When Companies Listen to Employees About AI, Everyone Benefits

According to the Stanford Institute for Human-Centered AI’s 2026 AI Index Report, more than 70% of organizations globally now use generative AI in at least one business function. As adoption continues to grow, AI tools have real potential to save workers time and free them up to focus on more meaningful aspects of their jobs. But depending on how those tools are introduced and governed, they can also reduce productivity, generate low-quality outputs, or harm workers by degrading job quality and security.

The difference between these scenarios often comes down to deliberate choices in how companies deploy new tools.

Today, Partnership on AI is publishing two case studies examining how companies are working to include employee expertise and perspectives to shape how they adopt AI systems. This work reflects a core principle of our Guidelines for AI and Shared Prosperity: that centering worker voice in AI development and implementation is essential to ensuring AI benefits employees and employers alike.

These case studies feature interviews with leaders at IBM and EXL, both participants in the Responsible AI Community of Practice, an initiative that we partnered with Chief Executives for Corporate Purpose (CECP) and Provoc to launch, to integrate employee voices when implementing AI in the workplace. This work builds on our Guidelines for AI and Shared Prosperity and Provoc’s Listen, Act, Be Accountable framework.

For our first case study, we interviewed Jon Lester, vice president of HR Technology, Data & AI, and Jamie VanDodick, director of AI Governance & Responsible Technology. Lester led a series of interviews with employees to understand how workers would want AI used in their jobs.

One finding that emerged from the study is that when leaders signal their openness to feedback, employees likely feel comfortable sharing their insights about AI. IBM’s interviews reinforced that employees want clarity, support, and a chance to shape how AI shows up in their roles. IBM’s approach shows that when leaders invite employees into conversation, provide clear and trustworthy ways to share feedback, and respond in ways people can see and feel, employees will actively contribute to responsible AI adoption. Actively encouraging experimentation also makes employees more likely to innovate with and adopt AI.

Our second case study features EXL, a global data and AI company that helps clients reinvent business models, improve outcomes, and accelerate growth. It employs more than 65,000 people across 50+ global delivery centers. We spoke with Donal McCarthy, Global Solutions and IP Centre of Excellence leader, and Ciara McMenamin, assistant general counsel at EXL.

EXL developed a survey of 5,500 employees to better understand workers’ experiences with the company’s AI governance framework and to build mechanisms for ongoing feedback. A key finding of the study is that when AI governance frameworks are clear and easy to navigate, compliance with those frameworks and employee innovation both improve.

“. . . when AI governance frameworks are clear and easy to navigate, compliance with those frameworks and employee innovation both improve.”

“. . . when AI governance frameworks are clear and easy to navigate, compliance with those frameworks and employee innovation both improve.”

Across both case studies, a consistent theme emerged: companies that devote real resources to responsible AI governance, with dedicated staff, structured listening processes, and accessible frameworks, are better positioned to make AI adoption work for their employees and their organizations.

These case studies show that investing in the people and processes needed for responsible AI governance is a meaningful first step in adopting AI, and a practical path toward the worker-centered implementation that we’ve called for in our work advancing shared prosperity.

We would like to thank our interviewees at IBM and EXL for their time and thoughtful participation, as well as Provoc and Chief Executives for Corporate Purpose for their collaboration and support throughout the cohort and across this series.