How Adobe Adapted To ChatGPT And Gemini Reshaping B2B Buying

To me, the most interesting part of Adobe’s customer zero story is that when AI disrupted how buyers learn, Adobe couldn’t buy a solution because the solution didn’t exist yet.

This is a story of marketing and technology leaders adapting an operating model under pressure and feeding those lessons back into products.

At Adobe Summit, I hear compelling visions for the future of digital marketing. What interests me, however, is what happens after the keynote ends. What does it actually take to operate this way?

That question led me into the research behind our new customer zero case study. I expected a story about AI implementation. Instead, I found a story about operating model adaptation in response to changing buyer behavior.

The Intermediary Changed

As a Forrester analyst, I’m conditioned to reframe mysteries around observable customer behavior. When I did, the investigation took a different turn.

Across the discover, evaluate, and commit stages of the B2B customer lifecycle, generative AI answer engines such as ChatGPT and Gemini have become the top preference for buyers as a source of information. Vendor websites and vendor product experts have been overtaken.

Buyers are increasingly learning about vendors through intermediaries that work for the buyer rather than the vendor. Vendor websites and product experts operate on behalf of the vendor. Answer engines operate on behalf of the user.

That single change has altered the economics of digital discovery.

The Response Was Organizational

Adobe could not solve this problem with a single tool because the challenge was not primarily technological. Adobe established ownership for AI-mediated visibility, installed a continuous review cadence, expanded measurement, embedded human oversight into AI-assisted workflows, and created mechanisms for sharing learning across teams. Adobe.com became a living laboratory where those lessons informed products such as LLM Optimizer.

The Innovation Was Organizational

I started this research trying to bridge the message I heard at Adobe Summit with the operational reality of bringing agentic technology to bear on a real business problem.

Marketing and technology leaders redesigned how the organization sensed change, interpreted signals, governed execution, and distributed learning.

What impressed me most was not Adobe’s use of AI. It was Adobe’s willingness to adapt under consequence.

Research helps leaders anticipate change. Customer zero experiences help leaders understand what adaptation looks like in practice.

Adobe did not wait for a playbook. It built one.

Adobe’s experience reveals a challenge that many technology executives are only beginning to confront: When AI becomes an intermediary between your organization and your customers, competitive advantage increasingly depends on how quickly your organization can sense change, interpret signals, and adapt.

There’s Still More To This Story …

If your organization is evaluating how AI answer engines, agents, and autonomous systems will reshape customer engagement, application strategy, and operational governance, let’s talk.

Schedule an inquiry or guidance session with me to explore how to redesign governance, measurement, workflows, and platform strategy for an AI-mediated world.

Forrester clients can read the report here: Customer Zero Case Study: How Adobe Built A Marketing Learning System For AI-Driven Buying Behavior.