Introduction Artificial intelligence (AI) is transforming the global economy, enabling innovation, growth and social advancement amid heightened technological and geopolitical complexity. Sustainable adoption of AI necessitates an ecosystem of intentionally designed principles, guidelines and practices – collectively referred to as “responsible AI” – to effectively govern the technology for desirable outcomes, as outlined in Table 1.Responsible AI practices are critical to unlocking sustainable innovation, yet significant implementation gaps remain. Responsible AI implementation by businesses matters to both organizations and governmentsTABLE 1 For organizations For governments –Enable business value and competitiveness through reliable and confident AI innovation –Increase adoption through enhanced customer/ consumer confidence in AI-driven products and services –Enhance employee inclusion and retention through trusted AI adoption –Ensure robust risk management to mitigate legal, financial and reputational exposure –Meet stakeholder expectations of innovation that protects privacy and civil liberties –Proactively respond to technological developments such as agentic AI, which depend on comprehensive governance and established trust –Reduce regulatory burden with proactive responsible AI implementation –Reinforce ecosystem partnerships by aligning standards, facilitating interoperability and enabling long-term innovation –Promote economic growth through sustainable AI innovation –Safeguard human rights and freedoms that may be challenged with AI adoption –Increase public trust in digital transformation by ensuring transparency and accountability of organizations implementing AI –Enable inclusive and adaptive policy frameworks built on a foundation of organizational responsible AI maturity –Be globally competitive and secure national objectives (e.g. sovereignty, cybersecurity, energy) –Promote innovation for all by ensuring equitable access to AI benefits across communities –Enhance societal and environmental benefits, especially within critical sectors –Improve delivery of government services with streamlined operations and increased decision-making efficiencies The responsible AI implementation gap Despite increased awareness, responsible AI practices by organizations remain immature. Measured on a four-stage maturity scale, a 2025 survey of 1,500 companies found that 81% remain in the first two early stages of responsible AI. While the number of companies with a stage 3 maturity increased from 14% in 2024 to 19% in 2025, less than 1% of companies are at stage 4 (Figure 1).4 This limited maturity is prevalent across organizations, regions and sectors (Figures 2 and 3). Though the “why” of responsible AI is largely understood, the “how” remains elusive to most organizations. Advancing Responsible AI Innovation: A Playbook 5

Advancing Responsible AI Innovation A Playbook 2025