We don't program intelligence line by line anymore, we shape behavior through data, models, prompts, tools, and governance.

We don't program intelligence line by line anymore, we shape behavior through data, models, prompts, tools, and governance. But here's the flip side. AI is now shaping our behavior at work too and a new Microsoft Research study shows us where.

Researchers analyzed 200,000 anonymized Bing Copilot conversations and mapped them to O*NET (the U.S. Department of Labor's database that breaks down 900+ occupations into the specific work activities they involve).

That let them measure AI use against real job tasks across the whole economy.

One of the key findings is that AI is concentrated in information work == the creation, processing, and communication of information.

A few things to note:

1\ AI is following the information. Most jobs have an information work component, which is why AI feels relevant almost everywhere. The depth of impact tracks the depth of information work in the role.

2] Wage and education matter LESS than people think. The correlation between AI applicability and wage is weak. Which means AI is not just coming for "low-skill" or "high-skill" work, it's applicable for ALL types information work (to varying degrees).

3\ There are two distinct AI futures inside every org. The study separates "what users ask AI to help with" from "what AI actually does in the conversation".

→ Some roles will use AI as a collaborator on the work they already do.

→ Others will delegate entire tasks to AI and shift focus elsewhere.

The leadership question becomes knowing which is which on your team.

Interestingly, the study notes that AI is often playing the role of advisor, teacher, or expert.

Microsoft Research Work 20260428 Ram S SHARED.pdf

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So, as word processors democratized typing will AI democratize expertise itself?

This rests on three conditions:

→ People can successfully apply AI expertise

→ AI broadens access to expertise

→ People have sufficient foundational knowledge to apply and evaluate AI assistance

That third condition (in my opinion) is the whole game.

In a world where everyone can generate 10 plausible answers, the rarest skill is knowing which one is right.

The premium on judgment goes up, not down.

Most of us built that judgment by doing the very work AI is now set to automate. Which leaves three uncomfortable questions:

→ How do people build expertise when the entry-level reps disappear?

→ Where does a human need to be in the loop?

→ What is trust, in a world of infinite plausible answers?

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Broader still I see this as the beginning of a new definition of expertise.

The next decade will compress more change than the last century.

The humans who thrive will be the ones who learn to shape it. They will bring judgment where AI brings scale, and meaning where AI brings answers.

And therein lies the BIGGEST opportunity.

I don't think of this as expertise being taken from us. I see it as being handed to us to redefine and shape.

Will we actively shape it or let AI shape it for us?

Until next time,

Ram

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Ram Srinivasan

MIT Alum | Author, The Conscious Machine | Global Future of Work and AI Adoption Leader published in Business Insider, Fortune, Harvard Business Review, MIT Executive Viewpoints and more.

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Disclaimer:

Ram Srinivasan currently serves as an Innovation Strategist and Transformation Leader, authoring groundbreaking works including "The Conscious Machine" and the upcoming "The Exponential Human."

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