Agentic AI adoption is not being held back by employee resistance, according to a survey of 281 The Information readers, challenging a common narrative in tech circles. Only 14% identified workforce resistance as a primary barrier, placing it at the bottom of the list of challenges. Instead, organizations are grappling with technical limitations, data security concerns, and difficulty identifying clear, high-value use cases. Despite the low level of resistance, the survey highlights significant hurdles in preparing workforces for AI integration. Employees face challenges related to the rapid pace of change, limited time for training, and a lack of accessible upskilling resources. While many workers are open to AI tools—especially those they’ve used personally like ChatGPT—frustration arises when companies roll out poorly designed pilots without proper context or training. As Jake Burns, AWS executive in residence, notes, treating AI as an “easy button” leads to disappointment and reinforces skepticism. Real value comes from deliberate investment in training and thoughtful implementation. The top barriers to adoption are data privacy and security concerns, followed by the lack of mature, validated agentic AI products and difficulty proving return on investment. Many respondents cited reliability issues, including hallucinations and inconsistent performance beyond proof-of-concept stages. However, the majority still believe AI agents will boost operational efficiency, reduce costs, and drive innovation. Half or more expect benefits like improved decision-making and new capabilities that were previously unattainable. In terms of use cases, task and workflow automation lead the list, followed by data analysis and insight generation—areas Burns calls a “no-brainer” for AI. Other promising applications include customer service, employee productivity, content creation, and software development. Data analysis, in particular, stands out as a powerful use of AI’s ability to process vast datasets in real time. Organizations are responding by launching pilot programs, identifying internal AI champions, and involving employees in implementation. Burns emphasizes the importance of creating enterprise-grade AI sandboxes to empower curious, experimental employees—what he calls “rebels and outside-the-box thinkers”—to discover value. These individuals often emerge when organizations provide access and encouragement, not top-down mandates. While concerns about job displacement and cultural resistance are present, they remain low on the list. More pressing are technical and organizational challenges: ensuring accuracy, maintaining security, and preventing overreliance on AI decisions. A third of respondents also worry about the erosion of human expertise due to overuse of AI. The survey underscores a critical insight: the real bottleneck isn’t people—it’s the maturity of the technology and the readiness of organizations to adopt it effectively. Success depends not on overcoming fear of AI, but on building the right infrastructure, training, and governance. The organizations that thrive will be those that treat AI as a strategic partner, not a shortcut, and invest in both the tools and the people who use them.