Your Career Adopted AI. It Hasn’t Absorbed It Yet.

A Restack on Steroids: extending another’s work into career progression. Built on Neha Kabra’s talk with Ashwin Francis and Raghav Mehra.

Adoption Is Not the Same as Absorption

I spend my days worrying about people walking into the workforce right now. This week I sat in on a conversation that never once mentioned careers, and all I did was listen carefully for parallels to the work I do at RISEUP@work. There were more than I expected.

This is a Restack on Steroids, which is how I take someone else’s thinking and carry it somewhere new, here into career progression. The source is a Cash & Cache Live conversation between Ashwin Francis, Raghav Mehra, and Neha Kabra (a McKinsey partner who advises banks and insurers on enterprise AI and writes HumAnIzing on Substack)

Neha highlighted a distinction that I’ve been reflecting on. She explained that enterprises often conflate adoption with absorption. Adoption refers to a manager monitoring how frequently you access a tool, whereas absorption occurs when you genuinely incorporate it into your routine, indicating a change in habit. In this stage, success is measured by what you produce, not just login frequency. “It’s not about adoption,” she emphasized. “It’s really about absorption, and absorption happens when habits change.”

She was talking about billion-dollar institutions. She could just as easily have been talking about a 23-year-old on their first team.

Here is the uncomfortable parallel. Your career is an enterprise, and it is making the very mistake Neha is warning her clients about. You have adopted AI. You can prompt your way to a polished deck, a clean analysis, a confident answer, on day one. What you have almost certainly not done yet is absorb it, and the gap between those two is where careers will quietly be won or lost over the next decade.

Absorption is the thing you cannot fake

Adoption you can perform. Absorption you have to earn, and the research is starting to show how easily the earning gets skipped. A Microsoft and Carnegie Mellon study of knowledge workers found that the more people trusted the tool, the less critical thinking they engaged in, and that handing routine work to a machine strips away the everyday reps that used to build judgment (Microsoft Research, CHI 2025). MIT put caps on people’s heads while they wrote with an AI assistant and recorded the weakest brain engagement of any group, which they named cognitive debt (MIT Media Lab). And a 2025 study in the journal Societies found the link between heavy AI use and weaker critical thinking ran deepest among the youngest people studied (Gerlich, Societies 2025). Put those next to Neha’s warning, and it sharpens into something personal. The people most able to adopt AI without absorbing it are the ones earliest in their careers.

Set the direction. Let AI change the flight.

Neha’s next idea was about strategy, and it travels straight into a career. A strategy that changes just because the underlying technology changed, she said, was never a strategy. The direction is London to New York. AI simply gives you a faster flight. Carve that line in the sand, and different routes and speeds are fine, but the destination holds.

Few early in their careers maintain this discipline. Your chosen direction reflects what you aim to master and the judgment you want to develop. AI accelerates your progress toward your goal but doesn’t determine its destination. The mistake is relying on the tool to choose your path, pursuing what seems easiest each quarter, resulting in rapid but aimless progress over a year. Define your core before leveraging AI to speed your advancement.

The mental exercise you skip

Her headline, the one she repeated, was that we overestimate what AI does in twelve months and underestimate what it does in ten years. Cloud took fifteen years to absorb, she reminded them, and plenty of enterprises still have not finished. Your judgment compounds on that same slow curve.

The reps you skip this year do not show up as a bad review. They show up in Year +10 as an absence, the expertise you were supposed to have built and did not. This is not a hunch. Anders Ericsson spent a career showing that expert performance is built through deliberate practice, the effortful reps most people would rather avoid (Ericsson, on deliberate practice). AI is extraordinarily good at removing exactly those reps. Convenient today. Expensive later, with interest.

Context is the moat, so build yours on purpose

The most strategic thing Neha said was about moats, using TSMC as an example. What makes the company defensible is not the factory; it is the context around it, the supply chain, and the accumulated know-how that nobody can quickly copy. If data can be shared and the tools are available to everyone, she asked, what is actually left to protect? Context.

The same is true of you. Your moat is never the output AI can generate for anyone with a login. It is the context only you accumulate: how your clients actually behave, why a number feels wrong before you can prove it, what happened the last three times someone tried this. She told her clients to keep an A-team in the loop with every vendor and to decide at each step what is shareable and what is not. Do that with yourself. Outsource the typing and gatekeep the thinking, because the thinking is the only part that stays yours.

Nobody has defined “high-value work”

Her most honest moment was an admission. She pointed out that while everyone claims AI will free humans to focus on high-value tasks, nobody clearly defines what those tasks are. Although judgments on taste and value are often discussed, an average person with an average IQ isn’t expected to have exceptional judgment, so what does that advice actually mean for them? She correctly notes that the definition is vague, and for someone just starting their career, this ambiguity becomes their entire goal. Instead of waiting for a job description, you define your role and judgment before anyone can specify it. Those who intentionally shape it are the ones who stop being average. Neha also cautioned companies against telling employees to automate themselves out of jobs, because no one willingly destroys their own value. The personal version of this risk may be even quieter but more dangerous: Don’t let AI automate away the crucial struggles that shape and build you.

She is right that it is undefined, and for someone early in their career, that undefined space is the entire assignment. You do not wait for a job description for judgment. You build it before anyone can write one, and the people who build it deliberately are precisely the ones who stop being average. Neha also warned companies never to tell staff to automate themselves out of a job, because no one destroys their own value on command. The individual version is quieter and more dangerous. Do not let AI automate away the formative struggle that was going to build you.

Absorb, do not just adopt

So, what does building absorption, rather than adoption, look like this year? Three habits carry most of it:

• Use AI to execute, and keep the thinking for yourself. A deliverable you cannot defend is adoption wearing absorption’s clothes.

• Do the hard reps AI offers to skip. Especially the messy first steps of any process, because those are the ones you have to be able to trace when something breaks.

• Build context on purpose. Stay in the room and in the hard conversation long enough to accumulate the one asset that cannot be handed to anyone else.

This is the whole reason RISEUP@work exists. Your career is the one asset you carry across every job, every boss, and every tool cycle, and its value in an AI world is your absorbed judgment, not your ability to produce output the whole world can now produce. If you want an honest read on whether you are absorbing AI or merely adopting it, our short RISEUP AI-usage Diagnostic is built for exactly that, at maven.riseupatwork.com/rad.

Neha’s clients will spend the next decade learning that a tool you have installed is not a capability you have absorbed. You get to learn it now, at the very start, while the habit is still forming and the cost of fixing it is close to nothing. Adopt the tool. Absorb the judgment. Only one of them is your career.

Thank you, Neha, for a conversation worth sitting with.

Watch the full conversation

The whole discussion is worth your time. Here it is.

Your Enterprise Adopted AI. It Hasn’t Absorbed It Yet.

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About the author: Dr. Deepak Bhootra is the Founder and CEO of RISEUP@work. He spent three decades as a senior leader within Fortune 100 companies across four countries, earned a doctorate studying what truly drives professional satisfaction and commitment, and has spent 13 years as an ICF-certified coach in more than 1,500 coaching relationships. RISEUP@work turns that experience into a career progression platform, built for the growth that begins after you are hired. It is live and welcoming early adopters at riseupatwork.com.

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