marketing Live, check out updates on innovations like conversational ad formats and Google’s AI-driven tools in their Merchant Center.
Today, I’m excited to share that Google is making significant enhancements to Asset Studio, aimed at helping advertisers like us generate creative assets more efficiently by leveraging the power of Gemini. This was announced at Google Marketing Live 2026.
Driving the news. Asset Studio will now feature AI-driven creation capabilities across text, images, and videos, allowing us to use natural language prompts to guide the process.
Google assures us that the platform is capable of understanding:
Marketing briefs
Brand guidelines
Website content
Campaign goals
By doing so, it generates creative assets that span different themes and formats, tailored to our needs.
Additionally, Google is integrating the Gemini Omni, their multimodal model, into Asset Studio. This enhances our workflows, especially in video creation.
With 1-Click Creative Testing, we can quickly identify top-performing assets in terms of campaign objectives. This means more efficient testing and better results for us.
How it works. By applying Gemini models, Asset Studio interprets our marketing briefs, guidelines, and objectives. Using natural language prompts, we can generate and perfect our assets, whether they’re text, image, or video. Plus, Gemini Omni ensures our video workflows are seamless.
The aim is clear: centralize creative production and minimize the challenges we face when building campaigns across platforms like Google and YouTube.
Why we care. Creative production bottlenecks are a major issue for us advertisers. Google’s updates show that integrating generative AI into our workflows makes creative production much more streamlined.
For those of us managing cross-platform campaigns, the ability to swiftly generate and test creative assets is a game-changer.
What to watch. As we automate more of our creative processes, it’s important to compare the performance of AI-generated assets against those from traditional workflows. We might need to rethink approval processes and brand safety in light of AI’s growing role.
Availability. We can expect the new Asset Studio features to become globally available in English this summer, opening up new possibilities for our advertising strategies.
Dig deeper. There are more updates from Google Marketing Live 2026 that are worth exploring for additional insights and tools that could benefit our campaigns. For example:
Today, I discovered some exciting news about Google’s expansion of Demand Gen with fresh YouTube creator tools. It’s all about enhancing performance advertising and was recently highlighted at Google Marketing Live 2026.
Here’s the scoop. Google has unveiled new updates for Demand Gen with a focus on partnerships with creators, innovative product discovery methods, and improved cross-platform campaign optimization.
As an advertiser, I soon will be able to:
Create engaging videos using the multimodal capabilities of Asset Studio.
Seamlessly integrate creator partnership videos during campaign setup.
Dynamically share Merchant Center product videos directly from campaign structures.
Include Demand Gen campaigns in Google Maps for increased outreach.
Google’s also pushing checkout links into more markets and expanding product feed support to new verticals, such as automotive. They mentioned that advertisers with vast product options tend to experience a 33% boost in conversions with product feeds.
Additional improvements in measurement include:
Campaign Type Attribution to understand source impact.
Uplift Experiments for deeper insights.
Enhanced third-party integrations with partners like TransUnion.
I also learned about Google introducing AI-assisted Demand Gen campaign creation, which uses existing campaign settings, like those from Performance Max, to simplify setup processes.
Understanding the mechanism. Demand Gen harnesses AI signals across YouTube, Discover, Maps, and Shopping to smartly allocate creative and product feeds amidst Google’s platforms. Advertisers, like myself, can leverage creator videos and Merchant Center product assets for more tailored campaigns responsive to user interest and engagement techniques.
The reason it’s noteworthy. Google’s tactic to pitch YouTube and Demand Gen as comprehensive performance channels shows a shift from just creating awareness. The merge of creator content, Maps inventory, and dynamic product experiences epitomizes the evolving intersection of discovery and commerce within Google’s ecosystem.
For us, the advertisers, these updates are a golden opportunity to marry creator-driven content with tangible conversion metrics.
What’s ahead. Google’s ongoing focus on creator tools and Demand Gen sets the stage for YouTube’s larger involvement in performance advertising plans. It’s essential to keep tabs on how Maps inventory and creator-led commerce campaigns may influence conversion performances.
When can we expect it? Many of these Demand Gen updates are globally expanding in open beta.
Want more insights? Check out more from Google Marketing Live 2026:
Today, I’m excited to share that Google is making Analytics 360 even more powerful by integrating the Meridian marketing mix modeling platform. They’ve also introduced a new predictive conversion metric that promises to enhance media mix decisions for advertisers.
I learned about these updates during the Google Marketing Live 2026 event, where Google unveiled several enhancements aimed at expanding measurement capabilities. The integration of Meridian, Google’s open-source marketing mix modeling tool, directly into Analytics 360 is a significant step forward.
