Someone Quit Their Job Over AI. Here's What That Tells Us.

Hello,

This is Simon with the latest edition of The Weekly. In these updates, I share key AI related stories from this week's news, list upcoming events, and share any longer form articles posted on the website.

Over the last few weeks, I've been interviewing clients across a range of businesses, sectors, sizes, and countries, asking them what AI means to their organisation, whether there's a mandate to use it, and how that shapes the way they work.

Something I didn’t expect to hear, was a client mentioning they'd resigned from their previous job because the company didn't share their enthusiasm for implementing AI. That's someone making a career decision based on where they believe the future is heading.

What struck me across all these conversations was just how varied the picture is. Some businesses know they're only at the start of their AI journey and are honest about it. Others are genuinely well advanced. And then there's a third group who believe they're further along than they actually are. That last one is probably the most interesting category to work with.

For some organisations, AI adoption is being driven from the top down. For others, it's entirely grassroots, led by individuals with a personal interest who are quietly getting on with it regardless of what leadership is or isn't saying.

Despite all the variation, there was one consistent thread: every single business knows they need to adopt AI. Whether it's to improve internal workflows, drive efficiency, or simply avoid being left behind by competitors, no one is arguing about whether to do it. The debate is about how and when.

There's no universal standard or timeline for AI adoption. Every business is moving at a pace that reflects their own priorities and resources, and that's fine.

Does it make my job straightforward? Not really. Everyone needs something slightly different at any given time. But that's also what makes it interesting.

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In this section, I’m going to bring to you a real world example of AI use. This week, we take a look at how JPMorgan Chase uses their AI platform to run part of their commercial business more efficiently.

A Yale School of Management analysis, reported by Fortune on April 29, found that the primary labour market damage from AI is falling not on established workers but on those who have not yet entered the workforce. Entry-level job postings fell to 38.6% of all postings in March 2026, down from 44% in 2023, and graduate unemployment has climbed to nearly 6%, rising at twice the rate of the broader workforce since 2022. AI tools are now performing the summarising, drafting, and initial-code tasks that organisations used to assign to junior hires; Goldman Sachs estimates AI is already reducing US employment by roughly 16,000 jobs per month, with younger workers absorbing a disproportionate share.

Why it matters: The conventional reassurance that "AI creates new jobs as it eliminates old ones" assumes workers can reskill into new roles. If the entry-level rungs are being removed, organisations face a talent pipeline problem in three to five years.

A Bloomberg columnist warned on May 2 that autonomous AI trading systems pose a catastrophic and underappreciated risk to global financial markets, following an earlier Bloomberg report that a fully functional AI trading platform was assembled in just six days. More than 80% of trades on the New York Stock Exchange are now executed by algorithm, and a single malfunction in 2025 briefly caused a 6% drop in the S&P 500 within minutes. The column, headlined "We Can't Let the Bots Put Global Finance at Risk," called for urgent regulatory intervention.

Why it matters: The speed at which AI trading infrastructure can be assembled — and the opacity of how it makes decisions — creates systemic exposure that existing oversight frameworks were not designed to handle.

Meta has confirmed it will begin laying off approximately 8,000 employees — around 10% of its workforce — on May 20, with further cuts expected through the second half of 2026, according to reports from CNN, Axios, and others published April 23. The company is also cancelling 6,000 planned hires, reducing effective headcount by around 14,000 positions, while simultaneously committing to spend between $115 and $135 billion on AI infrastructure this year — nearly double its 2025 capital expenditure. Teams are being reorganised into AI-focused "pods," with recruiting and HR absorbing cuts of 35 to 40%.

Why it matters: This is the clearest signal yet that large organisations are not simply adding AI alongside their existing workforce — they are using it to justify permanent structural reductions. When a company doubles its AI budget and cuts 10% of its people in the same breath, that is a strategic bet, not a cost-saving measure.

Thanks for reading, and see you next Thursday.

Simon,

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