Energy and utility companies are increasingly using AI to transform many aspects of their operations. Common use cases include strengthening cyber and infrastructure defenses, making engineering knowledge easier to find, and reducing the time that employees spend assembling information. Realizing this value requires the same discipline that utilities apply to other consequential technologies, including processes to define operating boundaries, validate performance, and ensure accountability.
For an organization responsible for critical energy infrastructure, model capability is only one part of the purchasing decision. Where AI runs, what information it can access, and what authority it receives determine which workloads a utility can responsibly put into production.
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本文节选自 Cohere 的《AI for utilities requires capability and control》，原文链接：https://cohere.com/blog/ai-for-utilities-requires-capability-and-control
