Microsoft Layoffs: Tech giant trims fat to feed AI growth, 6,000 jobs gone — here’s who’s out, who’s safe

Microsoft has laid off over 6,000 employees, or roughly 3% of its global headcount, as part of a sweeping structural shift to align its operations with its fast-growing AI ambitions. The layoffs come despite a strong quarterly report boasting $70.1 billion in revenue — a 13% rise year-on-year — and $25.8 billion in net profit. With performance numbers like these, many are asking: why the cuts?

Behind the figures lie cold calculations. Microsoft's $80 billion investment in AI infrastructure is fuelling mounting depreciation costs estimated at $15–20 billion annually. These expenses have already pushed gross margins down from 72% to 69%, a drop that spooked investors accustomed to consistent 70%+ returns.

To regain margin stability and keep Wall Street onside, the company moved to reduce high-cost headcount. The result: a deep and targeted workforce reduction.

Veteran engineers, middle managers, and high earners hit hardest

Among the displaced are some of Microsoft's longest-serving and most technically skilled workers. One 25-year veteran was laid off on his birthday. A senior engineer who had patched million-dollar vulnerabilities was cut. Even a key contributor to TypeScript, with nearly two decades at Microsoft, was shown the door.

According to internal reports shared on the Blind forum, employees earning more than $600,000 were disproportionately affected — this includes senior engineers, senior product managers, and principal managers.

The layoffs are expected to save Microsoft around $2.2 billion in the first year and up to $2.9 billion annually thereafter. These savings account for 40–50% of the $4.5–5.5 billion in capital Microsoft plans to return to shareholders in FY25 through dividends and buybacks.In short: investors demand high margins. High-salary employees are the cost.

Nadella’s AI strategy accelerates workforce transformation

CEO Satya Nadella has long championed AI as Microsoft’s future. Speaking at a recent Silicon Valley event alongside Meta’s Mark Zuckerberg, Nadella said, “Maybe 20, 30% of the code that is inside of our repos today, and some of our projects, are probably all written by software.”

Nadella described Microsoft as a "distillation factory", reducing large AI models into smaller, task-specific ones. He reiterated the company’s mission: to “bring technology and people together to realise the promises of AI responsibly.”

Despite this, AI is rapidly automating routine tasks once handled by junior engineers. Currently, AI generates up to 30% of Microsoft’s codebase. While entry-level jobs are being overtaken by automation, many senior engineers are being cut due to age bias, high salaries, or roles no longer deemed essential.

Layer by layer, management roles dismantled

CFO Amy Hood explained in the April 30 earnings call that Microsoft is trimming management layers to increase agility. The company plans to reduce its management structure from 8–12 layers to just 6–8.

Roughly 1,020 to 1,750 middle managers — or 17–25% of those laid off — are affected by this flattening. Meanwhile, product managers also faced steep cuts, with 900–1,400 positions eliminated. Microsoft is adjusting its engineer-to-PM ratio from 5.5:1 to 7–8:1.

The message is clear: fewer bosses, more coders, more AI.

Why not retrain workers instead?

As layoffs mount, some question why Microsoft doesn't redeploy its engineers to AI data centres or infrastructure roles. The reasons are blunt: skill mismatches, limited availability of relevant roles, and cost.

For example, AI data centres require specialised skills in hardware, energy systems, and high-performance computing — areas in which software engineers and PMs typically lack training. Additionally, each AI data centre requires only around 1,000 workers during construction and 100–300 long-term staff to operate.

Microsoft argues that widespread retraining would slow “agile development” and raise costs, undermining investor confidence.

Who’s safe now?

Very few roles, it turns out. Executives — who make the cuts, not take them — remain untouched. Most others face varying degrees of uncertainty.

Relatively safer are those tied directly to Microsoft’s AI, cloud, and security strategies. These include:

• AI researchers and machine learning engineers
• Cloud computing engineers
• Cybersecurity specialists
• AI data centre and infrastructure roles (e.g. robotics engineers, energy specialists)

As Microsoft shifts its business engine to AI, these roles are increasingly vital. Traditional software engineering, once at the heart of Microsoft’s growth, is being relegated — or automated.

A wider pattern: global layoffs across industries

Microsoft isn’t alone. Other global firms are following suit in pursuit of efficiency and investor returns.

Amazon axed around 100 roles in its devices and services division. An Amazon spokesperson told Reuters: “As part of our ongoing work to make our teams and programs operate more efficiently, and to better align with our product roadmap, we’ve made the difficult decision to eliminate a small number of roles.”

Panasonic is cutting 10,000 jobs worldwide to overhaul underperforming units. President Yuki Kusumi said, “Compared with industry peers… our selling, general and administrative expenses ratio remains exceptionally high.”

PwC US laid off 1,500 employees following a review, with many hit unexpectedly through “time-sensitive” Teams meeting notices. “This was a difficult decision, and we made it with care,” the firm said.

Cybersecurity firm CrowdStrike slashed 5% of its staff despite reporting a 25% revenue increase. CEO George Kurtz said, “While we will continue to prudently hire… we are reducing roles in some areas of the business.”

Microsoft’s latest move signals a sharp shift in tech’s human capital strategy. Earnings are high. AI is surging. But jobs — especially well-paid ones — are on the line.

Even seasoned engineers and respected experts are no longer guaranteed job security. As AI becomes more efficient and less expensive than human talent, and as shareholders chase ever-higher returns, companies are recalibrating what — and who — is essential.

The AI revolution is here. And it’s not waiting for anyone.