AI in the Workplace: What Separates Adopters and Holdouts

The availability of AI in the workplace has increased rapidly, yet many employees still do not use it regularly.

Within organizations that make AI tools available to employees, adoption varies widely by role level. Sixty-seven percent of leaders in these organizations report using AI frequently — a few times a week or more — compared with 52% of managers, 50% of project managers and 46% of individual contributors.

These differences reflect how many mainstream AI tools align with the tasks employees perform. Leadership and management roles are more often desk-based and involve activities such as writing, planning, analysis and communication, for which AI tools can be readily applied.

Role differences alone, however, do not fully explain why some employees use AI frequently while others use it rarely or not at all. Gallup’s February 2026 study of 23,717 U.S. employees finds that managerial support of AI use and intentional consideration of how new tools fit within existing workflows play a critical role in driving employees’ decisions to use AI.

Employees also report several concerns that may discourage them from using AI even when tools are available. Questions about usefulness, ethics and data security, along with established work habits, can influence whether employees experiment with AI and how frequently they incorporate it into their work.

Frequent AI Use Is Closely Linked to Organizational Integration and Support

Employees are more likely to incorporate AI at work when it fits naturally into their workflows and when their organization encourages and supports its use.

The differences are substantial. Within organizations that make AI available to their employees, 88% of those who strongly agree that AI integrates well with the systems and processes they use at work use AI frequently, compared with 55% of those who do not strongly agree. Similar differences in workers’ use of AI are seen according to agreement that their manager actively supports its use (78% of those who strongly agree are frequent users vs. 44% of those who do not strongly agree), that their organization supports experimenting with AI tools (72% vs. 44%) and that their organization has clear AI policies (68% vs. 47%).

The same factors that drive AI use are also tied to individual productivity and more transformational organizational impact. Among employees within organizations that make AI tools available, those who strongly agree that their organization’s AI tools integrate well with their existing systems and processes are:

• 7.2 times as likely to strongly agree that AI has transformed how work gets done in their organization
• 7.4 times as likely to strongly agree that AI gives them more opportunities to do what they do best each day

Similarly, employees who strongly agree that their manager actively supports AI use are:

• 9.3 times as likely to strongly agree that AI has transformed how work gets done in their organization
• 7.8 times as likely to strongly agree that AI gives them more opportunities to do what they do best each day

Skepticism About Utility and Ethical Concerns Limit AI Use

Even when AI tools are available and supported, what barriers remain for employees using AI at work infrequently or not at all?

Some concerns about AI use are common among both employees who use AI infrequently and those who do not use it at all. A preference to keep doing work the way it is currently done is one of the most frequently cited factors by both groups, reported by 46% of non-users and 36% of infrequent users in organizations where AI is available. Concerns about data privacy, security and compliance are also widespread, cited by 43% of non-users and 38% of infrequent users.

What differentiates employees who do not use AI at all from those who use it infrequently are ethics and perceptions of how useful it is. Within organizations that make AI available, 43% of non-users say they are ethically opposed to using AI, compared with 25% of infrequent users. Similarly, 39% of non-users say they do not believe AI can assist with the work they do, compared with 22% of infrequent users.

This suggests that non-users are more likely to question whether AI is relevant or appropriate for their work at a fundamental level, while infrequent users are more likely to see some potential value but still weigh a mix of practical concerns, perceived risks and how well AI fits into their role. This pattern is consistent with indices of occupations' exposure to generative AI: Some occupations are simply less likely than others to be affected by current generative AI use cases.¹

Implications

AI adoption in the workplace depends on more than access to tools. Even when AI is available, employees’ decisions to use it are informed by how they assess its relevance and risks and how well it fits into their workflows.

The findings suggest that concerns about the usefulness and the ethics of AI remain the most significant barriers to initial adoption. Employees who do not see a clear application for AI in their role or who question whether it belongs in their work are unlikely to begin using it. At the same time, a broader set of considerations, including data privacy, security and existing ways of working, can influence how often employees incorporate AI into their work once they have started.

The conditions associated with higher AI use also offer a path to addressing these concerns. When AI is built into existing workflows, supported by managers and reinforced with clear expectations, employees are more likely to use it consistently and to report stronger benefits. These same practices can help organizations clarify where AI adoption in business adds value, reduce uncertainty about its use and build confidence in how risks are managed.

Managers and leaders play a central role in addressing AI adoption challenges. Their influence extends beyond encouraging use to shaping how employees understand AI, trust its use and apply it in their work. Communicating clear use cases, addressing both practical and ethical concerns, and reinforcing how AI fits into daily work may be critical to moving employees from initial hesitation to confident adoption.