The Real Infrastructure Crisis: Skills That Depreciate Faster Than Hardware

The Real Infrastructure Crisis: Skills that Depreciate Faster than Hardware

By John W. Mitchell, President and CEO, Global Electronics Association

Key Summary

• Massive AI investment is accelerating technology adoption, while spending on workforce training continues to decline.

• Skills are now depreciating faster than hardware, creating a critical but overlooked infrastructure risk for employers.

• The electronics industry offers a clear preview of rapid skills obsolescence driven by fast innovation cycles.

• Future competitiveness depends on permanent upskilling and treating workforce skills as a managed strategic asset.

Over the past year, Google, Microsoft, Meta, and Amazon have poured $360 billion into capital expenditures, mostly to build and power AI. Across the economy, companies are racing to buy AI tools, automate workflows, and deploy agents faster than their competitors.

AI is reshaping the economy at a pace with almost no historical precedent. Consider this: ChatGPT reached 365 billion annual searches in just two years. Google needed 11 years to hit the same milestone. 

But while investment in machines is exploding, investment in people isn’t even close.  In fact, both the number of hours individuals spend on formal training and the average employer expenditure on training have declined slightly in recent years. This comes at a moment when skills are depreciating faster than hardware.  But for employers, ensuring that our human capital keeps pace with our technological capital isn’t just a nice-to-have; it’s vital. 

The Electronics Industry as a Preview of What’s Coming

You can already see the future in the electronics sector, where innovation cycles are so extreme that yesterday’s expertise is nearly obsolete.

Engineers who once built careers around 3G and LTE standards now face a world dominated by 5G, ultra-wideband, and soon terahertz-range communications. Materials science is shifting just as quickly: silicon’s long reign is giving way to gallium nitride, and early breakthroughs in graphene and other novel materials are rewriting the road map for next-generation semiconductors.

These shifts don’t just require new products. They require new skills.

Hardware engineers suddenly need strong software instincts. Factory technicians need fluency in automation, robotics, and AI-driven quality control. Entire subfields now demand workers who can operate at the intersection of the physical and digital worlds.

What’s happening in electronics is simply the most visible version of what’s about to hit every sector.

The Coming Economy of Permanent Upskilling

For decades, we’ve talked about “lifelong learning” as a nice idea—something individuals should probably do when they have time. But AI leaves no room for half measures.

Every role in every industry is about to change. Some gradually, many abruptly. And unless companies treat human capability the same way they treat any other strategic asset—something that requires upkeep, investment, and long-term planning—they will fall behind.

This isn’t a question of corporate benevolence. It’s a question of competitiveness.

Skills Depreciation: The Asset Employers Aren’t Managing

Companies already track depreciation on servers, software licenses, and physical equipment. Yet the asset most vulnerable to obsolescence, the skill base of their workforce, rarely gets similar attention.

That must change.

This piece argues that skills depreciation should be treated as a core management responsibility rather than a workforce development talking point. Sector-wide career pathways, employer-led upskilling, and public-private investment models are no longer optional; they’re the infrastructure required to operate in an AI-accelerated economy.

Machines are getting smarter at an exponential rate. Humans can, too, but only if we build systems that make continuous skill renewal as routine as upgrading hardware.