Driving the news. With this integration, I’m able to unify first-party and cross-channel data, measure incremental performance, forecast campaign outcomes, and optimize media mix investments with greater ease.
Moreover, Google is rolling out Qualified Future Conversions (QFCs), a predictive reporting metric powered by Gemini. QFCs link current ad activity to future sales signals like branded search behavior, providing insights that were previously harder to visualize.
How it works. From my perspective, Meridian combines first-party data, media signals, and cross-channel performance metrics in Analytics 360. This helps to model incremental impact while Qualified Future Conversions use Gemini’s predictive signals to understand potential future purchasing behaviors.
In the long run, Google aims to integrate QFC insights into Meridian for more accurate predictive modeling. This is part of their broader effort to simplify measurement and refine ROI forecasting in today’s complex media landscape.
Why we care. As I’ve observed, measurement and attribution are becoming increasingly challenging with evolving customer journeys and the emphasis on privacy. These latest updates highlight Google’s commitment to helping advertisers like us better understand and plan for long-term performance.
The combination of Meridian and QFCs can empower marketers to make better budgeting decisions by accurately linking current campaign activity to future outcomes. It’s a tool we should all keep an eye on.
What to watch. Predictive measurement is becoming crucial. I’m looking forward to testing whether Meridian and QFCs can offer more actionable forecasting compared to existing solutions.
Availability. I found out that Meridian integrations are rolling out globally in Google Analytics 360, supporting all languages. QFCs are in a restricted global pilot phase, with wider beta access anticipated later this year.
Dig deeper. If you’re interested, there’s more news from Google Marketing Live 2026, including tests of new conversational ad formats and AI-powered tools in the Merchant Center, as well as expansions across various Google services.
I’m excited to share that Google is enhancing its Direct Offers with AI-generated bundles, native checkout features, and enticing travel deals. This announcement, made at Google Marketing Live 2026, marks a significant upgrade for the platform.
Driving the news. Google aims to make promotional offers more visible within AI-powered Search experiences.
Brands will soon have the ability to upload a variety of promotional types:
– Discounts
– Giveaways
– Local coupons
– Product bundles
Google’s Gemini will assist in creating personalized offers that align with search intent. This means tailored promotions based on user queries and browsing habits.
How it works. Advertisers can upload eligible promotions and campaign guardrails through Google Ads. Gemini will then curate relevant offers like bundles and discounts that resonate with the shopper’s search and browsing behavior.
Additionally, Google is introducing native checkout support for merchants using the Universal Commerce Protocol (UCP), enabling users to complete purchases directly within AI-driven shopping experiences.
Travel partners such as Booking and Expedia will soon showcase travel offers directly within AI-assisted trip planning features, enhancing the overall travel booking experience.
Why we care. This integration is transforming promotions into an integral part of conversational shopping, steering away from conventional deal extensions and static offers.
Advertisers now need to optimize their promotions to fit within AI-powered discovery and recommendation systems.
The introduction of native checkout options is expected to streamline the transition from product discovery to conversion, potentially boosting sales.
What to watch. It’s worth observing how Google’s shift towards AI-assisted promotional commerce influences conversion rates and consumer shopping patterns.
Availability. Currently, Direct Offers is available as a pilot for advertisers in the U.S.
Dig deeper. Stay informed with more updates from Google Marketing Live 2026:
Today, I’m thrilled to share that Google has unveiled exciting new tools in the Merchant Center, all geared towards boosting retailer visibility on AI-driven shopping platforms. Announced at Google Marketing Live 2026, these tools are set to transform how products are discovered.
Driving the news. Let me introduce you to AI Performance Insights, a fresh reporting feature that gives merchants a snapshot of their brand’s performance across AI platforms.
This handy tool lets me compare my brand’s share of voice with similar competitors, ensuring I stay on top of AI-driven discovery metrics.
Google is also introducing Conversational Attributes, enhancing how we optimize our product listings to align with natural, conversational searches.
How it works. I can now add conversational attributes and update descriptions directly in the Merchant Center. Google’s AI can utilize this structured data to meet conversational search queries seamlessly across AI Mode, Gemini, and other AI platforms.
These updates are crafted to enhance discoverability as AI continues to reshape shopping experiences.
Moreover, Ask Advisor integrations are soon to be part of my Merchant Center tools.
Why we care. Structured product data is now more essential than ever as AI shopping experiences proliferate across Search, Gemini, and Maps.
By adapting product descriptions for conversational discovery, I can better position my products within AI-generated recommendations and shopping paths.
These new reporting tools also give me early visibility into how my brand performs in AI-powered environments.
