Gen AI Consumer Reliance Is Rewiring How Brands Get Chosen

Gen AI consumer reliance has quietly crossed a threshold that most brands have not noticed. New PYMNTS Intelligence data shows this is no longer about whether consumers try generative AI. It is about how completely they have started to depend on it for decisions that used to belong to search engines, review sites, and brands themselves.

Sixty-nine percent of consumers who use gen AI for learning and self-improvement say they use it more now than when they first started. This heavier use extends to other task categories as well, including 66% for writing and communication and 63% for managing banking, finances, travel planning, and health and wellness. Even the lowest-reliance category still shows a majority increasing their dependence over time, according to the same research.

This is the pattern Matt Britton has been tracking across his keynote work with Fortune 500 marketing organizations. Gen AI consumer reliance is not a passing curiosity or a productivity hack confined to knowledge workers. It has become a reinforcing loop, and Matt Britton argues that CMOs who still treat AI as an experimental channel are missing the moment their customers stopped asking questions and started asking AI to decide for them.

The stakes are direct. Today, 146 million people, 56% of U.S. consumers, use an AI model to complete at least one personal task. The share of non-users fell from 48% to 44% between October 2025 and February 2026, while mainstream users rose from 30% to 34%. That is not a spike. It is a steady migration of decision-making authority away from brand-owned channels and toward AI intermediaries that most companies have never audited, optimized for, or even tested.

As the founder of Suzy and a recognized authority on how emerging technology reshapes consumer psychology, Matt Britton has spent the past two years warning executive audiences that adoption curves matter less than dependency curves. This post unpacks the new data on gen AI consumer reliance, what is driving it, and what business leaders must do before their brand becomes an afterthought inside someone else's algorithm.

What Is Gen AI Consumer Reliance?

Gen AI consumer reliance describes the shift from occasional, exploratory use of tools like ChatGPT, Gemini, and Perplexity to habitual, default use for everyday decisions. It is measured not by whether someone has tried generative AI, but by how much more they use it today compared to when they first started. That distinction matters enormously for brands because reliance, not trial, is what determines whether AI sits inside a consumer's daily decision loop.

Stronger results and time savings are encouraging people to return more often, while growing user skills are helping turn occasional AI experiments into regular habits. The pattern suggests a reinforcing cycle. Matt Britton describes this as a flywheel: better tools produce better outputs, better outputs build user confidence, and rising confidence pushes consumers to hand over higher-stakes decisions, from vacation planning to financial choices.

This matters for anyone building a keynote or boardroom presentation around AI strategy. Gen AI consumer reliance is the metric that should replace simple adoption percentages in every strategic deck, because it captures behavioral momentum rather than a single point-in-time snapshot.

The Data Behind AI Habit Formation Among Consumers

AI habit formation among consumers follows a predictable arc, and the newest PYMNTS Consumer AI Benchmark data maps it in granular detail. Consumers are moving beyond occasional generative AI experiments, building the technology into how they learn, write, plan, travel and manage money, but a widening divide exists between occasional users and consumers who now rely on AI for more tasks, harder work and increasingly important decisions.

That widening divide is the real story for brand leaders. A small pullback group shows where the cycle can break, driven by weak value, privacy concerns, or a preference for direct control, but the larger pattern runs toward more frequent use, broader tasks, and greater reliance as capability and competence rise together. In other words, once consumers cross the habit threshold, they rarely retreat.

Privacy remains the one area holding some users back. Privacy and safety showed weaker progress, with only 39% of personal users saying those areas have improved. Matt Britton frequently tells audiences that this is the last real lever brands have. Companies that can demonstrate trustworthy data handling inside AI-mediated experiences have a narrow but real window to differentiate before reliance patterns fully harden.

Financial services and real estate brands face a particularly sharp version of this dynamic. Only 14% of Light Users feel comfortable using AI for financial or banking tasks , which means the brands that build trust early inside AI workflows stand to capture disproportionate loyalty later. Matt Britton's work on AI in financial services and AI adoption in real estate explores exactly this gap between broad usage and high-stakes trust.

Generative AI Adoption in 2026: From Experiment to Compulsion

Generative AI adoption in 2026 has moved past the hype-cycle phase entirely. More than 60% of consumers used a dedicated AI platform in the past year, signaling that AI has crossed into mainstream behavior rather than niche experimentation. That mainstream status is precisely why Matt Britton insists brands stop measuring "if" consumers use AI and start measuring "how much authority" they have handed over to it.

The clearest evidence of that authority shift shows up in search substitution behavior. 42% of consumers who primarily use dedicated AI platforms report using search engines less, compared with 33% among those who mainly encounter AI through search summaries. For brands that built decades of visibility strategy around traditional search rankings, this is the moment the ground shifts beneath them.

Consider a few of the year's fastest-moving indicators:

• Power user reliance is compounding. Power users are deepening reliance far faster than light users, including for complex tasks and important decisions.
• Reinforcement is happening even faster among engaged segments. In just one month, reliance on dedicated AI platforms increased 36% among Gen Z and 28% among Power Users.
• Time savings drive return visits. Generative AI has saved time for 55% of personal users who have increased their use.
• Enterprise access shapes personal habits. Among employees whose organizations provide access to an AI platform, 78% report using that same tool outside of work.

Matt Britton unpacks this compounding effect regularly on The Speed of Culture podcast, where he and guest experts break down how habit formation in AI mirrors early smartphone adoption but is moving at a materially faster pace. Listeners can find the full archive at speedofculture.co.

