How should organisations prepare for AI regulation before it arrives rather than scrambling after the fact?

Organizations should proactively build internal AI governance frameworks to anticipate regulation, given the ongoing delays and uncertainties in jurisdictions like the UK and EU [1][9][12]. Rather than waiting for comprehensive laws, companies can adopt management-based approaches by establishing risk management systems that include impact assessments, documentation, audits, and continuous monitoring of AI models, data sets, and uses [2]. This preparation aligns with calls for sector-specific guidance under existing rules, such as those from UK regulators on applying current frameworks to AI use cases [6], and helps early adopters gain competitive advantages despite pauses in full implementation [9]. Focusing on strategic, sector-specific compliance—such as developing standards and procurement in areas of comparative advantage—can position organizations ahead of scattered, reactive policies driven by AI's rapid evolution [4][5]. In regions like the EU, prioritizing preparation for high-risk regimes and general-purpose AI rules, even amid de-prioritized elements, reduces scrambling risks [10].