What to watch. With the rise of conversational search behavior, optimizing product feeds for AI visibility is becoming increasingly critical. I’ll also be keeping an eye on how Google defines and measures “share of voice” within these AI-powered shopping ecosystems.
Availability. AI Performance Insights will soon roll out in the U.S., Australia, Canada, India, and New Zealand. Meanwhile, Conversational Attributes are launching globally.
Dig deeper. Here are some more updates from Google Marketing Live 2026:
I’ve recently discovered that Google has introduced a new feature in Chrome Lighthouse to check for llms.txt files. Though Google mentions that llms.txt isn’t necessary for AI search visibility, Lighthouse has started flagging sites based on their presence.
Google’s latest Lighthouse audits, under the “Agentic Browsing” category, now focus on a site’s usability for machine interaction. I find this interesting as it aligns with Google’s push towards better machine readability.
The new audits are part of Chrome’s evolving “Agentic Browsing” features, which analyze if sites are prepared for automated interaction. This concept came soon after Google issued guidance on AI search optimization, debunking the necessity of llms.txt files in their new guide on generative AI features.
What Lighthouse Evaluates Now. Lighthouse’s Agentic Browsing tests focus on how well my site is built for machine interactions, incorporating various deterministic audits as per Google’s documentation. These checks include:
– WebMCP integration.
– Accessibility tree integrity.
– Layout stability through CLS.
– Presence of an llms.txt file.
These audits help ensure that there’s a machine-readable summary at the site’s domain root. Google explains that without llms.txt, agents might take longer to understand a site’s main structure.
The impact of these audits doesn’t translate into a traditional Lighthouse score but into a fractional pass ratio related to agentic readiness signals.
The Tension. Interestingly, while these audits don’t directly affect SEO rankings, their mention in Google’s readiness checks could make SEOs reconsider their stance on llms.txt files.
Agentic Engine Optimization. Google’s approach aligns with insights shared by Addy Osmani from Google Cloud AI about Agentic Engine Optimization. Osmani emphasizes creating web content that is semantically structured, token-efficient, and easy for AI to process.
SEO vs. llms.txt. According to Google, creating llms.txt or similar files isn’t necessary for AI search success, as outlined in the guide on Mythbusting generative AI search. The AI systems can discover, crawl, and index a variety of file types encountered on the internet.
John Mueller from Google responded to concerns about the role of llms.txt in a discussion with Lily Ray on Bluesky, stating that the use of these files is more for functionality and not directly linked to search engine optimization.
Google’s Take on AI Agents. Besides llms.txt, Google’s Lighthouse guidelines place strong emphasis on accessibility and interface stability. The insight I gained is that AI agents heavily rely on the accessibility tree as their core data model, focusing on integrity and proper layout.
Ultimately, while Google indicates llms.txt isn’t needed for search, including such files might be beneficial for adapting to Google’s evolving tools that prioritize machine readability.
When I hear about Microsoft rolling out its latest AI-powered features for advertisers, I can’t help but feel excited about the potential ease it could bring to multi-platform ad campaigns.
The unveiling of the new Import Center really caught my attention. It’s designed to streamline the way we can transfer campaigns from Google Ads and Meta Ads into Microsoft Advertising.
This impressive hub offers me the ability to search and filter campaign imports, edit or pause them as needed, access those imported campaigns with ease, view troubleshooting guidance, and even get performance recommendations once the imports are done.
Microsoft assures that this is all about minimizing the hassle of manual troubleshooting and simplifying how we manage campaigns across different platforms.
I find the expansion of AI-powered bidding capabilities particularly appealing as it includes cross-account portfolio bidding for both Search and Shopping campaigns. This addition allows me to handle portfolio bid strategies efficiently across various accounts, optimizing my budget by pooling significant signals.
The enhanced bid strategy reporting metrics such as Avg. Target ROAS, Avg. Target CPA, and Avg. Target impression share are promising tools that let me comprehend bid performances better and adjust targets from within the UI.
Reporting has become even more flexible thanks to the new custom column capabilities. This expansion gives me access to all conversion metrics in custom columns, allows segment reports by goal name, and lets me dive into additional metrics like CPA and ROAS, enhancing transparency and optimization insights.
In my perspective, these updates make campaign management far more seamless across all platforms, including Google, Meta, and Microsoft Ads, while expanding AI-powered bidding and automation.
I’m also catching up with two previously announced updates from Microsoft that are now widely available: seasonality adjustments for portfolio bidding and shared budgets, and the data-driven attribution for automated bid strategies.
By assigning conversion credit across the customer’s journey in campaigns that use Maximize Conversions, Maximize Conversion Value, and Enhanced CPC bidding strategies, these features could be transformative.
