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English(EN) Why Your AI Center Of Excellence Should Get Smaller As AI Gets Bigger

人工智能卓越中心必须将重点从用例转移到业务价值

麦肯锡的数据显示,大型公司越来越多地在整个运营中部署人工智能,88%的公司至少在一个业务职能中使用人工智能,44%的公司将其推广到整个企业。然而,财务回报并未跟上步伐,只有6%的组织在人工智能采用方面取得了高绩效。文章认为,传统的人工智能卓越中心(AI CoE)需要从人才库转变为业务价值的促进者,专注于决策、标准和问责制,而不仅仅是关注用例。 AI

影响 人工智能卓越中心需要从管理人才转向关注决策和业务价值,以确保人工智能投资产生财务回报。

排序理由 文章根据行业趋势和调查数据,就人工智能卓越中心应如何发展提出了观点。

在 Forbes — Innovation 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

人工智能卓越中心必须将重点从用例转移到业务价值

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Commentary
文章根据行业趋势和调查数据,就人工智能卓越中心应如何发展提出了观点。
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
product, opinion
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
1 days old
Coverage has settled into its steady-state source set.

完整方法见我们的编辑标准。

报道来源 [1]

  1. Forbes — Innovation TIER_1 English(EN) · Igor Rikalo, Forbes Councils Member ·

    为什么随着人工智能的壮大,您的人工智能卓越中心应该缩小

    Large companies aren't lacking effective ideas for using AI. Rather, they lack a reliable way to transform those ideas into business value.