AI is already deciding what’s next.
Not later or hypothetically. Right now. People ask AI tools to reduce options and compare trade-offs before they visit a site or talk to sales. By the time a human shows up, the list is shorter and the alternatives are already set. You’re no longer competing against the full market. You’re competing against what the system decided was worth showing.
That shift is easy to miss because nothing visibly breaks. There’s no new channel to manage or platform demanding budget. Decisions move upstream, outside the systems marketers rely on to understand demand.
A CRO won’t see it in the pipeline. A marketer won’t see it in analytics. Everything looks stable on the surface, until it isn’t. Familiar tactics lose efficiency. Attribution gets murkier. The change shows up gradually, without a clean line back to cause.
The IBM Institute for Business Value set out to measure this shift and found that consumers are already further along than most marketers realize.
What the IBM Consumer Research Study Examined and Why It Matters
The 2026 Consumer Research Study from the IBM Institute for Business Value surveyed more than 18,000 consumers across 23 countries, alongside 200 retail and consumer products executives. The research looked at how people are using AI today and how much decision-making they are willing to hand over next.
The headline number is straightforward: consumer use of AI applications such as ChatGPT and similar tools has grown 62% over the past two years. Adoption is even higher among Gen X and Baby Boomers, groups often assumed to be late to new technology.
More telling than usage is intent. Consumers increasingly want AI to move beyond answering questions. They want it to act: monitor prices, compare options, apply preferences and complete tasks with minimal oversight.
The study describes this shift as “agentic commerce.” In practical terms, it means AI tools that do not just inform decisions but execute them within boundaries a user sets.
That matters because the behavior isn’t limited to shopping carts. The same pattern shows up when a finance leader asks an AI tool to summarize vendors. When a marketer uses it to shortlist platforms. When a traveler lets it assemble an itinerary instead of browsing destinations.
Retail is simply where the behavior is easiest to measure.
The broader signal is this: people are getting comfortable delegating judgment to systems they trust. Once that happens, influence shifts away from touchpoints marketers control and toward inputs AI systems rely on.
Three Metrics That Show How Far This Shift Has Already Gone
The IBM study includes dozens of data points, but these three stand out. They don’t describe experimentation, they describe behavior that is already reshaping how decisions happen.
AI Adoption Is Broad, Not Experimental
As stated above, consumer use of AI applications has grown 62% over the past two years. Among Gen X, growth reaches 82%. Among Baby Boomers, it climbs to 92%.
For years, new technology followed a familiar pattern, younger users experimented first, everyone else followed later. AI is breaking that pattern. Adoption now spans age groups that control budgets, influence teams and make final decisions. It’s becoming part of how people think through choices, not a novelty layered on top of existing habits.
AI Is Shaping Evaluation Before Brands Enter the Picture
AI is already embedded in the evaluation phase:
- 41% of consumers use AI to research products
- 33% use it to review feedback
- 31% rely on it to find deals and promotions.
These are the moments when options get filtered and preferences take shape. By the time a brand shows up, AI has often completed the first round of decision-making.
Consumers Are Ready to Let AI Act for Them
When the study asked participants to rank the most desirable AI agents, consumers consistently prioritized systems that do more than recommend. Their top choices were deal-monitoring agents, always-on customer service agents, product review agents and personal shopper agents, all designed to act on a user’s behalf rather than wait for confirmation.
The appeal is efficiency. Set the goal once, then step out of the process. That preference for action over advice marks the shift from AI as an advisor to AI as an operator.
In financial markets, automated trading has followed this model for years: investors set risk and return constraints upfront and systems monitor conditions and execute trades without human intervention.
What’s different now is the scope. This model is no longer confined to specialists or institutional systems. Consumers are asking for the same delegation in everyday decisions, shopping, service and travel; areas they once managed themselves.
Together, these metrics describe a clear progression. AI is widely adopted. It already influences evaluation. And consumers are prepared to let it act. For marketers, the implication is simple: influence is moving upstream, into systems that decide what even gets considered in the first place.
“AI is turning shopping into a trusted conversation, much more than a search. Consumers now rely on assistants that feel almost human, know their preferences, and offer neutral, best-for-me advice that reshapes how they validate and decide what to buy.” Matthieu Houle CIO, ALDO Group
How Marketers Should Interpret This Data
The data doesn’t call for a new playbook so much as a reframing of what marketing is responsible for influencing in the first place, one that benefits from a curiosity-led approach to AI as systems take on more evaluative roles.
- AI is not a new channel. The shift is where influence happens. Decisions are forming earlier than most marketing systems are built to observe or measure.
- Marketing is moving from persuasion to qualification. The job is no longer only to convince people, but to supply clear, credible inputs to systems that summarize, rank and filter options before a human engages.
- Visibility now depends on legibility. Messaging that performs well on owned channels may never surface if it doesn’t appear in the sources AI tools rely on to evaluate trust and relevance.
- Brand trust is inferred, not announced. It’s built through consistency, clarity and verifiable signals across the web, not just through campaigns or positioning statements.
- The first decision often happens without a touchpoint. By the time a person enters the process, options may already be narrowed by an automated system applying constraints and preferences.
- The real risk is exclusion. If AI systems don’t understand you, trust you, or surface you, you’re not competing for attention or conversion. You’re absent from consideration entirely.
Once you accept that shift, the next question isn’t whether this matters; it’s what to change now so your brand stays visible where decisions are actually being made.
What to Do Next
This isn’t about doing more. It’s about focusing on the few things that determine whether you’re even considered in an AI-mediated decision.
Priority 1: Make Your Brand Legible to AI Systems
Start by understanding how your brand appears outside your owned channels. AI tools rely on third-party inputs: reviews, analyst coverage, partner sites, marketplaces, structured data and public references.
If your positioning is inconsistent, outdated, or fragmented across those surfaces, AI systems struggle to classify you correctly. That confusion often results in exclusion, not misrepresentation.
Priority 2: Replace Claims With Verifiable Signals
AI systems favor evidence over messaging. Vague differentiation, soft assurances and buried proof points don’t travel well when decisions are summarized or automated.
Clear pricing logic, explicit capabilities, documented trust signals and consistent product facts matter more than polished language. If a claim can’t be confirmed elsewhere, it’s likely to be discounted.
Priority 3: Design Marketing for Humans and Machines at the Same Time
People still respond to narrative, context and relevance. Machines respond to structure, consistency and clarity. Modern marketing has to work for both.
That means aligning content and data so systems can interpret you correctly and people can quickly understand why you matter. When those two audiences fall out of sync, machines increasingly determine which messages humans ever see.
This is where many teams fall behind, not because they lack creativity, but because their foundations aren’t built for automated evaluation.
The New Front Door to Decision-Making
AI isn’t replacing marketers. The IBM study shows it’s changing where influence happens and how early decisions take shape.
As consumers use AI to evaluate options and delegate action, marketing becomes less about winning the click and more about being included in the systems that narrow choices in the first place. The brands that succeed will be the ones AI can understand, trust and surface before a human ever enters the process.
If you want help understanding how your brand shows up in AI-driven evaluation and what to change to stay visible, let’s talk.
