Audit your role before AI does

Hey -

Last issue, I introduced two lenses — the techno-optimist and the techno-pessimist — and asked which one you'd been using to read what's happening in the world of work.

Most of us toggle between them depending on the day. On a good day, you're the human who AI elevates. On a harder one, you're quietly wondering how long your role looks the way it does.

Both reactions are rational. But neither gives you the full picture. And neither tells you what to do.

That's what this issue is for.

What both lenses agree on

Whichever direction this goes, one thing is clear: work is being restructured at the task level and that affects everyone differently depending on where you sit.

If you're early in your career, traditional entry points are shrinking as AI automates the tasks that once justified those roles. If you're mid-career or senior, the picture is different but no less significant. Your role is being redesigned from the inside. The boundaries between functions are blurring, teams are restructuring, and your value increasingly depends on how well you integrate AI into your decision-making and what productivity gains you can drive as a result.

The question isn't whether new jobs will emerge or old ones will disappear. It's whether you understand how your role is being unbundled and rebuilt, early enough to do something about it.

The Career Audit

Here's a four-step process for doing exactly that. It takes less than an hour. Do it with your current role in mind, not your job title, but what you actually do week to week.

Step 1: Map your tasks, not your title

Break your role into its component parts, everything you actually do in a given week. Get granular. Not "I manage stakeholders" but "I write status updates, run alignment calls, flag risks to leadership, interpret data for non-technical teams."

Your title is a label. Your tasks are what's being evaluated.

Step 2: Sort by substitutability

For each task, ask one question: Could a well-prompted AI do this with the same output quality? Sort into three buckets:

Most people find they sit heavily in the first two buckets.

Step 3: Find your leverage layer

Look at your low-substitutability tasks. These are your anchors. Now ask: what is it, specifically, that makes me the one doing this?

Is it institutional knowledge? Relationships built over years? The ability to read a room? Cross-functional credibility? The capacity to make a call when the data is ambiguous?

That's your leverage layer. The thing AI augments but can't replace. If you can't name it clearly, that's the work.

Step 4: Redesign your role around it

This is the part most people skip. Knowing your leverage layer isn't enough. You have to actively move toward it. That means delegating or automating your high-substitutability tasks, developing the skills that sit adjacent to your leverage layer, and making that leverage visible to your manager, your team, and your network.

The professionals who will thrive are the ones who've done this audit. They know which problems actually need them. They know where their judgment, relationships, and pattern recognition sit. And they use AI to clear everything else out of the way, protecting the space where they're genuinely irreplaceable.

Before you go

I've been writing about how AI is reshaping roles, but I wanted to give you something you could actually use this week, not just think about.

So I built The Career Audit, a 10-minute exercise that helps you see your own role more clearly: which parts of your work are genuinely hard to replace, which parts are quietly at risk, and where your real leverage is hiding.

Most professionals spend 60–70% of their time on work that AI can already replicate. This exercise shows you where you actually stand.

It's one page. Do it with your last working week in mind.

Until next issue,

Gaziza