64% of Americans Don't Trust AI Assistants: A Permission Problem
A growing number of Americans are hesitant to grant access to their personal data, hindering the adoption of AI assistants in smart homes. According to a recent report by Reviews.org, 63-65% of consumers express concern about major AI assistant platforms like Alexa and Siri. This is not just a minor issue; it’s a fundamental permission gap that tech companies are struggling to bridge.
The problem lies not with the technology itself but with how users perceive its capabilities and their own control over data collection. When 78% of users say they would disconnect a device if it collected more data than expected, and 50% have already deleted or limited their conversation history, it’s clear that trust is a critical issue.
The Wharton Blueprint for AI Agent Adoption identifies three primary frictions: perceived competence, trust, and the delegation of control. Notably, control concerns account for 26% of the total weight in the adoption decision. As Professor Stefano Puntoni notes, ‘What is difficult is the series of uncomfortable decisions that the end user and organizations need to take.’
This friction extends beyond personal use cases to the workplace as well. The IBM 2026 CEO Study highlights a massive gap between AI access and regular usage. While 85% of employees have access to AI tools, only 25% use them regularly. CEOs may believe their workforce is ready for AI assistants, but adoption depends on people, not just technology.
Consumer expectations are also at odds with the current state of AI development. The Prophet 2026 AI-Powered Consumer Report shows that 67% of consumers want AI to anticipate their needs without being asked. However, there has been a decline in the belief that consumers will rely on generative AI for most decisions. People crave convenience but are increasingly unwilling to grant permissions necessary for accurate anticipation.
The industry is attempting to bridge this gap through deeper integration and more user-centric design. For instance, Samsung’s pivot to clinically-integrated agentic health tracking systems connected to over 500 hospitals demonstrates a willingness to adapt to changing consumer expectations. However, the high stakes remain: either companies earn user trust or AI assistants will remain novelties rather than utilities.
The agent business model relies heavily on user trust. If companies prioritize aggressive data harvesting over user-defined boundaries, they risk creating sophisticated yet permanently disabled tools.