Welcome to today's edition of AI Marketing Geek, your daily dose of the latest AI developments, tools, trends, and actionable insights shaping marketing in 2026. As AI shifts from experimental hype to pragmatic, ROI-driven reality, we're seeing agentic AI take center stage. Autonomous agents are handling media buying, personalization, and commerce, which is wild to watch.

Something that looked like a standards committee project six months ago is starting to look like infrastructure. This morning, IAB Tech Lab's Agent Registry reached 10 active entries, a milestone that marks the initiative moving from theoretical to operational.

The IAB Tech Lab expanded its Agent Registry to 10 active entries, adding new participants including Amazon, Burt Intelligence, Optable, Dstillery, and HyperMindZ.ai, while introducing a three-tier deployment classification system designed to make agentic advertising infrastructure more discoverable and easier to integrate. The announcement was made March 11, 2026. All 10 entries are active and all operate under the Model Context Protocol standard.

The registry sits inside a broader initiative called AAMP, which IAB Tech Lab formally named in late February. AAMP, the Agentic Advertising Management Protocols, is the umbrella initiative under which IAB Tech Lab is developing all its agentic advertising standards work in partnership with the ecosystem. The initiative's scope extends beyond digital advertising into linear television, radio, and out-of-home.

The architecture has three layers. The first is high-performance delivery and execution, where ARTF defines how agent services can safely operate inside advertising systems including real-time bidding environments, cutting latency by 80%. The second is a management layer that defines how buyer and seller agents understand each other, negotiate, and complete transactions. The third is trust, which the Agent Registry serves, providing neutral agent transparency and accountability across the ecosystem.

The practical picture is starting to take shape. IAB Tech Lab demonstrated using its reference implementations to create a media plan based on a brief, negotiate with a seller, confirm the transaction, and push it to Google Ad Manager, all using agentic technology running alongside existing standards like OpenDirect and AdCOM.

This is the slow-moving story that ends up mattering more than the fast-moving ones. When AI agents can autonomously plan, negotiate, and execute media buys across publishers using standardized protocols, the implications for how campaigns get managed are enormous. Watch the Agent Registry grow. The companies building on these protocols now are setting themselves up to operate in whatever the programmatic stack looks like in 2028.

This is the most concrete case study available right now for what it looks like to actually adapt to AI search, and it comes from one of the most SEO-dependent B2B companies on the internet.

HubSpot's organic traffic peaked at around 24 million monthly visits. Between November and December 2024, HubSpot's organic traffic fell from 13.5 million to 8.6 million, a loss of nearly 5 million visits in a single month. By early 2025, estimates put their monthly organic visits as low as 6 to 7 million, a dramatic decline following Google's algorithm updates that prioritized user-generated content over traditional blog content.

CMO Kipp Bodnar described the team as being in "the pit of despair." Then they rebuilt. When AI Overviews began taking traffic from HubSpot's blog, Bodnar created an answer engine optimization strategy to ensure its content wasn't lost. The result: citations improved 433%, and AI-referred demand rose by 1,850%. Today, HubSpot's CRM has the highest share of voice in its category, and visitors from AI platforms tripled compared with traditional search and spend more per visit.

HubSpot replaced the linear inbound funnel with a framework called Loop Marketing, built around four phases: Express, Tailor, Amplify, and Evolve. The team saw an 82% lift in email conversions and AI engine traffic converting at three times the prior rate. HubSpot set up experimental pods whose entire mission was to learn as quickly as possible and share findings weekly across the organization.

The thing worth noting here is that HubSpot's traffic is still way down. They are not claiming to have recovered clicks. What they recovered was demand, which is the thing that actually pays for a business. HubSpot's content now performs well within AI-generated responses. Their traffic from LLMs is increasing because they are marketing to both humans and AI models, and as LLMs become an increasingly relevant platform, that investment has begun paying off.

The lesson is uncomfortable but clear. Optimizing to be cited by AI is now a distinct content strategy from optimizing to rank on Google. They overlap in places, but they are not the same job. HubSpot had the scale and resources to build a dedicated team around this. Most firms do not, which is exactly why understanding the mechanics of their playbook matters.

Before you build a GEO strategy, you need to know where you currently stand. Here is a quick audit you can do this week without paying for anything.

Open ChatGPT, Claude, and Perplexity. Search for the questions your best clients actually ask when they are evaluating someone like you. Not your keywords. The actual questions. Things like "how do I choose a fractional CMO" or "what does a law firm need to know about Google Ads." See which brands come up. See if yours does. If a competitor is being cited consistently and you are not, that is the gap.

Next, look at your pages from the AI's point of view. AI systems favor content that answers a specific question in the first two or three sentences of a section, uses clear headings structured as questions, includes a named author or firm with visible credentials, and contains at least one specific stat or cited claim. Run your top five pages against that checklist.

Finally, check your Google Search Console for impressions versus clicks. If your impressions are holding steady but your click-through rate is dropping, AI is answering the question before users get to your listing. That is not a ranking problem. It is a GEO problem, and ranking higher will not fix it.

The goal right now is not a full audit. It is getting a real picture of where you stand so you know whether you are invisible to AI engines or just underoptimized. Those require different fixes.

2026 is the year AI moves from "cool demos" to real and measurable business use cases. Expect more agentic tools, voice-powered targeting, and a focus on privacy-first data.

Stay ahead of the game by treating your AI reputation like your website. It would behoove you to make your brand easy for agents to understand and cite.

What AI experiment are you running this week? Reply and let me know. I'll feature top stories in future editions! (Everybody loves a good story)

Stay sharp,
Jon
@mistersterling
Chief AI Marketing Geek