What to Do If the AI Bubble Bursts

2026-04-12 · Source: Tech Policy Press · Field: Government & Public Sector — Public Policy & Governance, Regulatory & Compliance, Economic Analysis & Policy · Depth: Intermediate, extended

Summary

Asad Ramzanali, Director of AI and Technology Policy at the Vanderbilt Policy Accelerator, discusses his report "After the AI Crash," which argues that a potential AI bubble burst presents a significant policy opportunity. Ramzanali contends that a "basic math problem" exists, with J.P. Morgan anticipating $5 trillion in AI investments by 2030 against only tens of billions in current revenue, creating a substantial gap. He emphasizes that policymakers should proactively prepare for this anticipated crisis, drawing lessons from past financial downturns like the 2008 housing crisis. The report proposes several policy considerations, including stopping circular equity financing and opaque private credit in data center investments, addressing distortive government subsidies for data centers, exploring public cloud infrastructure from stranded assets, protecting workers through expanded social safety nets and a "Digital Works Progress Administration," and implementing utility-style regulation with a new digital regulator to separate hardware and software businesses.

Key takeaway

For policymakers and industry leaders weighing future tech regulation, this analysis underscores the urgency of proactive planning for a potential AI market correction. You should consider developing "on-the-shelf" policy responses now, focusing on structural reforms like separating hardware and software businesses and increasing financial transparency, rather than waiting for a crisis to force reactive, potentially insufficient measures. This approach can transform a market downturn into a chance for meaningful, long-term tech sector reform.

Key insights

Proactive policy preparation for a potential AI bubble burst can transform crisis into an opportunity for tech sector reform.

Principles

• Crises enable significant policy shifts.
• Financial engineering obscures market realities.
• Separating hardware and software can instill market discipline.

Method

The proposed method involves preparing policy responses before an anticipated AI financial crisis, drawing on lessons from past economic downturns to implement structural reforms rather than reactive, technocratic solutions.

In practice

• Halt circular equity financing in AI.
• Increase transparency for private credit in data centers.
• Expand unemployment insurance during tech downturns.

Topics

• AI Bubble Burst
• AI Policy
• Financial Engineering
• Data Center Subsidies
• Public Cloud Infrastructure

Best for: Policy Maker, Consultant, Executive

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Editorial summary, takeaway, and curation by AIssential. Original article published by Tech Policy Press.