Embrace Strategic Atrophy: Rethinking Skills in the Age of AI

There's a quiet panic in many workplaces today. It's not just about AI taking jobs—though that's a valid and complex concern—it's also about something more subtle: the fear of losing certain skills. I've had executives, educators, and engineers all say the same thing to me in different words: "If I start relying on AI for this task, I'll lose the ability to do it myself."

They're not wrong. But they might be asking the wrong question.

Over the last several years, I've worked at the intersection of AI and human-centered design—as a professor, a researcher, and a consultant helping organizations navigate the evolving relationship between people and intelligent tools. One pattern I keep seeing, no matter the industry: the tension between embracing AI and clinging to the skills we've historically valued.

But what if some skill loss is actually a good thing?

What If Skill Loss Isn't a Problem?

Let's face it: skills will atrophy. They always have. In fact, the history of work is a history of letting go.

When calculators became widespread in the 1970s, people worried that mental arithmetic would vanish. And to some degree, it did. But what emerged instead was a stronger emphasis on problem solving, estimation, and numerical reasoning—skills that matter more in real-world decision-making. We preserved the conceptual foundation and let go of the repetitive mechanics.

The same is true now, only AI is accelerating the scope and speed of change. Whether it's drafting reports, writing code, or analyzing trends, we're offloading more and more to AI tools—and that's not inherently a loss. It's a shift.

Strategic Atrophy: A Different Perspective

I call this strategic atrophy. It's the deliberate and thoughtful decision to allow some skills to fade because others are becoming more valuable.

We've been through similar shifts before. When GPS became mainstream, map-reading became a niche skill. When spellcheck became ubiquitous, we stopped stressing about perfect spelling. Today, generative AI is helping us rethink everything from content creation to customer support.

Instead of trying to cling to every skill, we need to get better at identifying which ones matter most—and which we can afford to let go of. Strategic atrophy is about smart prioritization, not surrender.

Skills to Keep, Skills to Let Go

This isn't a blanket call to abandon expertise. Far from it. Strategic atrophy means selective skill maintenance. Here's how I tend to break it down:

Skills to Keep

• Critical Thinking and Judgment: AI can surface insights, but it can't weigh competing priorities, ethical dilemmas, or long-term implications. We need people who can ask the hard questions AI can't.
• Human Empathy: Emotional nuance, active listening, and building trust are all squarely in the human domain. AI may simulate tone, but it doesn't feel. We still need that human touch.
• Collaboration and Communication: Cross-functional work, stakeholder alignment, and cultural understanding are all skills AI supports but doesn't own. Humans still lead in building consensus and resolving friction.

Skills to Let Go (or Redesign)

• Routine Data Analysis: AI excels at processing structured data. Analysts are better off focusing on translating patterns into decisions rather than processing raw numbers.
• Mechanical Writing Tasks: From email drafts to press releases, AI can speed up production. People should focus on originality, persuasion, and tone.
• Scheduling and Administrative Coordination: Let AI handle the calendars. Use that time for strategic planning and high-value relationship-building.

Avoiding the Trap of Nostalgia

A common trap I see is nostalgia—clinging to skills simply because they've always been valued. But value is context-dependent. What helped someone succeed in 2010 may be irrelevant by 2030.

That doesn't mean we shouldn't mourn the loss of certain abilities. But we should recognize that the goal isn't to preserve everything—it's to evolve purposefully. Skill loss isn't inherently bad. Sometimes, it's the price of growth.

A Case in Point: Legal Research

In law firms, junior associates historically built their credibility through long hours of legal research. Now, AI tools like Casetext and Harvey can summarize cases, extract citations, and draft memos in a fraction of the time.

Some firms fear this undermines associate development. But others are asking better questions: What do we want new lawyers to focus on instead? The answer: storytelling, advising clients, and legal strategy. Those are human-first tasks, and they're not going away anytime soon.

How to Talk About This With Your Team

It's not enough to make strategic decisions about skill prioritization—you also need to bring your team along. If you're a leader, consider running workshops around three core questions:

1. What skills do we currently spend the most time on?
2. Which of those create the most value?
3. Where could AI give us leverage—and where do we still need human strength?

Make it safe for your team to talk about what they're ready to stop doing, and what they want to double down on. That's how you create buy-in, not resistance.