How AI-Driven Consumer Behavior Is Changing Brand Discovery

AI-driven consumer behavior is fundamentally altering how products get discovered, compared, and chosen, and most brand marketing infrastructure was never built for this reality. Traditional search optimization assumed a human would click through to a website. Generative AI increasingly resolves that intent before a click ever happens.

The scale of that shift is significant. Industry tracking shows AI Overviews and AI-native search products now produce zero-click rates far higher than traditional search, with some AI search sessions ending without a website visit at rates between 60% and 93% depending on the platform. That means the brand mentioned, cited, or recommended inside the AI answer often wins the sale, while brands absent from that answer become functionally invisible regardless of how strong their traditional SEO once was.

Consistency inside AI answers is also far weaker than most executives assume. Research on AI brand mentions shows that only 30% of brands stay visible from one AI answer to the next, and just 20% remain present across five consecutive runs, according to recent AirOps research on AI search behavior. Different AI platforms also disagree with each other constantly. BrightEdge's Generative Parser research found that ChatGPT, Google AI Overviews, and Google AI Mode disagree on brand recommendations roughly six out of ten times for the same query.

Matt Britton frames this as the disappearance of the predictable funnel. Brands can no longer assume that strong organic rankings guarantee visibility inside the tools consumers now trust most. This is the exact gap his AI keynote presentations help leadership teams close, translating fast-moving AI search data into concrete marketing and product decisions.

Inside the Minds of Consumer AI Power Users

Consumer AI power users represent the leading edge of gen AI consumer reliance, and their behavior today predicts mainstream behavior within twelve to eighteen months. PYMNTS defines Power Users as people performing 25 or more AI-driven tasks. For this group, AI functions less like a single-purpose app and more like a general personal operating system used across discovery, planning, learning, and wellness.

This population is not small or fringe. Over one-third of Gen Z consumers and Power Users now go to AI first when starting personal tasks, signaling a move away from traditional browsing and search. Matt Britton has long argued that Gen Z behavior functions as a preview of broader consumer expectations, a thesis he expands on across his Gen Z consumer behavior keynote work and in his book, Generation AI.

Tenure with these tools also matters more than most brands realize. Seventy-five percent of power users have at least a year of experience , and reliance on gen AI for finances rises sharply with tenure, increasing the value of trustworthy data, permission controls, explainable outputs and smooth escalation to a human. Brands that ignore this maturing user base risk losing the exact customers who spend the most and decide the fastest.

Matt Britton's own platform, Suzy, was built to help brands understand these fast-shifting consumer segments in real time, using live data rather than lagging annual studies. That kind of speed is now a requirement, not a nice-to-have, given how quickly power user behavior is reshaping category norms.

Key Takeaways for Business Leaders

• Audit where and how your brand appears inside AI-generated answers across ChatGPT, Gemini, Perplexity, and AI Overviews, not just traditional search rankings.
• Prioritize trust signals such as transparent data practices and explainable outputs, since privacy remains the clearest weak point slowing deeper AI reliance.
• Track power user behavior as a leading indicator, since their habits today forecast mainstream consumer expectations within a year.
• Invest in generative engine optimization strategies designed for zero-click discovery rather than legacy click-through funnels.
• Educate leadership teams on the difference between adoption metrics and reliance metrics before budget cycles lock in outdated assumptions.

Frequently Asked Questions

What does gen AI consumer reliance actually mean?

Gen AI consumer reliance refers to the growing dependence consumers place on generative AI tools for everyday decisions, from financial planning to travel booking. Rather than measuring simple adoption, it tracks how much more frequently and heavily people use AI compared to when they first started, revealing a compounding behavioral shift rather than a one-time trial.

How fast is generative AI adoption growing in 2026?

Generative AI adoption has moved firmly into mainstream territory in 2026. 146 million people, 56% of U.S. consumers, now use an AI model to complete at least one personal task , with non-user populations shrinking steadily each month as more consumers move into mainstream and power-user categories.

Why should brands care about AI power users specifically?

Power users, defined as consumers performing 25 or more AI-driven tasks, represent the fastest-growing and most influential segment shaping AI-driven consumer behavior. Their reliance patterns today, including using AI as a default starting point for shopping, planning, and research, typically predict mainstream consumer expectations within twelve to eighteen months.

What can CMOs do to stay visible as AI reliance grows?

CMOs should treat AI visibility as a distinct discipline from traditional SEO, auditing brand mentions across multiple AI platforms since research shows major platforms often disagree on recommendations for identical queries. Building trust signals, fresh authoritative content, and clear data practices increases the likelihood of consistent AI citation and recommendation.

Turning Gen AI Consumer Reliance Into a Business Advantage

Gen AI consumer reliance is not a future trend to prepare for. It is a present reality already reshaping how consumers discover, evaluate, and choose brands. Matt Britton's research and keynote work exist to help business leaders act on this data now, before dependency patterns fully calcify around competitors who moved first.

The brands winning inside this new decision loop are not necessarily the ones with the biggest budgets. They are the ones treating AI visibility with the same discipline once reserved for search rankings and shelf placement. Matt Britton brings this data-driven, forward-looking perspective to every stage, helping executive teams translate consumer AI research into concrete strategy.

Organizations ready to understand how gen AI consumer reliance affects their category, customers, and competitive position can explore Matt Britton's speaker platform to book a keynote built around the freshest available data. The window to shape these habits is narrowing every quarter.