Decision authority: when should AI decide autonomously vs. human judgment in the loop? Organizations need this framework now, while decisions are still supervised, so it's ready before AI exceeds the humans overseeing it.
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Every organization has shadow generative AI. Transition from shadow to sanctioned requires three things: acceptable use policy, workforce training, governance that enables rather than bans.
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Healthcare: governance is life-or-death. Clinical AI validation, patient data governance, regulatory compliance under TGA, FDA, EMA aren't optional. And workforce augmentation must be positioned as enhancement, never replacement.
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Nvidia has shipped the first commercially licensed surgical AI brain to robot makers. Jazz Pharmaceuticals has committed up to $2.46 billion and Merck up to $510 million to two AI antibody platforms. BARDA has closed its window on AI antivirals. The substrate of medicine has been quietly outsourced.
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Financial services is regulation-hardened—strong on governance. But workforce enablement lags. Non-technical staff in relationship management and compliance aren't equipped for AI-assisted workflows.
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AI strategies fail at transitions between capabilities. Scanning insights that never become experiments. Experiments that never survive governance. Governed tools that never reach prepared users. Identifying which handoff is broken is the fastest path to fixing it.
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Qualcomm shipped the chip, Google the operating system with Gemini, Snap a standalone pair at $2,195, Acer the cheap end, and Meta the proof people wear them. The AI-glasses computer has been assembled, and the layer that decides what your glasses recognize belongs to a handful of chip and OS firms.
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Pilot purgatory: the team that builds experiments well doesn't know how to hand them to the team governing production. The experiment succeeds. The governance gate kills it. Understanding which handoff fails is the key.
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Stop debating. Start with 90 days: audit AI usage and establish governance baseline (Days 1-30). Launch two pilots with kill criteria (Days 31-60). Embed measurement and board reporting (Days 61-90).
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Board members asking about AI want three things: risk if we do nothing, risk if we act, how we're governing it. Structure around these three questions and bring data, not borrowed frameworks.
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