Canada's 2017 AI strategy was primarily about funding research and commercialization. The new 'AI for All' plan is a comprehensive, whole-of-government approach addressing trust, democracy, literacy, and sovereignty. This evolution shows how AI's perceived impact has broadened from an academic pursuit to a fundamental societal force in just a few years.

India is taking a measured, "no rush" approach to AI governance. The strategy is to first leverage and adapt existing legal frameworks—like the IT Act for deepfakes and data protection laws for privacy—rather than creating new, potentially innovation-stifling AI-specific legislation.

Despite the risk of a fragmented legal landscape, the slow pace of federal AI legislation makes state-level action essential. States are acting as "laboratories of democracy," pioneering regulatory approaches that can later inform a much-needed national framework.

OpenAI is shifting its policy strategy, now supporting state-level regulations like those in Illinois. This marks a move away from waiting for a comprehensive federal standard towards a more practical approach that acknowledges public sentiment and the need to build trust locally.

Federal and state governments are massive customers of technology. Instead of relying solely on legislation, they can use their procurement power to enforce AI safety and ethical standards. By setting strict purchasing requirements, they can compel companies to build more responsible products.

The UK's strategy of criminalizing specific harmful AI outcomes, like non-consensual deepfakes, is more effective than the EU AI Act's approach of regulating model size and development processes. Focusing on harmful outcomes is a more direct way to mitigate societal damage.

A16z advocates for a "gap analysis" approach to AI regulation. Instead of assuming a legal vacuum exists, lawmakers should first examine how existing, technology-neutral laws—like consumer protection or civil rights statutes—already apply to AI harms. New legislation should only target clearly identified gaps.

There is a temptation to create a flurry of AI-specific laws, but most harms from AI (like deepfakes or voice clones) already fall under existing legal categories. Torts like defamation and crimes like fraud provide strong existing remedies.

Expect AI legislation to be a series of targeted, incremental bills rather than one sweeping law. Congress will address specific issues like model transparency and intellectual property while engaging in international diplomacy and observing state-level experiments.