Hands-On Training Key to Learning Gen AI

When Joe Whittinghill talks about generative AI, it’s not from the outside looking in. As Microsoft’s recently retired Chief Talent and Learning Officer, Whittinghill spent 25 years at the tech giant, working across HR, finance, M&A, and most recently, spearheading culture and learning transformation efforts alongside the CEO and CHRO. He shared in my interview with him a deep understanding of organizational learning and talent development that has given him a unique vantage point on how generative AI is reshaping work—and why hands-on training is the key to unlocking its promise.

Embracing the Frontier of AI Through Practice 

Whittinghill is quick to frame generative AI as not merely a trend, but a generational inflection point. “It’s going to be one of the biggest changes not only to work and learning, but to human life that we’ve seen in generations,” he says. From accelerating pharmaceutical development to transforming corporate education, the possibilities are vast—but so are the fears.

What he’s seen, both at Microsoft and in the broader landscape, is that anxiety around AI often stems from uncertainty. “People think they’re going to lose their job to a robot or some software program,” he explains. But the solution, he argues, isn’t to retreat from the technology—it’s to engage with it directly. That’s why, across Microsoft, from engineers to HR professionals, employees were encouraged to start experimenting with AI tools early and often.

“Just start playing with it,” he advises. “Familiarity brings down anxiety.” It’s a deceptively simple but profoundly effective strategy. Whether it’s a CEO or an early-career employee, hands-on interaction with AI helps demystify its capabilities and lowers the psychological barriers to adoption.

Why Hands-On Training Works 

One of the biggest insights from Whittinghill’s experience is that active experimentation—what is called “learning in the flow of work”—is the most effective approach to AI adoption. “Hands-on training has been so far the most successful approach, because success begets success,” he notes.

This learning-by-doing model is powered by natural language processing (NLP), which allows users to engage with AI conversationally. The barrier to entry is lower than with earlier technologies. “You write a sentence like you’re talking to someone, like you’re asking a librarian,” Whittinghill says. “It’s not a search engine—it responds to your questions and  remembers the conversation and builds on it.”

Because of that, microlearning modules, real-time coaching, and interactive workshops with live AI tools outperform traditional training formats. It’s not about memorizing functions, but about building confidence through use. The act of experimenting—and seeing meaningful results—is the most direct path to capability.

Addressing Fear and Building Trust 

Despite its user-friendly interface, generative AI still generates resistance. One of the major roadblocks Whittinghill highlights is fear—specifically, fear of obsolescence. Citing the World Economic Forum’s projection that 40% of core skills used today will be irrelevant in a few years, he emphasizes that this kind of transformation can spark existential anxiety.

“When you impact people’s livelihoods, anxiety really spikes,” he says. But instead of avoiding that fear, Microsoft tackled it head-on with transparent communication, education, and clear examples of AI’s benefits at work and home. Whittinghill frequently pointed to real-world applications—like AI helping farmers optimize water use in drought-prone areas—to illustrate how the technology could support, not replace, human expertise.

Moreover, giving employees early wins with AI not only builds skills, it boosts morale. “Humans love to learn,” he adds, “but more than that, they love success.” That sense of accomplishment becomes a powerful motivator in reducing resistance to change.

Personalized Development, Powered by AI 

Beyond learning, AI is also transforming people development. One of the most promising areas Whittinghill highlights is the rise of personalized AI agents that assist employees in real time. These tools go beyond training—they act as intelligent coaches, helping managers prepare for one-on-ones by recalling past conversations, nudging them with follow-ups, and even suggesting moments to discuss career goals.

These systems, while still maturing, promise to make employee development more timely, tailored, and human-centered. However, they hinge on privacy. “The AI needs to know who you are, and what you’re working on,” Whittinghill explains, “but only if that data is secure.” Microsoft, he says, has been vocal about calling for regulation and ethical boundaries to protect user data—especially in sensitive areas like mental health, where AI also holds great promise.

His work with the University of Washington’s mental wellness board has exposed him to the emerging potential of AI-driven therapy tools, but also the critical importance of human oversight. The message is clear: trust is as important as technology.

Shaping the Future of Work, One Prompt at a Time 

Looking forward, Whittinghill is optimistic that AI can help organizations move toward more balanced, human-centered work models. He points to Northern European countries as examples of productivity without burnout. “They’re very focused when they’re at work, and they deeply value time with family and community,” he says. AI, he believes, can help other regions catch up—not by replacing work, but by making it more efficient.

Whether it’s AI preparing your taxes or organizing a family calendar, Whittinghill sees a future where technology frees us to spend more time on what matters. And yet, this isn’t a future that builds itself. It requires leaders and employees alike to get involved, iterate, and adapt.

He recalls a recent speech to broadband providers in Montana—organizations ranging from four-person teams to large companies. His advice was consistent: “Don’t start with your AI strategy. Just start using it. Unleash your employees to experiment.”

And perhaps most powerfully, he believes generative AI marks the return of a lost art: rhetoric. Not in the classical sense, but in the practical one. “It’s the skill of communication and persuasion,” he says. “Your prompts, your questions—that’s how you get clarity.” In his view, those who become rhetoricians of the digital age—clear, curious, and courageous—will thrive.

The Path Forward

Joe Whittinghill’s message is both simple and profound: the best way to learn generative AI is to do it. By encouraging curiosity, hands-on engagement, and a culture of safe experimentation, leaders can empower their organizations to embrace the AI era with confidence, not fear.

The future of work isn’t about mastering a new tool—it’s about evolving our mindset. And as Whittinghill makes clear, the sooner we roll up our sleeves and get our hands on the technology, the better prepared we’ll be to shape what comes next.

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