Monday.com Cuts 630 Jobs (20% of Staff) to Fund AI Push

What happened

Monday.com is cutting 630 jobs, equivalent to 20% of its global headcount, as the work-management software provider redirects investment toward an AI-first strategy. The layoffs span the company's operations worldwide and mark one of the most significant workforce reductions in its history as a public company.

According to TechCrunch, the cuts are explicitly framed by Monday.com as a reallocation of resources rather than a response to financial distress — the company is trimming staff to free up capital and organisational focus for building and scaling AI-driven capabilities across its product suite.

Why it matters

The move is another signal that software companies increasingly see AI not as an add-on feature but as the organising principle for where headcount, budget and leadership attention should go. For Monday.com, that means fewer people doing the work AI is expected to absorb or accelerate, freeing resources to build AI-native features rather than incrementally improving existing tools.

For leaders in experience and digital transformation, the story is a live test case of a tension many organisations are quietly navigating: shrinking the human layer that supports customers while betting that AI systems can maintain — or improve — service quality at scale. How well Monday.com manages that transition, particularly for customer-facing functions, will be closely watched by peers making similar calculations.

By the numbers

• 630 roles are being eliminated at Monday.com as part of the restructuring.
• 20% of the company's global workforce is affected by the cuts.

The Renascence take

Reframing layoffs as an "AI-first" pivot is now a familiar corporate script, but the real question is rarely whether AI can do the work — it's whether the organisation has redesigned its service model around that assumption before removing the people who previously caught the gaps.

Cutting a fifth of a workforce to fund AI ambitions is a capital allocation decision, not a service design one — and treating it as the latter is where companies get burned. The customers and employees left behind don't experience a "strategy," they experience whatever gaps open up when institutional knowledge, judgment and escalation paths disappear faster than AI systems can replace them. A customer-obsessed operator making this trade would map every touchpoint the departing roles used to own, stress-test the AI or automated alternative against real edge cases first, and be transparent with customers about what's changing and why — rather than letting them discover it through slower responses or a noticeably different quality of service.