In my last blog, Preparing Your Workforce for AI Takes More Than Technical Skills, I discussed the importance of developing the human skills employees need to succeed alongside AI. But preparing employees is only part of the equation. How leaders introduce and position AI can be just as important to its success.

As organizations continue to adopt AI, much of the conversation centers on efficiency, automation, and getting more done in less time. While these are valuable benefits, research from the Stanford Institute for Human-Centered Artificial Intelligence suggests that focusing too heavily on productivity may actually discourage employees from embracing the technology. Instead, leaders should emphasize how AI can help employees grow, develop new skills, and focus on more meaningful work.

When a manager announces a new AI tool that can cut work time in half, leadership may see greater efficiency, but employees may hear something different: “Is my job at risk? Will my skills still matter?”

Recent research highlighted by the Stanford Institute for Human-Centered Artificial Intelligence suggests that the way managers introduce AI may be just as important as the technology itself. Employees are more likely to engage with AI when it is presented as a way to make their jobs more meaningful rather than simply a tool to increase productivity.

Stanford research examined two divisions of a law firm that introduced the same AI tool to paralegals but took different approaches. One manager focused on efficiency and faster turnaround times, while the other emphasized reducing tedious tasks to make room for more meaningful work.

Employees in the second division used AI 58% more and experimented with it 70% more. Rather than focusing on doing more with less, positioning AI as a way for employees to develop new skills, solve complex problems, and contribute in more meaningful ways is more likely to gain a positive response.

Rethinking How We Measure Employee Performance

One of the most important points in the Stanford research is something I believe deserves more attention from HR professionals and business leaders. If AI changes how employees work, we also need to change how we measure their performance.

For years, many organizations have relied on traditional productivity metrics such as the number of tasks completed, cases handled, reports generated, or hours spent on particular activities.

We need to move beyond simply measuring how much work gets done and place greater emphasis on the quality, impact, and value of that work.

That might mean evaluating employees on their ability to solve problems, improve processes, contribute new ideas, strengthen customer relationships, or make more informed decisions.