The real “economic multiplier” of integrating AI into existing workflows is not automation, it’s augmentation. This is where work is redesigned so AI can empower humans to perform better.

That’s the conclusion of Harvard University’s Mark Esposito in his contribution to learning giant Pearson’s recent ‘Mind the Learning gap’ report.

Pearson’s modelling also concluded that AI-powered augmentation could add up to $6.6 trillion (or 15% of GDP) to the US economy by 2034.

However, realizing this trillion-dollar return from AI requires investment in not just technology, but people and their skills.

This is something that Pearson itself is embracing for its 18,000 employees worldwide. UNLEASH spoke to Pearson CHRO, Ali Bebo, to find out how the learning company practices what it preaches on AI work redesign.

How Pearson turned AI adoption into a workforce capability, not just a tech rollout

When it comes to AI, Bebo tells UNLEASH: “I’m energized by the opportunity, not intimidated by it. We are not chasing tools. We are redesigning work.”

“The real value of AI is not in using it once for a task. It is in building it into how people learn, communication and grow over time,” she continues.

Pearson’s AI work redesign has involved embracing its own DEEP framework, which stands for Diagnose, Embed, Evaluate and Prioritize.

Bebo shares: “We start by diagnosing how work should change. We break roles into tasks and map them to skills so we can be precise about where AI should augment work” – this has created clear shared language and strategy for AI use.

The message to Pearson’s employee base is “AI is a tool to augment their work, not replace their judgement.”

“If you’re using AI to avoid thinking, you’re doing it wrong.”

Then Pearson embeds learning into the flow of work. The idea is that “every employee can safely experiment with tools and learn what works in their context.”

One example of this that Bebo is particularly proud of is Communication Coach, an agent co-created with Microsoft and embedded into Teams.

“It listens to how you communicate in meetings and gives you feedback afterward – what makes it different is it measures skills through real behaviour, in the flow of everyday work, not in a training module or one-time assessment,” she explains.

Then Pearson measures what is creating value by looking at “real usage patterns” – this evaluation enabled Pearson to prioritize learning as a strategic investment.

What Pearson realized during this DEEP process was “innovation does not only come from the top.”

“Bottom-up exploration is how many of our best ideas surface.”

This framework “allows us to set a clear direction while still learning from the people closest to the work – that is how we turn AI adoption into a workforce capability, not just a technology rollout,” Bebo tells UNLEASH.

Pearson is already reaping the rewards of this approach.

Bebo shares that “people are telling us they feel more resourced, that there’s more focused investment in them, and that they know where they are and where they’re headed.”

“That tells us the tools and systems we’re putting in place are working.”

Why learning to learn and CTO-CHRO partnership is an AI ‘force multiplier’

Usually when technology is rolled out, the model is to deploy technology and then have people adapt to the system.

However, AI requires this to be inverted; success comes from learning and adoption happening together.

What makes Pearson’s DEEP framework so effective is it ensures that learning happens alongside AI rollouts, not as an afterthought.

“We do not treat learning as something separate from work. We build it into the work itself, so development happens while work is happening,” notes Bebo.

It’s crucial that people keep learning as their work evolves; that’s why Pearson has identified ‘learning to learn’ as one of the key power skills for its employee base.

“‘Learning to learn’ has two components: the behavioral side and the metacognitive side. We’re helping people develop specific techniques and build habits that change how they approach acquiring new knowledge.

“When someone has built these learning behaviors there’s a stickiness to it. They can pick up a new skill, and they can build proficiency much faster because the learning foundation is already in place.

“That’s why we call it a force multiplier.”

Bebo advises her HR peers to identify two or three power skills that will “accelerate and build resilience” in their organizations.

She also recommends to “act your way into the right thinking instead of thinking your way into the right actions.” HR can no longer have an 18-month planning cycle; Bebo is now working in six-month stints as that’s what the pace of change with AI demands.

While the rate of change is high, as Bebo looks into Pearson’s future, she tells UNLEASH that “the principles guiding our work won’t change.”

Importantly, “we’ll keep building the partnership between people and technology” – Bebo and Pearson’s CTO Dave Treat are the “new power couple”; their “partnership is essential because people architecture and tech architecture now intersect in ways they never have before.”

“You need that close collaborate to scale both.”