AI Might Not be the Actual Cause of Enterprise Job Cuts

Though it might be quite easy to attribute job cuts to the impact of artificial intelligence, that is likely not the actual cause of job cuts in the corporate overhead area at the moment. Many employers arguably “overhired” in the wake of the Covid pandemic. 

During 2020–2022, U.S. firms in technology experienced simultaneous labor scarcity and demand uncertainty from several sources:

• Demand surged suddenly

• Workers exited the labor force or changed jobs at unprecedented rates

• Hiring pipelines broke.

• Losing employees felt existential.

So companies stopped hiring “to plan” and started hiring to secure supply. In essence, labor became something to “stockpile,” not optimize. That was the root of the overhiring wave. 

The rationale was fairly simple:

• Many workers leaned in the direction of  “lifestyle” over “employment”

• Being short engineers, for example, could cap revenue growth

• Being understaffed could cause outages, customer churn, or lost market share.

• Hiring later might be impossible at any price.

So firms rationally decided “it was safer to carry excess labor” than risk being unable to execute.

By mid-2022 to 2023, though, demand normalized. Growth rates slowed; capital became more expensive; productivity fell sharply and the scarcity of labor ended. 

Phase	Labor Market Condition	Company Behavior	Headcount Decision Logic
Pre-Covid (2019)	Balanced labor market	Hire to forecast	Staff aligned to revenue
Early Covid (2020)	Hiring freezes	Defensive posture	Preserve cash
Post-Covid surge (2021)	Extreme labor scarcity	Aggressive hiring	“Hire anyone we can get”
Peak demand panic (2022)	Workers hard to find	Labor hoarding	Hire ahead of demand
Demand normalization (2023)	Labor supply improves	Hiring freezes	Headcount locked in
Correction phase (2023–2024)	Normal job market	Layoffs & restructuring	Resize to revenue
Post-reset (2024–2025)	Rational labor pricing	Targeted hiring	ROI-based staffing

“AI” might be the stated rationale for the job cuts, but that is likely a smokescreen for a past wild hiring binge. AI might eventually have a labor market impact in its own right, but that is likely not what is driving the current wave of big-company layoffs. 

And that “boom and bust” cycle is not terribly unusual for other  industries beyond computing.  

Era	Scarce Resource	Corporate Behavior	Outcome
1999–2000 dot-com	Software engineers	Hire aggressively	Mass layoffs 2001
2006–2007 housing	Construction labor	Expand payrolls	Collapse 2008
2017–2018 oil boom	Petroleum engineers	Labor hoarding	Bust layoffs
2021–2022 tech	Knowledge workers	Over-hire	2023–24 layoffs