Every time a media company announces layoffs, speculation turns to AI. “They’re replacing journalists with robots.” “This is just the beginning of the AI job apocalypse.”

I’ve been watching media layoffs for 20 years. The current wave looks like every previous wave—same causes, same dynamics, same flimsy justifications from management.

AI isn’t driving these cuts. Not yet. But it will, and that’s what we should actually be worried about.

The Real Reasons for Current Cuts

Let me walk through what’s actually behind the layoffs we’re seeing:

Advertising market weakness. Digital advertising has been soft, and programmatic rates keep declining. Publishers dependent on advertising are cutting to match reduced revenue.

Platform traffic collapse. Facebook’s news exit, Twitter/X’s decay, and Google’s AI features have crushed referral traffic for many publishers. Less traffic means less revenue means layoffs.

Failed diversification bets. Many publishers invested in video, podcasts, or events that didn’t pan out. Now they’re unwinding those investments—and the people who staffed them.

Private equity pressure. Heavily leveraged publishers owned by private equity face debt payments regardless of market conditions. Staff is the biggest expense, so staff gets cut.

Post-pandemic normalization. Some publishers hired during the pandemic traffic boom and are now right-sizing to match more typical audience levels.

These are all familiar dynamics. They explain most of what we’re seeing.

Why AI Isn’t the Current Driver

When companies lay off workers because of AI, they generally do a few things:

• Announce AI investments simultaneously with cuts
• Restructure specific functions around AI capabilities
• Change job descriptions for remaining workers to include AI
• See productivity gains that justify headcount reductions

Most current media layoffs show none of these patterns. Companies cutting staff aren’t simultaneously deploying AI replacements. They’re not restructuring around AI capabilities. They’re just cutting.

The exceptions—places where AI genuinely contributed to cuts—are rare. A few publishers have reduced transcription staff. A handful have automated certain data journalism roles. But these are exceptions, not the pattern.

The AI-driven layoff narrative fits a compelling story but doesn’t match observed reality.

Why This Matters

You might wonder why I care about the distinction. Layoffs are layoffs—does the cause matter?

It matters because we’re focusing on the wrong threat.

The current layoffs, while painful, aren’t fundamentally new. The industry has been through waves of cuts before. We know how to respond: unionization, skill development, entrepreneurship, career transitions. These strategies address structural industry decline.

AI-driven displacement will be different. It will require different responses. And we’re not preparing for it.

What AI-Driven Layoffs Will Actually Look Like

Here’s my prediction for how AI will eventually affect media employment:

Phase 1 (Now-2026): AI assists journalists, making individuals more productive without reducing headcount. Early adopters gain advantage but don’t displace workers.

Phase 2 (2026-2028): Some functions become substantially automated—routine content, basic research, simple editing tasks. Headcount reductions begin in these areas.

Phase 3 (2028+): AI capabilities expand to more complex journalism tasks. Major publishers reduce staff significantly while maintaining or increasing output. The economics of journalism change fundamentally.

We’re still in Phase 1. The current layoffs are a different phenomenon.

How This Changes the Response

If I’m right that current layoffs aren’t AI-driven but future ones will be, it suggests different strategies:

For current layoffs: Traditional responses remain appropriate. Collective bargaining, severance negotiation, career transition support, entrepreneurship. The people being laid off now face a difficult but familiar labor market.

For future AI displacement: Different preparation is needed. AI literacy becomes essential—not just using tools but understanding how they’ll reshape the industry. Positioning for roles AI can’t replicate. Building skills that complement rather than compete with AI.

For the industry: The time to prepare for AI impact is now, while employment is merely declining rather than collapsing. Policies, retraining programs, and structural adaptations need development before the crisis hits.

What Journalists Should Do Now

If you’re a working journalist, here’s my advice:

Develop AI skills. Not to replace yourself—to make yourself more valuable. Journalists who can effectively use AI tools will outcompete those who can’t.

Build unique capabilities. What can you do that AI can’t? Deep source relationships. Local presence. Investigative judgment. Complex ethical reasoning. Audience trust. Double down on distinctively human skills.

Create portable assets. Personal brand, subscriber relationships, demonstrated expertise—assets that go with you regardless of employer or industry structure.

Stay flexible. The media industry’s future is uncertain. Rigid expectations about career paths or work structures may need revision.

What Media Companies Should Do Now

For publishers and editors:

Plan for AI honestly. Don’t use AI as cover for cuts driven by other factors. But do think seriously about how AI will change operations over the next five years.

Invest in transition. Workers displaced by AI deserve more support than workers displaced by ordinary business cycles. The automation that benefits the company should share some value with affected workers.

Maintain human judgment. The rush to automate shouldn’t compromise editorial quality. AI can assist; it shouldn’t drive.

Be transparent. When AI does drive changes, say so. Pretending otherwise damages trust with workers and readers.

The Uncomfortable Conclusion

We’re in a strange moment. The media industry is shedding jobs for reasons that predate AI while being anxious about AI job losses that haven’t quite arrived yet.

The current pain is real. The future pain will also be real—and probably worse. We’re not preparing adequately for either.

I don’t have a comprehensive solution. What I can offer is clarity about the distinction. Current layoffs call for current responses. AI-driven transformation calls for different preparation.

Confusing the two serves no one except executives who want to blame technology for their own choices.