AI is the intermediary your customer talks to first. Martech Futurist | July 2, 2026
Recent research keeps circling the same shift, and it's a big one. AI has stopped being another tool you bolt onto the martech stack. It's becoming the layer that sits between your brand and your customer. It’s the intermediary that decides what a buyer sees before they ever reach you. That reorders how discovery works underneath. It isn't a surface change you can patch with a campaign.
Start with discovery. AI answer engines like ChatGPT, Claude, and Gemini are becoming the front door for finding products, and they don't reward brand awareness or a good story. They reward interpretability. A model needs to read your product's attributes and find third-party evidence that backs them up. Structured data does the work a tagline used to do. Decades of symbolic equity buy you nothing here; a brand can be beloved and still go missing from the recommendation entirely.
Then there's adoption, which is stalling across most marketing organizations. The tech isn't the bottleneck. The problems are organizational — data that lives in fragments, success metrics nobody agreed on, too many tools that don't talk to each other. The teams pulling ahead treat AI as a change-management problem and staff it that way. Buying the license was never the hard part.
And the CX conversation has moved past optimization. The real question is orchestration, and whether your systems can hand a customer's context from one touchpoint to the next without dropping it. The winners in this next phase won't be the ones with the most advanced AI. They'll be the ones who kept people at the center and built systems connected enough to carry context all the way through.
The distance between what vendors promise and what enterprises have actually deployed is still wide. Adobe, Optimizely, and Sitecore are all racing to own the answer-engine optimization layer. Meanwhile 69% of organizations are still only piloting these tools — running the experiment, not operating it. So the CMO decision is fairly stark: build the data and content infrastructure now, or accept a real chance of being locked out of AI-mediated customer journeys inside 18–24 months. There's not much runway left to move deliberately.
Emerging Themes Across This Week's Research & Articles
Theme 1 — The AI Visibility Crisis: Traditional brand-building metrics (awareness, share of voice, emotional resonance) are becoming insufficient for AI-mediated discovery. Brands must now compete for AI recall share — how reliably they are retrieved as a solution when their attributes match a user's query. This requires a cross-functional shift in how brand value is structured and communicated.
Theme 2 — AI Operations Maturity Gap: Despite near-universal AI tool adoption, only approximately 33% of organizations have moved beyond experimentation. The bottleneck is structural: undefined strategy, non-standardized processes, dirty data, tool sprawl, and change management failures. Marketing operations teams are at the epicenter of this challenge.
Theme 3 — CX as a System, Not a Channel: Forrester's June CX events and research reinforce that fragmented brand, customer, and employee experiences are breaking growth. The organizations winning are those aligning all three into a coherent system — and the AI era is accelerating the cost of fragmentation.
Theme 4 — B2B Influence and the AI Buying Journey: B2B social media influencers now play a more central role than ever in the buying journey, while AI is reshaping how B2B buyers discover and shortlist vendors before ever engaging sales. CMOs must rethink both their content architecture and their influencer strategy simultaneously.
Featured Insights
How to Get AI to Surface Your Brand
Source: Harvard Business Review (https://hbr.org/2026/06/how-to-get-ai-to-surface-your-brand) | Authors: John Gale, Luca Cian, Luc Wathieu | Published: June 29, 2026
Research across 15 retail categories and 1,000+ brand mentions on ChatGPT, Claude, and Gemini reveals that only 8.4% of brands appear consistently across all three platforms — and AI systems recommend brands based on interpretability (measurable attributes, structured product data, credible third-party evidence), not brand awareness or emotional storytelling. The study introduces the concept of AI recall share as the new competitive metric: how reliably a brand is retrieved when its attributes match a user's query. Brands like Brooks Running outperform Nike in AI recommendations not because of scale, but because their product attributes are precisely named, measurable, and validated by independent experts.
My take: This is a fundamental reframe of brand strategy. The implication is that CMOs must now treat brand architecture as an information architecture problem — requiring cross-functional alignment between marketing, product, and third-party validation. Symbolic positioning alone will not get your brand included in AI-generated consideration sets. The diagnostic is simple: query your category on ChatGPT, Claude, and Gemini today and see where you stand.
Answer Engines Will Select Your Content. Your Digital Experience Has To Do More.
