AI is setting the people side of work on fire

Happy Thursday, everyone.

It's been just over a year since It's Not the Work launched, and the response from HR leaders like you has been the best part of it. Your replies and thoughtful messages every week are a reminder of why we started writing this in the first place.

We've been thinking about new ways to bring you knowledge you can actually use at work, and from this week we're trying something new. The regular weekly issue now comes with a downloadable guide. You can read part of it inline below, or download the full version and share it with your team for free."

Alongside the guides, we're also working on a series of HR leader interviews. If you are interested in contributing, you can apply here.

Quick poll for you, so we can tailor what comes next.

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🤝 This edition is kindly brought to you by Metaview

Metaview surveyed 505 recruiting and hiring leaders, and the numbers are hard to ignore. 90% described their partnerships as "good." 58% admitted they actively wish they could work around their counterpart. That disconnect is showing up in real business damage, especially speed-to-hire and candidate loss.

🤐 The hiring tension is more serious than most leaders realize: 58% of recruiting and hiring leaders wish they could bypass their counterpart entirely

⚡ Misalignment is directly costing teams talent: Teams with excellent recruiter-manager partnerships are 60% less likely to lose candidates to faster-moving competitors

🤖 AI becomes valuable when it improves collaboration: Teams that say AI is core to hiring are 3.8x more likely to report excellent working relationships

📈 The strongest hiring teams treat AI as shared infrastructure: 85% of companies exceeding business goals are actively using AI in hiring workflows

Read the full report here

Most AI-at-work coverage is about productivity. What HR actually has to deal with is everything underneath that: the anxiety, the trust issues, the fairness questions, and what happens to people when the texture of their work quietly shifts beneath them.

That's what this week's guide is about. What AI Is Doing to Your People pulls together six places where that's already playing out. Three of them are below. The other three are inside the guide.

There's an assumption baked into most AI-at-work conversations: faster and easier means better. Behavioural science has been politely disagreeing with that for years.

Csikszentmihalyi's research on flow shows that real engagement needs a task that stretches you, somewhere between boredom and overwhelm. Take the challenge away and the experience flattens. The IKEA effect tells us people value what they've put effort into building, and self-determination theory adds that mastery is a core psychological need, one that only grows with effort. Over-automation, meanwhile, erodes the underlying skill over time (Parasuraman & Manzey, 2010).

Let AI handle the friction, but keep the thinking yours. If it writes every first draft, the underlying skill plateaus. Watch out for roles that quietly become review jobs. A day spent editing AI output looks efficient on paper and feels monotonous in practice. And track energy alongside output, because rising productivity with falling engagement is a leading indicator of attrition.

The Financial Times reported earlier this year that HR teams are now receiving beautifully structured, legally fluent grievances drafted with AI assistance in minutes. Perfect tone, impressive formatting, and the occasional hallucinated piece of legislation.

When I wrote my own formal complaint years ago, I rewrote it obsessively, deleted half of it, and lost sleep over the rest. That friction forced me to think hard about what I was actually alleging. AI removes it, and the burden of judgement now sits entirely with whoever reads it.

The psychology here is well-mapped. Authority bias kicks in fast: when a complaint reads like a barrister drafted it, the tone alone nudges decision-makers toward deference. Research by Reber and Schwarz (1999) showed that text that reads more smoothly is judged as more likely to be true, even when the content is identical. Overloaded HR teams default to surface cues like polish and confidence rather than weighing the substance of the argument.

What that means in practice

On TikTok, a user called Leo posted the breakdown of his interview for a dream news reporter role. The interviewer turned out to be an AI bot that opened with "Let's circle back. Tell me about a time when, when, when…“ and got stuck in a loop. Leo couldn't get a word in. Without missing a beat, the bot thanked him for his "great responses." A few days later, a rejection email arrived addressed to ”Henry,“ congratulating him on an interview that had apparently taken place the day before.

AI hiring is sold on speed and objectivity, but most of the tech still struggles to deliver on either. An Australian study found AI interview tools have error rates as high as 22% when dealing with accents and speech variations, and the same systems often flag career gaps as red flags, which disproportionately affects women and caregivers.

What that means in practice

Tell candidates upfront if they're talking to a bot. Ask vendors for accent-and-speech error rates broken down by demographic. Build a human escalation path so that when something goes wrong, a real person fixes it within 24 hours. The tool screens. The human hires.

Those are three of the six. The full guide covers the other three: AI predicting team dynamics, AI coaching, and the pull toward work people can actually see and touch, with the behavioural science underneath each and three to four things to try in practice.

→ Get What AI Is Doing to Your People (free PDF)

This is the first guides coming your way over the next few weeks. The PDF is yours. Pass it on to anyone in your team who'd find it useful.

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