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AI readiness is no longer only about infrastructure or technology adoption. It increasingly depends on whether people, institutions and public systems have the capability to use AI effectively, responsibly and at scale. AI Readiness Is Larger Than Technology The discussion around national AI readiness often begins with technology. How much computing capacity is available? Which…
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AI can generate a recommendation. Responsibility still requires someone to decide what should happen next. AI systems are becoming increasingly capable of generating recommendations. They can summarize information, identify patterns, rank possibilities, generate alternatives, predict likely outcomes and suggest possible courses of action. These capabilities can significantly improve the speed and scale at which people…
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Access to tools does not demonstrate capability. As AI becomes part of everyday work, meaningful progression requires evidence that people can understand, apply, evaluate and execute with increasing levels of responsibility. Access Is the Starting Point, Not Capability The expansion of access to AI has changed the entry point for learning and work. People can…
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AI can make individual tasks faster. The more important question is what happens to the wider system — its dependencies, decisions and capability requirements — once that task no longer works the same way. Artificial intelligence is increasingly being introduced into everyday work through a familiar promise: make processes faster, reduce repetitive effort, lower costs,…
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AI access is expanding rapidly. The more important question is whether people and institutions can use that access with context, judgment, systems thinking, responsible adoption and effective execution. Artificial intelligence is becoming easier to access. AI systems are increasingly available to individuals, professionals, businesses and institutions. Tools that once required specialist knowledge are becoming easier…