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Practical perspectives on AI governance, trusted data, and enterprise transformation.
Responsible AI
One technology, several regulatory models. The question is no longer whether artificial intelligence will be governed. The question is how organizations can keep pace as different jurisdictions pursue different approaches. Europe has enacted a comprehensive risk-based law. The United States relies on executive policy, existing regulators and increasingly active states. Canada is continuing to shape […]
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AI Fundamentals
ChatGPT looked sudden. It wasn’t. When ChatGPT was released as a public research preview on November 30, 2022, generative AI appeared to arrive almost overnight. Within weeks, people were using a conversational interface to draft, summarize, translate, code and answer questions. For many executives, this was the moment artificial intelligence moved from a specialist technology […]
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Responsible AI
A dispenser that did not see every hand. In 2017, a short video circulated widely online. An automatic soap dispenser responded to a lighter-skinned hand but failed to activate for a darker-skinned hand. When a white paper towel was placed over the same hand, the dispenser worked. The device was quickly labelled the “racist” soap […]
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AI Fundamentals
The autonomy gap between perception and reality. A modern vehicle can steer, brake, change lanes, follow navigation and park itself. To a passenger, that can feel close to autonomy. Under the formal responsibility model, however, many of these systems remain driver assistance because the person behind the wheel must continuously supervise the road and take […]
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Enterprise Data
AI has a context problem. Enterprises rarely suffer from a shortage of information. They suffer from a shortage of reliable context. A customer table may contain millions of records, but that does not tell an analyst which field represents the legal customer, which source is authoritative, how the values were transformed, or whether the data […]
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Strategy & Transformation
A convincing demo can still be a failed transformation. AI creates an unusual management problem: it is often easy to demonstrate and difficult to operationalize. A small team can produce a polished prototype in weeks using curated data, manual workarounds and a limited group of enthusiastic users. The demonstration may be technically impressive and still […]
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