I’m introducing FactCheck as a new way for brands to understand how accurately AI engines describe them at scale.
AI engines can make claims about my brand that simply are not true. With FactCheck, I can measure what is accurate, identify what is wrong, and see which sources are driving those errors.
That visibility matters because AI-generated answers are increasingly shaping how people discover, evaluate, and trust brands. FactCheck helps me move from guessing about AI accuracy to actually analyzing it with clarity.
I’ve noticed something exciting happening with Google Search Console lately. The AI performance reports are becoming accessible to a wider audience, and it’s a game-changer for those of us eager to see how our content performs in Google’s AI environments.
John Mueller from Google recently shared on Bluesky, “We’re just rolling these out incrementally to sites, and reviewing the feedback along the way. I know everyone wants the new shiny thing immediately… but first, patience.” It’s like waiting for a gift you’ve been longing for!
AI performance report. These reports offer insights into how well our content and websites are featured in AI-driven searches, showcasing metrics such as impressions, pages, countries, devices, and dates. Although it doesn’t yet track click data, it’s still a significant step forward.
Expanding access. Earlier today, I spotted several SEOs sharing that these reports are now available beyond the UK! They’re able to access reports for sites in the US, India, Switzerland, and more.
As John mentioned, Google is gradually rolling these updates out to more sites, listening to feedback, and hopefully moving towards a global release.
What it looks like. Here’s a snapshot of the report:
Why we care. As someone deeply invested in how content is presented, I find this development thrilling. Publishers and site owners like me have long wanted more control over Google’s AI features. The speed at which Google has rolled this out is impressive—just within 20 days of its initial release!
I’ve got some exciting news to share! I’m thrilled to introduce the revamped Profound Index, your go-to leaderboard for AI Search. This update marks a new era in search, providing both clarity and authority in the rapidly evolving world of AI-driven solutions.
In this rebuild, we focused on enhancing the user experience and performance metrics. Whether you’re an AI enthusiast or a professional seeking the latest insights, the improved Profound Index is designed with you in mind. Its comprehensive data sets and intuitive interface make it an indispensable tool for anyone looking to stay ahead in the realm of AI Search.
I’ve come to realize that prompt tracking is often misunderstood as mere noise, but it’s actually a golden opportunity to refine AI interactions through a structured approach.
AI responses can be unpredictable. However, by utilizing repeated runs, establishing fixed sampling rules, and calculating confidence intervals, we can transform variance into a trustworthy metric.
By embarking on this journey with me, you’ll soon be equipped to create a reliable AI tracking system.
For those immersed in AI SEO strategies, understanding the true trajectory of your efforts over the noise is crucial. Explore more with How Much Can We Influence AI Responses.
While many have dismissed prompt tracking due to its variability, I’ve discovered that it mirrors the unpredictability seen in weather forecasts and credit scoring, which are still meticulously tracked.
Reflecting on keyword tracking’s evolution, I see a parallel path for prompt tracking, which requires adapting its methodology to account for the numerous platforms now at play.
At pivotal industry events, experts speak of a shift from single search queries to a conversational model, emphasizing the changing landscape we must adapt to.
The shortcomings of current prompt-tracking tools are evident in their lack of innovation, yet I believe we can rise above with a more strategic approach.
Although single-turn prompts provide limited insight, constructing full conversational sequences reveals persistence, a vital metric often overlooked.
Imagine tracking a B2B SaaS CRM journey through defined stages, extending prompts to capture decision-making across multiple touchpoints to truly gauge influence.
HubSpot’s visibility across platforms like ChatGPT and Perplexity illustrates the nuanced understanding needed to strategize investments in brand-centric content.
The future of prompt tracking resembles opinion polling, employing systematic and repeatable methodologies to extract meaningful data amidst variability.
This piece first appeared on the author’s website and is shared with permission here.
I’ve discovered that Profound is the ultimate hub for marketers aiming to excel in the AI-driven landscape. It’s where I run my visibility, sentiment, and accuracy analyses.
This platform is my go-to for building marketing Agents and uncovering new opportunities. It’s here that I generate innovative content and take action based on deep insights.
Given all these functions, it’s only natural that Documents have found a home here too. Profound seamlessly integrates document management into my existing marketing workflow.
As someone who eagerly follows Google’s updates, I was thrilled to learn about the latest developments in Google Search Console. Recently, Google has started to roll out new Search Generative AI performance reports. These reports, along with a feature to block your content in AI responses, are designed to give website owners more control.
Currently, these features are being introduced to a select group of website owners in the UK, but there are plans to expand access in the near future. This gradual rollout allows us to get accustomed to these changes before they become widely available.
Exploring the Search Generative AI Performance Report
The new AI performance report in Google Search Console is something I’ve been anticipating. Although it doesn’t cover everything, it does provide some important insights into how our content is performing within AI responses, AI Mode, and AI Overviews on Google Search. The report includes data on impressions, pages, countries, devices, and dates. However, a notable omission is click data, so we’re left guessing about the exact number of searchers clicking through to our sites from AI responses.
Google stated:
– We’re rolling out new insights for website owners regarding their pages’ appearances in generative AI Search features. These insights include impressions metrics and information on which pages appear in AI responses and in which countries. We’re working closely with website owners to determine what insights would be most helpful and will expand the metrics available over time.
Additionally, Google shared more details about the metrics we can expect:
– Impressions: Frequency of your site’s URLs appearing in generative AI features in Search and Discover.
– Pages: Identifying URLs that appeared within AI features.
– Countries: Understanding visibility on a country basis.
– Devices: Identifying the devices used to view your website. Available for Search results.
– Dates: Monitoring performance with hourly, daily, weekly, and monthly granularity.
