Your Senior Team Is More Exposed to AI Than Your Graduates, and Why That Matters

Anthropic just published a report measuring how AI is actually affecting the labour market, based on observed usage rather than forecasts. Most of the coverage has focused on job losses. The more useful findings sit further down, and for mid-market leaders they are the ones that matter.

I spend my days in private conversations with leaders of scale-up and mid-market companies. In public, they talk about AI with confident ambition. In private, the question is different: “How do I deal with this on top of everything else?”

It reminds me of the late 2000s, when digital marketing was moving from a niche experiment to a board-level issue. Every leader knew it was important. Most were too busy with the core business to properly engage. They delegated it, underfunded it, and hoped it was just a new channel rather than a fundamental shift in how business worked.

Many got it wrong. They woke up a few years later to find their competitors had built huge, direct-to-customer relationships they couldn’t replicate.

AI is following the same pattern, on a shorter timeline.

I’m not a tech founder with a utopian vision. I’m an operator who has spent 20 years watching how technology actually lands inside complex businesses. My job is to cut through the noise for leaders who have to make payroll and deliver a P&L.

The Anthropic report measures what’s happening rather than what might happen [1]. And the findings point somewhere most leaders aren’t looking.

Most Companies Are Worried About the Wrong Jobs

The assumption most leaders are working from is that AI threatens entry-level, administrative roles. The data says otherwise.

The Anthropic report shows that workers with the highest exposure to AI are not junior. They are more likely to be:

Older (average age 42.9) More educated (four times more likely to hold a graduate degree) Higher-paid (earning 47% more on average)

That’s much closer to your senior team than your graduate intake.

Senior, white-collar work is saturated with tasks that large language models excel at: summarising complex information, drafting reports, analysing data, communicating findings. These are the core activities of knowledge work.

The primary issue isn’t a future threat to your junior talent pipeline. It’s the current, expensive, and often inefficient workflows of your most senior people.

A £20-a-Month Alternative to a £500,000 Consulting Engagement

I often hear leaders say, “We have bigger problems right now than AI.”

Fair enough, but AI is increasingly how you solve those bigger problems. Point it at your operational data and it can surface many of the same patterns a consulting team would look for: where your highest-paid people spend time on low-value, repetitive tasks, where information sits in silos, where hours go into manually compiling reports that could be automated.

The difference is the price. A top-tier consulting firm charges £500,000. An AI subscription costs £20 a month. That forces a simple question: “Why are we paying our best people to do work a machine can do?”

The Anthropic report calls this the “Deployment Gap.” For many roles, the theoretical capability of AI is over 90%, but real-world usage is barely a third of that. The gap is a management and process problem, not a technology one, and AI is making it visible.

Most companies already know they need these operational improvements. What’s changed is that the cost of not making them is now quantifiable, and harder to defer.

Three Questions to Put to Your Leadership Team on Monday

This isn’t about a five-year plan. It’s about what you raise this week.

1. “Where are our highest-paid people doing £20-an-hour work?”

Start with a workflow review, not a headcount review. Ask your senior team to log their time for one week, focused on reporting, summarising, and drafting. The results will give you a heat map of your biggest augmentation opportunities. The goal is to free these people from low-value work so they can focus on decisions, client relationships, and leadership.

2. “Are we building an experience gap into our talent pipeline?”

The Anthropic report identifies one clear, structural change: a 14% slowdown in hiring for workers aged 22-25 in exposed fields. We are, in effect, automating the training ground for our future leaders. If the traditional entry-level tasks disappear, where does the next generation learn their craft? This is a long-term risk. You need a plan for developing talent that doesn’t rely on the old apprenticeship model of repetitive, administrative work.

3. “Who has permission to get this wrong?”

Real adoption doesn’t come from a top-down mandate. It comes from bottom-up experimentation. Right now, in your organisation, there are people who are curious and motivated to use these tools. Most of them don’t have explicit permission to try things that might not work, or to spend time on a project without a guaranteed ROI. Find those people, give them a real business problem, a small budget, and the air cover to experiment. What they learn will become your company’s early advantage.

The Inefficiencies Are Already on Your Balance Sheet

The tools are cheap, accessible, and getting better every month. The problem that remains is organisational, not technological. The low-value work is already spread across your most expensive teams, and you don’t need a strategy document to start finding it.