AI can be used as either offense or defense, but one approach gets the best results. Martech Futurist | June 9, 2026
A split runs through this week's research, and it's the uncomfortable kind for CMOs. Companies are pointing AI in two opposite directions. One group uses it to defend what they already do: trimming costs, automating the busywork. The other points it at growth: new revenue channels, a customer experience built to win people the old funnel never reached. The studies below don't treat those as equal bets, and they're fairly blunt about which one pays off.
Of everything in this batch, the HBR piece on AI and growth is the one I'd read first. It goes after the standard CMO reflex — point AI at cost-cutting and workflow cleanup — and counters with field-tested evidence that the same technology, aimed at organic growth, can multiply a firm's value by 2x or more. Which flips the question. Instead of "how do we automate the campaigns we already run," it becomes "how do we use AI to reach and convert customers we couldn't before." CMOs still pitching AI internally as a productivity play are leaving the biggest money on the table.
Forrester's state-of-agentic-AI report sits on the gap between claiming and doing. 75% of enterprises say they're adopting agentic AI. Hardly any have pushed it past a narrow pilot. For marketing teams that's a window — open now, closing fast. Tool count isn't what separates the leaders. They got ahead by rebuilding workflows and governance around systems that act on their own, then reorganizing teams to match. Bolt an agent onto a legacy campaign process and you'll get a marginally better legacy campaign process. Not a transformation.
MarketingProfs' breakdown of the "martini pipeline" is where the customer-journey story gets urgent. Two numbers carry it. 94% of B2B buyers now lean on generative AI somewhere in the buying process, and 95% of deals go to a vendor that was already on the buyer's day-one shortlist. Put those together and the traditional demand-gen funnel is basically obsolete. So the spend has to move. Pull it out of top-of-funnel awareness and into being visible inside the LLM answers themselves, plus a brand story consistent enough that the model repeats it the same way every time. Structured, verifiable proof helps too. And the catch is that buyers are building these shortlists in private AI sessions your analytics will never see.
The second HBR study, on consumer advertising, lands somewhere more practical. Let people control their own ad experience — what they see, or when they see it — and the numbers move your way. Attention goes up 9–15%, depending on the format. Annoyance drops 8–17%. And recall and purchase intent both improve. Calling that a UX tweak undersells it. What's really being renegotiated is the deal between advertiser and viewer — and streaming platforms and digital marketers should be working on it now, before ad fatigue eats further into engagement and starts driving people to cancel.
Four calls to make before the quarter's out:
Rebalance the AI roadmap toward growth. Go through it line by line and work out what share actually targets new revenue versus cost reduction. If it's mostly the latter, that's your finding.
Pressure-test your agentic readiness — and not just which tools you've bought. Look at governance, orchestration, and whether the workflows have genuinely been rebuilt.
Run an LLM brand audit. Check how you show up in AI-driven buyer research now, while competitors are still working out that it matters.
Rework the ad experience around giving people some control, instead of holding them captive through the break.
Featured Insights
Companies Are Using AI for Efficiency. They Should Use It to Grow.
Source: Harvard Business Review | Authors: Shlomo Benartzi, Randall Long, and Stefano Puntoni
Link: https://hbr.org/2026/06/companies-are-using-ai-for-efficiency-they-should-use-it-to-grow
Commentary: This is the most strategically important article for CMOs this week. Drawing on real-world marketing experiments — including AI-generated LinkedIn ad campaigns that delivered 3.2x actual lift in click-through rates — the authors demonstrate that AI deployed for organic growth can increase firm value by 50–135%, compared to roughly 10% from cost-cutting alone. The 'growth blindspot' they identify is real and pervasive: most marketing AI investments are still oriented toward efficiency, not expansion. CMOs need to reframe their AI roadmaps around revenue growth, not just operational savings, and build the evidence base to justify higher valuation multiples with investors.
The State Of Agentic AI In 2026: Companies Are Chasing, Few Are Catching
Source: Forrester | Author: Brian Hopkins
Commentary: Forrester's new report on agentic AI is a reality check for every enterprise that has announced an 'AI-first' strategy. Three-quarters of enterprise leaders claim to be adopting agentic AI, but almost none have scaled it beyond narrow pilots — and the reasons are structural, not technological: ROI uncertainty, governance gaps, platform confusion, and the 'trust tax' of logging and auditing every autonomous action. For marketing organizations, the practical implication is clear: agentic AI bolted onto legacy workflows produces task savings, not transformation. The companies pulling ahead are redesigning roles, approvals, and workflows around autonomy — and treating every agent as a governed identity with credentials, logging, and a named owner.
