Advancing Responsible AI Innovation A Playbook 2025

Play 9 Increase responsible AI literacy and workforce transition opportunities As organizations reinvent themselves around AI, fostering responsible AI literacy and cross-disciplinary skills across the enterprise is critical to prepare for cultural change, capability-building and talent transformation. For governments, investing in AI education is foundational to a public capable of informed decision-making in AI use and to a pipeline that meets increasing business demand for responsible AI experts. Organization leaders Key roadblocks that arise within the organization Gap between AI use and risk literacy: 53% of the US population reported using a generative AI tool.92 However, only 1% were able to correctly answer all questions regarding basic AI literacy,93 pointing to vulnerabilities for individuals and organizations.  C-suite underestimates worker concerns: 59% of workers express substantial concerns about the impact of generative AI on job security. Yet only 29% of executives assume workers have concerns about job loss.94 This underestimation can lead to underinvestment in literacy and trust-building approaches. Actions for organization leaders –Invest in responsible AI literacy across the organization: Embed literacy regarding AI capabilities, limitations, risks, compliance and ethical considerations into learning and development offerings (see Case study 10). Cross-functional training and change management initiatives are needed to upskill technical and non-technical workers. This can decentralize risk management and enable all employees to be informed users of AI, cognizant of when escalation is needed for support. In the long term, literacy will need to account for evolving AI risks and regulations and for variability in training needs for current AI adopters and an AI-native future workforce. –Enhance literacy specificity with defined policies and tooling: Integrate organizational responsible AI policies and procedures into training programmes. Upskill employees with trainings tailored to approved AI tool use while ensuring transferable skills. –Inform leadership decision-making with employee listening: Define metrics to measure AI adoption, the state of responsible AI practices and trust across the workforce. Then, use those insights to inform workforce transition initiatives. Literacy strategies must reflect and address the employees’ various AI concerns that could hinder AI adoption and responsible use (see Table 3). Establish avenues for ongoing employee input to refine trainings (see Play 1). Advancing Responsible AI Innovation: A Playbook 33