People, Productivity, and Performance: AI Insights from Daniel Bertrand

In a recent conversation with Daniel Bertrand, Digital Enablement Lead at Microsoft, we explored what it really takes to move AI from "interesting" to "impactful" inside a modern enterprise. The short version: It’s not about the tech. It’s about the people.

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We’ve seen this before.

"I would relate it most closely to the early days of the internet," Daniel said. "You had all this potential, but no one really knew what to do with it. If you think about those early websites, they were basically just digital brochures."

That’s where we are with generative AI. The use cases are basic: summarize my emails, draft a response, recap a meeting. The business impact? Still to be determined.

But that’s changing quickly. Faster than any other shift in tech.

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What’s holding teams back? Expectations.

"Everyone’s expectation for the technology was that, oh, AI and Copilot is going to do all the parts of my job that I hate," Daniel shared. "And Copilot doesn’t do that. Then they moved on."

He calls this the "trough of despair" — the moment where the promise of the tech doesn’t match the lived experience.

But the real blocker isn’t capability. It’s clarity. Most organizations haven’t invested in helping people understand how to use AI in the context of their role. They’re skipping over the critical part: enablement.

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Five things every organization needs to drive AI adoption

Microsoft, like many of the companies Daniel consults with, has landed on five key moves that separate organizations getting real ROI from the ones still stuck in pilot mode:

1. Executive alignment: "AI has to be integral. It can’t be out there just doing its own thing. It has to be part of driving the overall strategy."
2. Empowering champions : "Identify who are the cool kids in your org… the people that are already successful in the role. Recruit them as champions and influencers." ‍
3. Role-based immersion: "People really want AI to help them in their specific role in their specific flow of work." ‍
4. Daily practice: "We would send prompts for people to try. That would just get them in the habit of doing it. Then they’d go off and think, 'What if I tweak this prompt?'" ‍
5. Make it fun: "We threw in leaderboards. For sales teams, that kind of healthy competition really triggered the learning we wanted to see."

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You can’t skip the people part.

One of the biggest insights from Microsoft’s internal rollout? The more technical someone is, the more likely they are to resist AI.

"My value to Microsoft is my technical expertise. If I’m using AI, I’m shortchanging Microsoft on my value," Daniel recalled from internal feedback. That fear is real. And it’s why enablement has to include more than training. It has to address mindset, performance expectations, and career evolution.

"If AI can do the work you’re focused on today, that means you can expand your brainpower thinking about tomorrow."

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From awareness to transformation

Microsoft tracks usage with a framework that measures three levels of engagement:

• Monthly active usage = awareness

• Weekly active usage = adoption

• Daily active usage = transformation

"When we get north of 50% daily active usage of Copilot, we started to see some positive impacts," Daniel shared. In pilot cohorts, this meant significant gains in pipeline creation and revenue.

That’s the goal: not just tools in hands, but AI in flow.

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The bottom line

AI adoption isn’t a tech rollout. It’s a behavior shift. A mindset shift. A culture shift.

"AI is not going to take your job. A person who is utilizing AI better than you might."

Organizations that get it right aren’t just implementing tools—they’re designing new ways of working. And they’re doing it by starting with the one thing that never changes: people.

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Interested in what that looks like at scale? We can help.