Advancing Responsible AI Innovation A Playbook 2025

Design resilient responsible AI processes for business continuityPlay 3 Resilience is needed to future-proof organizations’ AI strategies and their governance, ensuring their adaptability to AI convergence with other technologies,29 emerging AI architectures, models and capabilities, and regulatory shifts. Organizations must also embed resilience, ensuring novel risks and opportunities are tackled as they arise. Organization leaders Key roadblocks that arise within the organization Problems in interpreting how current regulations affect AI Ambiguity in the interpretation of AI regulations, creating uncertainty among companies about how to invest in responsible AI Actions for organization leaders –Invest in strategic foresight: Reduce uncertainties with methodological approaches, such as: –Horizon scanning: A structured evidence- gathering process that explores the strategic environment for early signals of change.30 –External engagement: With regulators, standards and norms-making bodies to anticipate evolving policy directions, and with industry, academia and civil society to stay abreast of technological and societal developments. –Scenario planning: Methods that prompt organizations and individuals to look beyond their assumptions of the future. –Adopt a resiliency framework: Prepare for unknown unknowns, including through adopting a resiliency framework that wraps around risk management: –Contingency planning: Identify each system that is critical to safety, mission, business, and security31 and which, if impacted, could pose significant damage to the organization, its offerings, or the public. Prepare business continuity and contingency plans. –Knowledge sharing: Prioritize multi- directional knowledge sharing (e.g. incident reporting or policy changes) that capture evolving AI uses, risks, and opportunities. However, balance policy adaptation frequency with predictability to enable adherence. –Balance global consistency and local responsiveness: Multinational organizations must anchor AI governance in non- negotiable global principles while balancing local adaptation that reflects cultural and regulatory realities. –Prepare for fragmentation but invest in interoperability: Organizations operating across jurisdictions should harmonize multiple AI risk frameworks by mapping common and competing elements to a unified master control set and crosswalk customized to the organization.32 Organizations can enhance interoperability by engaging in international forums like the International Standards Organization (ISO), adopting broadly recognized standards and sharing best practices (see Play 5). Advancing Responsible AI Innovation: A Playbook 15