As AI reshapes the workplace, who gets impacted first - fresh hires or managers?

Welcome back, explorers.
We’re at a turning point in the workplace - where human roles are being redefined not by policies, but by algorithms. As AI quietly takes on more tasks in the workplace, it’s time to ask: who is being impacted first, and how should we respond?

Let’s dive in together. 👇

 🔥Today’s big AI story

Let me take you to a familiar scene from just a few years ago… A recent graduate walks into their first job. Nervous, excited, eager to prove themselves. Their manager - often someone juggling multiple team members, KPIs, and Zoom calls - welcomes them with a blend of encouragement and, well, mild panic. There’s always too much to do, and not enough time.

Fast forward to today.
That same graduate? Might be competing with a chatbot. That manager? Might be using AI to get reports, write strategy decks, and analyze performance - or worse, being questioned if their role is still essential. This brings us to a tough but timely question: As AI becomes a co-worker, who gets impacted first - fresh hires or middle managers?

🧠 Let’s unpack what’s really happening

AI isn’t just automating tasks; it's reshaping how work is structured.

According to a 2023 McKinsey report, AI is set to automate 60–70% of tasks done by knowledge workers, especially those that are repetitive and rule-based.

This includes:

• Drafting emails

• Creating reports

• Scheduling meetings

• Sorting data

• Even helping write performance reviews

So both entry-level jobs and middle management roles are in the firing line. But the type of impact is different.

👶 Fresh Hires: Losing the Playground

Entry-level roles often teach people how to work. It’s where you learn office culture, build communication skills, and develop your instincts.

But when tools like ChatGPT and GitHub Copilot can write emails, summarize documents, and even generate code, many companies are questioning:

"Do we really need that junior hire right now?"

In fact, low-end coding is one of the first areas being automated.

Fresh engineering graduates who once spent their first few years writing basic scripts, debugging, or fixing UI errors now face a new reality - AI can often do this work faster, cheaper, and without supervision.

A report from GitHub shows that developers using AI coding assistants completed tasks 55% faster, especially on routine assignments. But that also means companies are hiring fewer junior developers, opting instead to pair senior engineers with AI tools.

That’s a big deal. Because if the ladder’s bottom rung is missing, how do future engineers climb?

🧑‍💼 Managers: The Invisible Squeeze

Now let’s talk about middle managers - often the glue between leadership and teams.

AI tools are now:

• Creating dashboards

• Summarizing team updates

• Prioritizing to-do lists

• Even conducting sentiment analysis from employee messages

This leads some companies to think:

"If AI can manage workflows and communication, do we need as many people managers?"

Gartner predicts that by 2026, 20% of traditional middle management roles will be redesigned or removed, as AI steps in to manage processes and decisions.

But here’s the nuance: managers who adapt, who lead through influence and not just instruction, will thrive. Those who don’t - won’t.

💡 So... who’s really at risk?

The short answer: both.

The longer answer: It depends on how adaptive you are.

AI doesn’t eliminate value - it eliminates waste.

If a fresh hire can show curiosity, adaptability, and bring creative or interpersonal value - they’ll still thrive.

If a manager uses AI to empower their team instead of fearing it, they become more valuable than ever.

🔁 What should we do?

If you’re early in your career:

• Don’t just learn tools. Learn how to think and how to connect.

• Build skills AI can’t replace: storytelling, emotional intelligence, decision-making.

• If you’re an engineer, go beyond syntax - learn architecture, systems thinking, and problem framing.

If you’re a manager:

• Use AI to remove friction, not replace connection.

• Lean into strategy, mentorship, and creativity - things AI still can’t replicate well.