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Governance failures rarely begin with a lack of information. They begin when boards receive distorted, filtered, delayed, or incomplete signals and mistake them for reality. Effective governance depends on signal quality, escalation integrity, and decision-making processes—not just compliance.
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AI in healthcare is not a product to approve but a system to govern. This ISI paper examines the failure of “approve and go” models and argues that boards must oversee decision quality and require vendors to share clinical risk alongside clinicians.
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AI in healthcare is not a technology problem — it is a governance system challenge. This paper introduces the Strategy Governance System, showing why boards must move beyond approval to govern decision quality, signal integrity, and adaptive oversight.
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Micromanagement is not a leadership flaw. It is a governance failure. When control concentrates decision-making, organisations become fragile. This paper examines how micromanagement signals breakdowns in decision architecture, capability, and system integrity.
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Boards rely on dashboards—but risk emerges before metrics move. This paper examines how structured floor engagement functions as a governance sensing system, improving signal integrity, cultural oversight, and early risk detection.
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Artificial intelligence is often presented as a transformative solution. In practice, AI frequently acts as a stress test for organisational systems. When deployed in complex environments such as healthcare, AI exposes weaknesses in data integrity, workflows, governance, and system readiness.
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Healthcare AI, sustainability, and net zero are not technical challenges with tidy solutions. They are wicked problems—complex, evolving, and resistant to linear control. This paper sets out an integrity-based governance architecture for holding risk, accountability, and adaptation under pressure.