I inquired about click data from a Google representative, who mentioned that they are exploring additional metrics that will help inform our strategies in the future.
Initially, this report is available to a subset of users in the UK, with plans to expand globally in the future.
Another exciting feature Google introduced is the ability to block your content from appearing in AI search features like AI Overviews, AI Mode, or AI Discover. Google described this as a “new toggle” within Google Search Console, allowing us to decide whether or not our site should be part of these AI search features.
Google notes that opting out will prevent your site from receiving traffic or impressions from these features. Importantly, this control won’t affect your ranking in standard search results outside of generative AI Search features, so there’s no risk of negatively impacting core web search visibility.
Again, like the performance report, this toggle is currently available to a subset of UK website owners, with plans to widen access as they complete further testing. Google had promised these controls after facing some backlash from the EU, and it’s promising to see them starting to roll out now.
One study even showed that 1/3rd of SEOs are willing to block Google from showcasing their content in AI search features.
Why It Matters
As site owners and publishers, many of us have been asking for control over how and if our content appears in Google’s AI features. Now, we have just that. Although it’s initially limited, I’m hopeful these features will eventually be available to all.
Moreover, we’ve been requesting AI Search reporting from Google from day one. With Google’s announcement following Bing’s release of its own AI performance report, we’re taking a significant step forward. While Google’s report currently targets UK site owners and lacks click data, it holds promise for a global rollout soon.
From February to May 2026, I dove deep into the fascinating world of agentic AI adoption. I explored how it’s being embraced by enterprises, mid-market players, and SMBs across the U.S. and worldwide. By gathering insights from top consulting firms like McKinsey, Gartner, and IDC, as well as academic institutions and AI leaders, I pieced together a comprehensive overview of agentic AI’s current landscape.
This report fuses insights from over 30 research efforts and industry surveys, covering 15,000+ businesses. It provides a granular look into how businesses are integrating autonomous AI agents this year, breaking it down by company size, industry, deployment stage, primary use cases, and adoption and abandonment patterns.
*Statistics are based on data up to May 14, 2026, unless indicated otherwise.
While generative AI generates immediate outputs, agentic AI shifts the way systems function entirely. This piece zeroes in on agentic AI’s adoption, defined as follows:
Agentic AI revolves around AI systems autonomously planning, deciding, and executing complex tasks from beginning to end.
The term adoption signifies any case where an organization uses at least one agentic AI system at any stage, from initial trials to full-scale implementation.
Meanwhile, abandonment involves halting an agentic AI program or specific projects. This doesn’t always mean closing an organization’s entire AI operations, as they might continue other initiatives.
Agentic AI adoption significantly varies by organization size. A breakdown of recent adoption rates across different segments unveils fascinating trends.
As I dug into the data, I discovered enterprises are leading the way with 25% adoption, thanks to their resources and AI budgets. However, smaller sectors, like mid-market firms and SMBs, are catching up fast. Their year-on-year growth rates are even outpacing those of enterprises!
I predict that SMBs and mid-markets will continue adopting agentic AI faster than their larger counterparts. This trend is partly driven by accessible solutions such as Salesforce Agentforce and Microsoft Copilot Studio, which empower companies with tighter budgets. In contrast, enterprises face challenges due to their intricate systems and diverse data environments.
Agentic AI deployment spans various maturity stages, presenting unique challenges depending on available resources. For SMBs, scaling can be costly, making it particularly challenging.
The table showcases deployment stages among adopters, revealing that 62% of enterprises, despite higher resources, linger in the experimentation phase. Notably, only 13% achieve full deployment.
A few patterns stand out from the data:
Firstly, experimentation predominates across sizes, with a 56% average gap to partial deployment. This highlights caution across sectors in deploying agentic AI.
Despite enterprises’ resources, mid-market companies are seeing greater partial deployment rates, likely due to fewer approval bottlenecks and more budgetary leeway compared to SMBs.
Also, scaling correlates with resources. Enterprises, despite early-stage phases, manage full-scale deployment at rates double those of mid-markets.
These patterns reveal that most organizations are still exploring, with few transitioning to production deployment.
It’s not all smooth sailing. According to Gartner, around 40% of agentic AI projects might be canceled by 2027, due to challenges encountered during deployment.
Although abandonment rates generally decline over time, mid-markets still see higher rates due to their broader range of obstacles and fewer resources compared to large enterprises.
Summarizing the common reasons for project failures:
Data quality matters. Without quality data, agents struggle, highlighting a universal need for centralized and uniform data pre-deployment.
Clear expectations are vital. Projects without well-defined success criteria often fail to demonstrate value, risking cuts in resources when results are inconspicuous.
Costs weigh heavily on SMBs. For SMBs, financial constraints dominate abandonment reasons, overshadowing other factors. Mid-market firms display more varied primary drivers.
Such insights explain why full implementation is elusive for many, despite significant investments. Companies need to address multiple challenges concurrently to progress beyond experimentation.
On an industry level, exploring adoption across sectors shows where agentic AI thrives and lags. Regulatory factors, data readiness, and competitive dynamics result in differing adoption levels.
Industries like education, construction, and real estate lag, owing to budget constraints, less advanced data infrastructures, and fewer automation opportunities. Nonetheless, even these sectors demonstrate notable enterprise adoption, signaling a broader reach beyond tech and financial services.
Finally, examining use cases underscores where agentic AI is making headway. Customer service and supply chain coordination rank high due to their structured processes. On the other hand, finance sees lower adoption due to stringent regulatory scrutiny.
If you fancy obtaining a PDF copy of this insightful report or learning more about our work, feel free to reach out here.
For further exploration into agentic AI and its surrounding trends, consider delving into the following reads:
