AI Is Creating New Winners and Losers. Here’s How Smart Leaders Are Restructuring to Get Ahead.

In 2025, the tech industry finds itself caught in a paradox. On one hand, we’re witnessing an AI gold rush. Companies are investing billions, betting that artificial intelligence will unlock the next wave of innovation. Meanwhile, over 22,000 tech workers have already been laid off this year — 16,000 in February alone.

Apparently, this signals a turning point in how companies structure teams and allocate talent. Intelligent systems are redefining how teams work, which skills are gaining value and where human roles still matter.

It’s not simply about whether AI is causing the layoffs. What matters is how firms respond. As layoffs accelerate across the tech industry, leaders now face a choice: restructure with purpose or fall behind.

What is driving the wave of job cuts

Tech industry layoffs have become a defining feature of AI-driven transformation since 2022, and the trend hasn’t slowed. Microsoft is cutting 9,000 jobs, following earlier rounds this year. HP is reducing its workforce by 2,000 people in October, expecting to save nearly $300 million. At first glance, these moves resemble classic downsizing during economic uncertainty.

But profitability doesn’t exempt companies from resetting. SAP, for example, despite strong performance, is letting go of up to 10,000 employees. The company is flattening management, consolidating teams and rebuilding platforms for AI-driven operations. Even younger firms are following suit. Scale AI, a major player in model training, recently laid off 200 employees and 500 contractors, just weeks after closing a $14.3 billion deal with Meta.

Look closer, and a pattern emerges. As firms rebuild around AI, roles tied to legacy systems, siloed processes or repetitive tasks are disappearing, making room for new capabilities, but not without disruption.

Related: AI Won’t Wait for Your Strategy — Why Should Your Leadership?

What kind of roles is the AI era creating?

While some jobs disappear, I’ve noticed new ones emerge to support AI-first operations. The focus is shifting from repetitive work to compact, cross-functional teams that build, train and integrate intelligent systems.

The most in-demand skills I see today combine technical fluency and adaptive thinking — engineers who scale AI infrastructure, product managers who understand model behavior, and analysts who can bridge data, business and strategy. Meanwhile, traditional entry-level paths like QA, support and content moderation are narrowing, putting AI upskilling at the center of workforce planning.

The impact is global. The U.S. remains the epicenter, but Europe and India are also restructuring. For example, Tata Consultancy Services is cutting over 12,000 jobs — the largest layoff in its history, citing a skills mismatch. As automation spreads, experts warn that up to half a million roles could be displaced over the next few years.

For younger professionals, this creates urgency. Opportunities are still there, but the timeline to reskill is shrinking fast.

How you handle tech industry layoffs matters

Layoffs are never easy, but how they’re handled matters more than how many people are affected. From my experience advising companies through transitions, three principles make the difference.

Tie every decision to strategy

When layoffs happen, people assume they’re just about saving money. That perception stems from poor transparency, making cuts feel abrupt and disconnected from a bigger plan.

The goal is to make every workforce change part of your strategy, not just a reaction to external circumstances. To do so effectively, here is a short checklist to guide the process:

• Define the purpose – Translate your AI or growth goals into clear priorities that guide which roles evolve or phase out.
• Map impact areas – Evaluate which functions add value, which can be automated and where human expertise remains critical.
• Redeploy before reducing – Move people toward new AI projects or targeted reskilling before considering exits.
• Communicate the vision – Explain how changes position the company for future growth.

Handle layoffs in one clear move

Nothing unsettles a team more than uncertainty. When layoffs come in waves, people lose focus and start wondering if they’ll be next. Еven top employees may leave to escape the instability. Furthermore, repeated cuts also erode confidence among investors and customers.

If layoffs are unavoidable, make them a single, well-prepared move. Align leadership on scope and timing, communicate transparently about the reasons, and support those affected right away. Then, reassure the remaining team with a clear view of what comes next.

Related: Why Every Company Will Need an AI Specialist by 2026 — and What Happens If You Don’t

Reskill before you replace

As AI reshapes work, many roles are evolving rather than disappearing. Repetitive, rule-based tasks — common for junior developers, testers and support agents — are most exposed. With targeted support, these employees can move into areas like AI-assisted QA, data curation or model monitoring, where human judgment still matters.

To make this shift sustainable, organizations must become skills-based, placing skills not job titles, at the core of talent management. This lets you redeploy people into new value areas as strategy changes. According to Deloitte, SBOs move from rigid job structures to dynamic, skills-oriented models that allow talent to flow where it’s needed.

From my perspective, transitioning toward this model starts with three practical steps:

1. Decompose work into skills – Break jobs down into tasks and skills so you can see where existing people already have relevant capabilities and where gaps exist.
2. Link skills to strategy – Decide which skills will drive AI value (e.g. data literacy, prompt engineering, evaluation) and map people toward those.
3. Prioritize learning – Assign employees to small, concrete AI initiatives so they acquire and apply new skills on the job, not in isolation. At Accedia, for example, our Innovation Development Center acts as a living lab where cross-functional teams pilot AI use cases in real workflows, build working solutions, and scale the proven ones across departments.

Conclusion

Tech industry layoffs reveal more than cost pressures. They signal a shift in how organizations define value, talent, and readiness for the AI era. From what I’ve observed, the companies that thrive treat this moment not as an ending, but as a chance to redesign, reskill and rebuild smarter. The question isn’t whether AI will change your workforce – it’s whether you’ll use it to make your people and your organization stronger.

In 2025, the tech industry finds itself caught in a paradox. On one hand, we’re witnessing an AI gold rush. Companies are investing billions, betting that artificial intelligence will unlock the next wave of innovation. Meanwhile, over 22,000 tech workers have already been laid off this year — 16,000 in February alone.

Apparently, this signals a turning point in how companies structure teams and allocate talent. Intelligent systems are redefining how teams work, which skills are gaining value and where human roles still matter.