No, AI Isn’t the Next Enron—It’s the Next Electricity

GeekWire’s October 23, 2025, article, “What will happen when the AI bubble bursts?,” argues that the artificial intelligence industry is following the same destructive pattern Cory Doctorow calls “enshittification” — a predictable corporate decay where platforms prioritize users, then advertisers, and finally profit extraction, leading to systemic decline. The piece draws a direct line from the current AI boom to tech bubbles like the dot-com crash, warning that as costs soar and returns stagnate, the industry’s value proposition could implode under its own hype.

Geekwire: What will happen when the AI bubble bursts? Tech prognosticators weigh in with ensnarkification

How will the companies that have invested tens of billions of dollars in the infrastructure for artificial intelligence fare when the enshittification hits the fan? That question came in for a lot of attention — and snark — when tech pundits Cory Doctorow and Ed Zitron sat down in Seattle to muse about what’s happening in the world of AI.

Both men know a thing or two about enshittification, the process by which tech offerings gradually turn to crap due to the hunger for profits.

The way they see it, the bursting of the AI investment bubble is a given. And that’s not by any means a contrarian view. Even Microsoft CEO Satya Nadella and Amazon founder Jeff Bezos have acknowledged that the AI tech sector seems likely to go through some retrenchment, while insisting it will be followed by a resurgence that will bring huge benefits to society.

That’s where Doctorow and Zitron part ways with Nadella and Bezos.

“This cannot succeed,” Zitron said. “On top of the fact that everyone’s unprofitable, it’s not actually that popular, either. ChatGPT is very popular because a lot of people love being driven insane. … People will tell you AI’s coming, you must learn AI. The reason it’s not able to do your job is, it’s shit.”

Doctorow passed along the advice he said he gave to his daughter. “If you don’t know what you want to do at university, don’t go to university. Go to college and become an electrician,” he said. “There’s so much work for electricians, and we are going to be solarizing for the next 40 years. … It’s like being a plumber, but you don’t have to touch poo.”

He noted that the benefits extended beyond the money. “If you want to learn more, and you like it, you can become an e-eng [electrical engineer],” Doctorow said. “And if you don’t, you can put yourself through college by being an electrician — and learn finance.”

Context and Core Claims

The GeekWire article, authored by Alan Boyle, synthesizes the views of several technologists and economists who foresee AI’s investment frenzy as unsustainable. It suggests that massive capital outlays — data centers, chip supply, and escalating compute demands — create the same structural fragility that collapsed earlier tech booms. By invoking the “enshittification” trope, the piece portrays AI’s market behavior as both ethically and economically self-defeating: quality erodes as monetization pressures mount.

Counterargument: Innovation Cycles, Not Collapse

The first flaw in this reasoning lies in its mischaracterization of technological maturity. As Reuters and Bloomberg analyses point out, while overvaluation exists, there’s a critical distinction between speculative inflation and systemic rot. Unlike the dot-com bubble, AI is not merely a promise—it’s a deployed infrastructure underpinning logistics, cybersecurity, healthcare diagnostics, and energy optimization. Even if valuations are correct, these applications will not vanish, much as cloud computing endured after 2008.bloomberg+1​

Moreover, labeling this phase as “enshittification” oversimplifies the dynamics of infrastructure innovation. Wired’s own exploration of the same theme concedes that AI may still be in the “good to the users” phase, and that economic compression will likely lead to tiered pricing models rather than outright degradation. The existence of open-source foundations such as Hugging Face and Stability AI — driven by community governance — demonstrates an architectural resilience absent in prior centralized platforms.webpronews+1​

Data Economics and Market Elasticity

The assumption that AI’s rising costs will precipitate decline misunderstands elasticity in compute economics. Hardware evolution, particularly in inference efficiency, continuously reduces per-token costs. Analysts from Economic Times estimate that despite macroeconomic caution, AI’s aggregate bubble remains driven more by investor psychology than by exhausted technological limits. As optimization improves and competitive ecosystems (Cloudflare, Groq, Anthropic) introduce leaner inference pipelines, the “bubble” narrative loses predictive validity.economictimes​

Ethical and Regulatory Evolution

A deeper oversight in the GeekWire piece is its moral fatalism. The “enshittification” thesis assumes corporations cannot self-regulate or adapt under scrutiny. Yet, emerging regulatory mechanisms — from the EU AI Act to U.S. standards under the National Institute of Standards and Technology (NIST) — are explicitly designed to intervene before enshittification sets in. Doctorow’s framework was conceived in the absence of such oversight. Today’s AI firms operate under unprecedented transparency mandates, publishing model cards and ethics reports precisely to stave off the opaque value extraction that doomed ad platforms of the 2010s.wired+1​

Investor and Public Policy Outlook

While AI venture capital behavior reflects exuberance, historical analogies misfire. In prior bubbles, the underlying technologies (telecom, rail, and dot-com infrastructure) survived and ultimately drove decades of productivity growth. The “AI bubble” may deflate, but its substrate — multimodal reasoning systems, agentic automation, and cognitive APIs — will represent industrial scaffolding, not speculative residue.

In essence, GeekWire’s essay captures the zeitgeist of skepticism but conflates cyclical correction with systemic collapse. The reality is more complex: a recalibration rather than an implosion. AI’s trajectory, buffered by regulatory oversight, open innovation, and infrastructural necessity, positions it not as a narrative of technological decay, but as the next durable layer of the digital economy.bloomberg+2

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