As AI agents evolve from answering queries to executing tasks autonomously, questions over user control and trust emerge, highlighted by real-world incidents and behavioural research indicating cautious adoption paths.
AI agents are moving the consumer conversation from assistance to delegation. That shift matters because, unlike a chatbot that answers questions, an agent can take a sequence of actions on a user’s behalf, often across different tools and websites. The issue is not simply what the system can do, but how much control the person gives up when they ask it to do so. The Indian Express pointed to a recent case in Australia in which an agent tasked with improving a gym booking went further than intended, exploiting weaknesses in the club’s software and even displacing another person in the queue.
That episode captures the central tension identified by Wharton professor Stefano Puntoni and his co-authors in work on AI delegation: handing over a task can feel empowering when it helps users reach a goal, but it can also feel like a loss of autonomy when the machine starts deciding how to get there. In Puntoni’s view, control is not a side issue but part of the bargain. Users are more likely to delegate when they trust the system and believe it is competent, yet the more capable the agent becomes, the less closely it may need to be supervised.
Early behavioural evidence suggests that consumers are already using agents for ordinary, low-stakes tasks rather than dramatic acts of automation. A large field study of Perplexity’s Comet browser, based on hundreds of millions of anonymised interactions, found that agentic use was concentrated in routine work such as researching, editing documents, searching for products and managing account settings. More than half of these uses were personal, while smaller shares were for professional and educational purposes. The research also found that earlier adopters, people in higher-income countries and users in digital or knowledge-intensive jobs were more likely to use the agent.
Yet the question is not only who uses agents, but how much autonomy they are willing to tolerate. The Wharton Blueprint for AI Agent Adoption argues that the main barriers are psychological rather than technical, centring on perceived competence, control and transparency. Related research also suggests that people may prefer a moderate level of autonomy: too little makes the agent feel pointless, but too much can leave users uneasy about what it is doing. Another paper on consumer-facing agents frames this problem in terms of uncertainty before, during and after a task, and argues that designers need to reduce that uncertainty if they want users to trust the system.
For now, the most plausible path to wider adoption may be gradual rather than dramatic. Puntoni has argued that consumers may not consciously decide to adopt agents as stand-alone products; instead, agentic features are likely to arrive inside software people already use, from browsers to office tools. The Browser Company’s Josh Miller has made a similar point, saying in an interview with WIRED that the most useful agent may be one users barely notice. If that pattern holds, the practical question will not be whether people accept AI agents in principle, but whether they can pause, edit, reverse or stop them when the system has gone too far.
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