Source: Forrester Blog (https://www.forrester.com/blogs/answer-engines-will-select-your-content-your-digital-experience-has-to-do-more/) | Author: Phyllis Davidson | Published: June 25, 2026
Forrester reports that 69% of digital business strategy decision-makers are already piloting or deploying answer engine optimization (AEO) solutions, as major vendors — Adobe (Brand Visibility + Semrush acquisition), Optimizely (AEO insights platform), and Sitecore (Scrunch acquisition) — race to help brands influence AI-generated answers. Davidson's critical insight is that visibility in AI answers is only the first step: what happens after the answer matters more. When a visitor arrives from an answer engine, they expect continuity with the experience that sent them there — and most organizations lack the connected systems, accessible data, and interoperable workflows to deliver it.
My take: The vendor landscape is moving fast, but enterprise readiness is not. CMOs should resist premature platform switching and instead focus on the foundational work: connecting content, data, and AI strategies into a coherent infrastructure. The organizations that begin building that foundation now will be better positioned to make AI-mediated experiences count — not just show up in them.
Why AI Underperforms in Marketing Operations — And 5 Foundations for Success
Source: MarketingProfs (https://www.marketingprofs.com/articles/2026/55144/ai-adoption-marketing-operations-strategy) | Author: Steffen Drucks | Published: June 2026
Despite 90% of organizations using AI tools, McKinsey data shows only approximately 33% have moved beyond experimentation. This article identifies the five structural shifts marketing operations teams must make: (1) Strategy — define specific business problems AI must solve with measurable KPIs; (2) Processes — standardize and codify workflows before embedding AI; (3) Data — ensure clean, comprehensive, structured inputs; (4) Technology — rationalize the AI tool stack rather than adding to it; (5) People — treat AI adoption as change management, not software deployment. The AI for AI's sake mentality is identified as the primary failure mode.
My take: This is the operational reality check that most AI strategy conversations skip. The organizations stalling on AI ROI are almost always failing on one of these five dimensions — most commonly data quality and undefined success metrics. CMOs should audit their marketing operations against these five foundations before approving any new AI tool investments.
Three Parting Lessons From Forrester's June CX Events
Source: Forrester Blog (https://www.forrester.com/blogs/three-parting-lessons-from-forresters-june-cx-events/) | Author: Rick Parrish | Published: July 1, 2026
Across Forrester's CX events in Amsterdam, New York City, and San Francisco, one message emerged consistently: the organizations that will thrive in the AI era are not those with the best AI — they are the ones that put people first. This reinforces Forrester's 2026 Total Experience Score research, which shows that brands pulling ahead are aligning brand experience, customer experience, and employee experience into a unified system that drives measurable growth. Fragmented experiences — even when individually optimized — break growth momentum.
My take: This is a critical counterweight to the AI hype cycle. The temptation to automate and optimize every customer touchpoint with AI can actually fragment the experience if the underlying human and organizational alignment is not there first. CMOs should evaluate their CX investments through the lens of system coherence, not individual channel performance.
Key Takeaways
Strip it all back and one imperative is left for CMOs. The infrastructure choices you make over the next 12 months will set how visible and relevant your brand is in an AI-mediated market for the decade after that. Twelve months of decisions, ten years of consequences.
AI isn't taking marketing's job. It's changing what you compete on. The brands that come out ahead will have built architectures a machine can actually read and verify. They'll have connected content and data tightly enough that context survives the handoff between AI-mediated touchpoints. And their marketing-ops teams will have the discipline to run AI in production instead of parking it in a pilot.
The ones falling behind are still treating AI as a productivity add-on bolted to the same old workflow, as if nothing underneath has changed. What's changed is how customers find and pick brands in the first place. The room to position yourself early keeps shrinking, and doing nothing gets more expensive by the quarter.
Three immediate actions for CMOs:
Run an AI brand audit. Ask ChatGPT, Claude, and Gemini the questions your buyers would ask about your category, and see whether you show up at all. That gives you a rough AI recall share — and, more useful, it surfaces the specific attributes and evidence gaps keeping you out of the recommendation.
Audit your marketing operations against the five AI foundations — strategy, processes, data, technology, and people — before you sign off on another AI tool. If the foundation isn't there, the tool won't fix it.
Look at your CX architecture as a whole system, not one channel at a time. Whatever's broken in the experience today, AI will amplify. It scales the fragmentation you already have.