Power Users Show Businesses How Agentic AI Goes Mainstream

In theory, the appeal of autonomous AI agents is obvious. An AI agent that monitors your finances, shops for better insurance rates, refills household essentials, manages subscriptions, or books travel based on your preferences promises a future of reduced friction and reclaimed time.

In practice, findings in the January 2026 edition of the “Agentic AI Report” from PYMNTS Intelligence reveal that consumer enthusiasm for this future is divided. Some users are eager to hand over the reins. Others remain deeply cautious, even resistant.

The report found that this divergence reflects a more fundamental truth about autonomy, trust and control, one that may have major implications for businesses racing to deploy agentic AI.

Rise of the Power User

Every technological shift has its early adopters, and agentic AI is no exception. Power users, consumers who already integrate AI tools deeply into their work and personal lives, are the most enthusiastic about autonomous systems, per the report. They are comfortable with complexity, familiar with AI’s limitations, and accustomed to experimenting with new interfaces. For them, agentic AI feels like a natural extension of existing behavior.

From a business perspective, power users are invaluable. They provide early demand, real-world feedback, and proof points that agentic systems can work. But they are also misleading if treated as a proxy for the broader market. Designing exclusively for this cohort can create products that feel intimidating, opaque or reckless to everyone else.

Because for a much larger segment of consumers, the idea of autonomous AI provokes anxiety rather than excitement. These users may be comfortable with AI suggesting what to buy or helping draft an email, but they draw a firm line at delegation. Letting a system act independently, especially in financial or personal contexts, can feel like a loss of agency.

Consumer attitudes toward agentic AI may be best understood not as a binary divide, but as a spectrum shaped by circumstance. Tasks that are repetitive, low-cost, and easily reversible attract the highest tolerance for autonomy. Tasks involving long-term consequences or significant financial exposure do not.

The same individual who allows an AI to reorder household supplies without hesitation can also refuse to let it manage investments or insurance decisions.

Read the report: From Assistive to Agentic AI: Consumers Wade Into Autonomous Commerce 

Gradual Transition, Not Sudden Leap

The temptation for companies is to build toward the most advanced vision of agentic AI and assume consumers will catch up. History offers a more cautionary lesson. Technologies that achieve mass adoption typically allow for gradual engagement, not forced transformation.

In the context of agentic AI, this can mean designing tiered experiences. Assistive modes allow users to receive recommendations and insights without relinquishing control. Semi-autonomous modes enable AI to execute actions with confirmation or predefined limits. Fully autonomous modes empower AI to act independently within agreed-upon parameters.

These layers must be intelligible. Consumers need to understand what the system can do, what it will not do, and under what conditions it acts. Autonomy that feels hidden or automatic erodes confidence; autonomy that is explicit and adjustable can earn it.

The companies best positioned for the agentic AI transition may not be those moving fastest, but those embedding autonomy within systems consumers already regard as legitimate and accountable.

The uneven readiness for agentic AI creates a strategic challenge. Companies must innovate without outpacing their customers, which requires a deep understanding of segmentation that is not just demographic, but behavioral and psychological.

Autonomy is deeply personal, shaped by experience, risk tolerance and values. The companies that may succeed in this next phase of AI are likely to be those that respect this diversity rather than trying to erase it.