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Making AI Work
The AI Operating Playbook for Business Results
Your company has AI everywhere. The business results are somewhere else. Making AI Work draws from practical enterprise projects to help readers design, improve, and optimize workflows, review outputs, and prove tangible business value.
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About
About the Book
Your company has AI everywhere. The business results are somewhere else.
Your teams bought more licenses, ran more pilots, and built more impressive demos. After every review, the same question remains: Where is the AI value?
Making AI Work answers that question through lessons from real enterprise projects, including the ones that stalled. It also looks into how Microsoft, the company behind Copilot, moved its own AI from isolated experiments into production deployment.
The book is organized around the key questions companies face as they put AI to work:
- Why work needs to be redesigned before more AI agents are added
- Which work deserves automation and which does not
- Which five assets an agent needs before taking on real work
- Who checks the output, and how to catch errors that look right
- How to tell when a workflow is ready and prove its value
- What to do when customers stop searching and start asking AI
You can buy AI tools. This is the operating playbook for getting business results from them.
Author
About the Author
Weiwei Hu
Weiwei Hu leads big data, analytics, and AI transformation at a Fortune-50 technology company, where her teams took AI from experimentation to Agentic AI workflows enablement. She chairs a 3,000+ member data science community, and writes about making AI practical, AI operating models, and the human side of technology. She is the author of Generative Engine Optimization (GEO).
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