Three Things to Fix Now That the Enterprise B2B Funnel Is a Martini Pipeline
Source: MarketingProfs | Author: Shira Abel
Link: https://www.marketingprofs.com/articles/2026/54954/ai-buying-journey-llm-brand-audit
Commentary: With 94% of B2B buyers now using generative AI during the purchase process and 95% of deals won by vendors on the buyer's day-one shortlist, the traditional B2B funnel has structurally collapsed. This article provides a concrete, actionable framework for CMOs: conduct an LLM brand audit (test 10–20 buyer prompts across ChatGPT, Claude, Perplexity, and Gemini), ensure narrative consistency across all buyer-facing surfaces, and restructure customer proof for algorithmic extraction rather than human persuasion. The shift from 'awareness and consideration' to 'shortlist confirmation' is not a trend — it is the new reality of B2B buying, and most marketing organizations are not yet structured to compete in it.
Research: When Consumers Have More Control Over Ads, They Respond Better
Source: Harvard Business Review | Authors: Siddharth Bhattacharya, Debashish Ghose, and Gordon Burtch
Link: https://hbr.org/2026/06/research-when-consumers-have-more-control-over-ads-they-respond-better
Commentary: Across three studies with 1,300+ participants, this research finds that giving consumers control over either ad content or ad timing produces 9–15% more visual attention and 8–17% less annoyance — with downstream improvements in recall, brand impressions, and purchase intent. The strategic insight for CMOs is that consumer agency is not a concession to viewer preferences; it is a performance lever. With 37% of U.S. consumers having canceled a streaming subscription specifically because of ads, the captive-audience model is not just annoying — it is destroying subscriber value. Platforms and brands that deploy 'choice menus' strategically — matching the form of control to the viewer's context and commitment level — can simultaneously improve engagement, retention, and advertising ROI.
Emerging Themes
Theme 1: The AI Growth Imperative vs. the Efficiency Trap. Multiple sources this week converge on the same warning: organizations that use AI primarily for cost reduction and operational efficiency are systematically undervaluing the technology. HBR's research shows that AI-driven organic growth can multiply firm value by 2x+, while efficiency gains top out at roughly 10%. CMOs who have built their AI business cases around headcount reduction and workflow automation need to urgently reframe their investment thesis around revenue expansion.
Theme 2: Agentic AI Is Real, But Enterprise Readiness Is Not. Forrester's data makes clear that the gap between agentic AI ambition and agentic AI execution is wide and growing. The constraint is not technology — long-running agents that operate for days or months are already in production at leading firms. The constraint is governance, orchestration, and organizational readiness. Marketing operations leaders who are planning agentic AI deployments need to invest in the control plane (identity, logging, workflow redesign) before adding more agents.
Theme 3: The B2B Buyer Journey Has Already Changed. The MarketingProfs analysis, supported by Forrester's buyer research, confirms that the traditional B2B funnel is obsolete. Buyers are forming shortlists in private AI sessions before they ever engage with marketing. The implication for CMOs is that LLM visibility, narrative consistency, and structured proof are now core marketing infrastructure — not nice-to-have optimizations.
Theme 4: Consumer Agency as a Performance Strategy. The HBR advertising research adds a consumer-side dimension to the AI and personalization conversation: giving consumers control over their experience — whether in advertising, content, or service interactions — produces measurably better outcomes for all parties. This principle extends well beyond streaming ads to the broader question of how brands design AI-driven customer experiences.
Summary
The intelligence from this week's sources points to a pivotal inflection point for marketing leadership. The organizations that will define competitive advantage over the next 18–24 months are those that make three strategic shifts simultaneously: from AI-for-efficiency to AI-for-growth; from agentic AI pilots to governed, scaled agentic systems; and from traditional demand generation to LLM-native buyer journey strategies.
The window for these shifts is not indefinitely open. Forrester's data shows that the companies pulling ahead in agentic AI are already redesigning workflows and governance structures — not just deploying tools. The MarketingProfs analysis shows that buyers are already forming shortlists in AI sessions that most marketing organizations cannot see or influence. And HBR's growth research shows that the valuation premium for AI-driven organic growth is already being priced into markets.
CMOs who treat these as future considerations rather than present imperatives risk being structurally disadvantaged by the time the window closes. The most urgent action item: audit your current AI investment portfolio against the growth vs. efficiency framework, and redirect at least a meaningful portion of AI spend toward revenue expansion initiatives with measurable organic growth impact.