The Gap: AI Now Forecasts Its Own Future

Log Entry: 2026-02-19 | Subject: AI, Labor, Economics, Displacement, Workforce

Deutsche Bank did something interesting this week. They asked their AI tool to identify which industries AI itself plans to disrupt. The results, covered by Fortune, were predictable in the broad strokes: software, finance, customer service, media. But the framing matters. The AI projected 92 million jobs displaced by 2030, alongside 170 million new roles created. A net gain on paper. But paper does not pay rent during the transition.

The Numbers: Who Is Projecting What Institutional estimates of AI's impact on global employment by 2030 (millions of jobs) Jobs Displaced New Jobs Created Jobs Exposed / At Risk (not all eliminated) 0 200M 400M 600M 800M WEF / Deutsche Bank 2025–2026 | Global 92M displaced 170M created ← +78M net Goldman Sachs 2023 | Global 300M exposed Jobs affected, not all eliminated No creation estimate provided McKinsey 2017 | Global 400M–800M displaced 555M–890M created IMF 2024 | Global ~40% of global jobs exposed (~1.3B+) Scale exceeds chart — percentage-based estimate, no creation figure provided Forrester 2026 | US Only 10.4M displaced (US) US-only figure — no creation estimate; revised up 4x from 2.4M in 2023 The Gap: Only WEF and McKinsey estimate both sides. Everyone else quantifies the displacement but leaves the recovery as a theoretical exercise. That silence is the gap. Sources: World Economic Forum Future of Jobs Report 2025 · Goldman Sachs (Briggs & Kodnani, 2023) · McKinsey Global Institute 2017 IMF World Economic Outlook 2024 · Forrester AI Jobs Forecast 2026 Note: Estimates measure different things — "displaced" ≠ "exposed" ≠ "affected." Direct comparisons require caution.

Disruption Is Not Displacement

Here is what keeps nagging at me. We keep conflating disruption with displacement, and they are not the same thing.

Disruption reshapes how work gets done. Displacement removes the person doing it. Both are happening simultaneously, and the conversation around each requires completely different thinking.

Disruption is an engineering problem. You adapt your tools, your workflows, your business model. Displacement is a human problem. It is about identity, livelihood, and what happens to the millions of people caught in the gap between the old role vanishing and the new one materializing.

Nobody Has an Answer Yet

That gap is what nobody has a credible answer for.

Universal basic income gets floated. Retraining programs get funded and quietly forgotten. New economic models get theorized in white papers that do not survive contact with reality.

The honest answer is: we do not know what comes next. Not really. The scale of occupational transition being projected (12 million people in the U.S. alone shifting careers) is without modern precedent, and our existing frameworks for managing workforce change were built for a world that moved slower.

Net Positive Is a Macro Statistic

I am not saying the sky is falling. The net job creation numbers might hold. But "net positive" is a macro statistic, and people live micro lives.

The question is not whether the future of work looks different. It is whether we are being honest about the fact that we have not invented the bridge yet, and that admitting we do not know is more useful than pretending we do.

The Protocol: Disruption is an engineering problem. Displacement is a human one. The 92 million jobs displaced and 170 million created look great in aggregate, but aggregate does not help the person standing in the gap. The honest move is to stop pretending we have built the bridge and start actually building it.
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