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Our interviewees also expressed strong skepticism about trusting AI too much, noting that companies are deploying it before it is ready.
At the same time, the recent EY report How boards can lead in a world remade by AI (pdf) expressed the need for boards to adopt transformative rather than incremental thinking about AI. Next level competitive differentiation is expected to come from fundamentally redesigning processes and operating models around AI rather than simply automating existing workflows.
Boards should encourage management to identify where AI can reshape value, reassess its technology risk appetite, and ensure that AI initiatives are tightly linked to strategic outcomes. These initiatives must be implemented responsibly, with governance, ethical oversight, and strong data management to avoid regulatory, operational and reputational risks.
The report also underscores significant implications for talent and workforce strategy and indicates that talent models need to change. Boards should ensure that human capital strategies evolve accordingly, balancing short-term cost savings with long-term organizational capability and social expectations.
Another critical theme is accountability. Despite advances in AI autonomy, responsibility for outcomes remains firmly human. Issues such as bias and inaccurate outputs can expose companies to organizational and reputational risks. Boards must ensure robust governance, clear accountability and transparent risk management practices, converting trust into a competitive differentiator.
Finally, boards themselves must evolve. The EY Enhancing Board Oversight of Technology report (pdf) provides fascinating insight into what chief technology officers are looking for from their boards, where a mix of education, clarity and respect for expertise is seen as best practice. Continuous AI education for directors, deeper collaboration with management and integration of AI considerations across all board discussions are increasingly essential for effective oversight.