AI adoption in the workplace succeeds when leaders treat it as a change-management effort rather than a software rollout: HR and IT share ownership, employees get safe room to experiment, and trust sets the pace. That was the shared view of two CIOs and two HR leaders who joined PeopleReign CEO Dan Turchin on September 17, 2026, for a Lessons From Leaders panel.

The panel, “When Intelligence Is Everywhere, Intelligence Is Nowhere,” asked what creates competitive advantage when everyone has access to the same AI. The answers were about people, not tools, and they add up to five lessons.

The five lessons at a glance

  1. Share ownership of AI adoption between HR and IT.
  2. Make experimentation safe for employees.
  3. Run two tracks: top-down goals and bottom-up ideas.
  4. Govern across functions and tie decisions to company values.
  5. Start where friction is high and measure the impact.

Watch the full recording: https://youtu.be/22QBr6Wmclc

The panelists

What does AI adoption in the workplace actually require?

AI adoption in the workplace requires changing how people work, not only deploying tools. The panelists named four ingredients: involving employees early, training them, having leaders model their own use, and setting clear norms for where experimenting is safe. Julie Rodda said success is usually not technical: “It’s organizational, it’s behavioral, it’s a people change.”

The data shows the gap. Gallup’s workplace AI tracker (data as of May 2026) found that 52% of U.S. employees use AI at work at least a few times a year, but only 15% use it daily, and 47% say their organization has integrated AI tools. At organizations that have, employees who strongly agree their manager supports their team’s AI use are 1.7 times as likely to use AI a few times a week or more.

Lewis Choi framed the work with the diffusion of innovation curve: win the innovators (about 2.5% of people), show value to reach the early adopters (about 16%), and let the early majority follow. “Every morning I wake up, I’m two years behind,” he said, which is why he benchmarks constantly.

What does change management for AI adoption look like in practice?

AI change management is the practice of preparing, equipping and bringing employees along as AI changes how work gets done. The two HR leaders on the panel started from different places: iRhythm built a structured enablement program, while Ibotta gave licenses to everyone and relied on company values.

At iRhythm, a multi-year plan builds from AI basics to advanced skills, the CEO shared his own AI practices at a town hall, and self-identified experts are paired with less proficient colleagues. Rodda admitted the company over-indexed on policy early on, which made people afraid to try the tools, so it re-clarified where experimenting is safe. Ibotta anchored its rollout in the company value that a good idea can come from anywhere, and is now looking for best practices to scale.

The panel agreed that two tracks must run in parallel. Leaders set goals for high-friction, cross-functional processes, while smaller use cases bubble up from the people closest to the work. Choi called the right model a hamburger and warned that bottom-up ideas rarely scale across functions without incentives from leadership. Stuart Kippelman was blunt about the alternative: “this will never work with AI if it is top down.” He added that unglamorous projects deliver, citing a 40% increase in cash collection from predictive analytics and AI.

Who should own AI adoption: the CHRO, the CIO or both?

Both, with different jobs. On the panel, the HR leaders described owning AI enablement, training and workflow redesign, while the CIOs owned technology choices and business value. Gartner predicts that 30% of organizations will have blended HR-IT teams for AI enablement by 2029.

Rodda said “this is HR’s time to shine.” When her role was elevated this year, she chose the title chief people and capability officer to reflect work done by human and digital talent together, and she is adding an org design role to partner with business leaders on enterprise AI implementations. Choi built a Technology Enablement and Adoption organization at Neurocrine for the same purpose. Kippelman rejects the idea that IT only aligns with the business: “I am part of the business and driving revenue.”

How do you earn employee trust in AI?

Employees trust AI when it is deployed responsibly and visibly. Responsible AI is deploying AI in ways that avoid harm to employees, customers and society and that can be tied to business value. The panel offered two simple tests: would this look bad if it made the news, and what business problem does it solve?

The trust gap is real. Workday’s August 2026 AI@Work survey found that half of respondents hid their AI use at least once in the past month, and 37% said their manager had not discussed AI’s effect on their role in the past three months.

Choi’s company built a responsible AI council. It offers employees enterprise versions of general-purpose AI assistants but has not turned on connectors to SharePoint, because AI makes poorly governed files easy to find. “Responsibility and value go hand in hand,” he said. Rodda said patients, employees, risk and the board each bring a lens at iRhythm, and company values, lead with integrity and solve for the patient, guide which tools it adopts. Daspit said it would be irresponsible to build AI savings into a financial plan before the impact is understood. Turchin tied it together: “innovation can never move faster than the speed of trust.”

What creates an advantage when everyone has the same AI?

Curiosity, adaptability and the willingness to break down silos, according to the panel. Rodda named curiosity, Daspit named adaptability and human connection, and Choi wants to be a “wall breaker” who dissolves silos. Kippelman wants AI to surface hidden meaning he would not have noticed himself. Daspit reminds employees that “we hired them because they are humans.”

What are the five lessons for driving AI adoption?

The panel’s advice reduces to five lessons, each grounded in what the leaders described:

  1. Share ownership. Agree who owns enablement, governance and value, and name a bridge role between HR and IT.
  2. Make experimentation safe. Say which uses are low risk, train before you restrict, and have senior leaders show their own practice.
  3. Run two tracks. Set top-down goals for cross-functional processes, collect bottom-up ideas, and reward scaling the best ones.
  4. Govern across functions. Use a cross-functional council, tie decisions to company values and ask what problem each project solves.
  5. Start where friction is high. Rodda’s examples were talent acquisition and HR operations. Measure impact before you plan savings.

Frequently asked questions

What is the best way to drive AI adoption in the workplace?

Treat it as change management. The panelists recommended involving employees early, training them, having senior leaders model their own AI use, naming internal champions and being clear about where experimenting is safe. Gallup’s workplace data adds a manager angle: at organizations that have integrated AI, employees who strongly agree their manager supports their team’s AI use are 1.7 times as likely to use AI a few times a week or more.

What is AI change management?

AI change management is the practice of preparing, equipping and bringing employees along as AI changes how work gets done. It covers communication, training, leader role modeling, internal champions and clear rules for safe experimentation. Julie Rodda of iRhythm said the barriers are usually organizational and behavioral, not technical.

Who should own AI adoption in a company, HR or IT?

Both should share it. On the panel, the HR leaders described owning enablement, training and workflow redesign, while the CIOs owned technology choices and business value. Gartner predicts that 30% of organizations will have blended HR-IT teams for AI enablement by 2029. Most companies will keep the two functions separate but will need them closely coordinated.

How do you build employee trust in AI at work?

The panelists pointed to four moves: involve employees early, train them before restricting them, have senior leaders model their own AI use, and be clear about where experimenting is safe. Workday’s August 2026 AI@Work survey shows why it matters: half of respondents hid their AI use at least once in the past month.

What is PeopleReign?

PeopleReign is a people-first AI platform purpose-built for IT and HR employee service. Its action-taking AI helps employees resolve issues instantly and give every employee back 4-6 hours of productive time per week. It integrates with more than 100 enterprise systems, including ServiceNow, Salesforce, Zendesk, Workday, SAP SuccessFactors, Slack, Microsoft Teams and SharePoint, and works alongside them rather than replacing them.

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