The traditional government model of setting a regulation and waiting years to assess it is obsolete for AI. A new approach is needed: a dynamic board of government, industry, and academic leaders collaborating to make and update rules in real-time.

The Ministry of Economy, Trade and Industry (METI) categorizes sectors to apply targeted policies. 'Green' areas have lost supply chain autonomy and require diversification. 'Blue' areas possess technological superiority and need control (e.g., export controls). 'Red' areas face disruptive innovation and demand proactive strategic investment.

Effective government requires more than just budget and staff ("capacity"). It needs "dynamic capabilities": the agility to pivot, collaborate effectively, and learn from experimentation. Most public sector reform misses this, focusing only on reactive, market-fixing roles rather than proactive, market-shaping ones.

To move quickly in a shifting regulatory landscape, teams need a pre-agreed framework. By establishing clear decision rights, strong defaults, and explicit guardrails ahead of time, organizations empower teams to respond to crises autonomously without escalating every call.

Formal standards development organizations (SDOs) like the ISO operate on a 12-24 month timeline. This deliberate, consensus-based process is too slow to keep pace with the rapid evolution of AI technology, creating a governance gap that requires more agile, iterative approaches.

Japan’s AI Promotion Act is intentionally light-touch, lacking penalties or risk tiers, because the country views AI as a critical solution to its severe labor shortage. Policymakers concluded that most AI-related harms are already covered by existing laws, making new, heavy-handed regulation counterproductive to adoption.

Engineering problems have clear outcomes that can be reverse-engineered. Most policy challenges are design problems, requiring exploration and iteration to find a solution. Framing policy this way allows for flexibility and user-centered solutions rather than rigid compliance.

To gain corporate buy-in for its security agenda, Japan's government combines protective measures like export controls with promotional incentives like R&D support. This 'run faster' strategy reframes national security regulations from being a restrictive cost into a direct opportunity for innovation and expansion in strategic sectors.

A more effective policymaking model is "outcomes-driven legislation," where lawmakers define a goal and give agencies freedom to achieve it. The current model, which specifies every rule, locks agencies into rigid, inefficient processes, especially when legislators disagree on the ultimate goal.