Technical teams build capabilities but often lack business context. Business leaders demand solutions but rarely fully understand technical constraints. Data teams control the raw material but are often disconnected from both. And when things go sideways-as they often do-the fingerpointing begins.
This isn't a minor coordination issue; it's a fundamental design flaw in how organizations approach artificial intelligence (AI)-and a fundamental failure in how we create, capture, connect, and communicate its value. It is also a failure in our underlying understanding of how to get value from AI.
The Values of Artificial Intelligence shows how to fix this flaw-not through reorganization or the usual buzzwords, but through frameworks that make value creation truly broadly-owned when it succeeds and accountable when it fails.
The tools in these pages are practical, tested, and deeply human-designed to bridge what technology delivers with what people ultimately value.
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