How do you move your business forward with AI?

I start with four questions: What’s causing pain now? What’s coming that worries you? Which opportunities are you missing? And where do you want the business to go? Those answers give AI a purpose and give us something worth measuring.

Then I talk to the people doing the work. Leadership sees the consequences; practitioners can often show you where the trouble begins. A specialist spending hours finding information or copying it between systems is a useful place to investigate. That’s the thinking behind how we approach discovery at Whispering: understand the work, choose a manageable problem, and test a better way.

Someone who can connect the business goal to the work required to achieve it, and take responsibility for moving it forward. My experience across strategy, design, development, and operations helps me understand where teams depend on one another. I’ve brought developers into brand discussions because understanding the customer and the business changes the decisions they make in code.

That ability mattered when I managed a 12-project HR transformation for one of the largest healthcare networks in the country. The goal was to help a 400-person operations center grow from supporting 50,000 employees to 186,000. I managed daily progress, risks, and leadership communication while helping teams resolve problems. The year-long program succeeded about two weeks ahead of schedule.

That was before AI. The lesson still applies: improvements in one area depend on what happens around them. AI makes it even more important to have someone who understands those connections and can bring the right people into the decision.

I would begin with an honest conversation about what’s changing, what isn’t decided, and where people have concerns. Then I’d involve them in choosing and testing the improvements. People know which parts of their jobs waste their expertise. Giving them a say in changing those things creates a much stronger starting point than handing them a tool and expecting enthusiasm.

The pressure is real. In Microsoft’s 2025 Work Trend Index, 80% of the workforce surveyed said they lacked enough time or energy to do their work. I see an opportunity to give skilled people more room to do what they were hired for. That means planning what they can accomplish with the time AI frees up, including better customer experiences and opportunities the team couldn’t previously pursue.

Agree on what improvement looks like before the pilot begins. It could be less rework, a shorter wait for customers, or more work completed without adding pressure to the team. Compare the result with the starting point, include the cost of checking AI’s work, and ask the people using it whether it genuinely helps. In PwC’s 2026 CEO survey, 56% reported no significant financial benefit from AI to date. Adoption alone tells us very little.

I’ve also learned that trust needs follow-through. Earlier in my career, I gave people too much latitude on two high-stakes projects and paid for it. I now pay closer attention to strengths, limitations, and early signs of trouble. With AI, I apply that same judgment: make responsibility clear, review the results, and intervene when something isn’t working.

Four years of building with AI have changed how I work. They’ve also made my earlier experience more useful. I can see new ways to solve familiar problems, with a clearer understanding of what it takes for people to adopt the change. That’s the combination I bring to product and design leadership.