As we strategize for integrating agentic AI into our workflows, it’s important to remember that the goal is to not only drive elevated productivity and performance, but to do so in a way that empowers employees. Deploying AI agents to support employees reach new heights can create positive and sustainable change – enabling a new employee experience. And AI adoption thrives in people-centric environments, as our research shows that high frequency AI users are 1.9x as likely to agree that their organization has people-centric AI practices compared to low frequency AI users.
Chapter 2 of our 2025 Agentic Teaming & Trust Research Report dives into the accelerating value of putting employees at the center of your agentic AI transformation. In this chapter, we explore the positive impact that people-centric transformation has not only on AI adoption, but also AI value and employee experience sentiment.
We found an average 38 percentage-point gap between low and high frequency AI users on the presence of people-centric practices at their organization, such as receiving adequate training in AI, having resources for AI upskilling, and receiving recognition for AI adoption. Rather than treating AI technology as a “flip-the-switch” implementation, these organizations are investing in change management principles and it’s fueling the flywheel of increased adoption and further learning and growth.
We’re also seeing this play out in organizations where there is strong leadership presence in AI transformation. When leaders are explicitly involved in the transformation and openly sharing their experience, it can have a positive impact on the rest of the organization. We found significantly higher agentic AI value perception for employees who reported leadership role modeling effective AI use than employees who reported not having this role modeling.
When leaders actively use AI, it helps employees better understand practical use cases – especially important since 1 in 2 employees report facing moderate to extreme challenges with everyday tasks that shape their work experience. Whether it’s finding the right information, setting goals, sharing feedback, or collaborating with others, these basic activities are unexpectedly difficult. If we are strategic in the way we build and integrate agents, we can ideally reduce this friction for employees, which should free them up to work more efficiently and effectively.
Building the human-AI flywheel can drive sustained change and empowerment. By involving employees in the transformation, they feel involved, considered, and supported, which can increase adoption and impact. Tangible improvements to everyday employee experience can be a game-changer for your employees. As we move forward with AI agent integration, the opportunity is clear: agentic AI can be a catalyst for a more empowered, connected, and resilient workforce.
Want to explore the full story?
Download the PDF - Chapter 2: The Multiplier Effect
Catch up on previous chapters from this report:
Download the PDF - Chapter 1: Ready for Agents
The Agentic Teaming & Trust Study was conducted by the Microsoft People Science team utilizing an Online Panel Vendor, commissioned by Microsoft, with 1,800 full-time employees across nine markets between June 11, 2025 and July 7, 2025. This survey was 12 minutes in length and conducted online. Global results have been aggregated across all responses to provide a total or average. Each sample was representative of business leaders across regions, ages, and industries (i.e., Construction, Financial & Professional Services, Retail, Food, & Beverage, Healthcare, Media & Entertainment, Technology, Transportation, Travel, & Hospitality). Each sample included specific parameters on company size (i.e., organizations with 1,000+ employees) and job level (i.e., business leaders/business decision makers, those in mid- to upper job levels such as C-level executive, VP or director, Manager). The overall sampling error rate is 2.31 percent at the 95 percent level of confidence. Markets surveyed include Brazil, China, France, Germany, India, Japan, Mexico, United Kingdom, and the United States. Findings represent aggregated responses and may not reflect all organizations or industries.
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