{"product_id":"the-lean-ai-handbook-building-deploying-and-scaling-ai-for-business-value","title":"The Lean AI Handbook: Building, Deploying, and Scaling AI for Business Value","description":"\u003cp\u003e\u003cstrong\u003eA hands-on framework that combines Lean, DataOps, MLOps, and cross functional delivery to ship AI from prototype to production with speed.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eAI projects fail more often, not because the math is hard, but because delivery is. \u003cem\u003eThe Lean AI Handbook \u003c\/em\u003eshows leaders, analysts, and AI builders how to build, deploy, and scale AI that delivers real business value, quickly and reliably using Lean and Agile practices. You'll learn how to streamline the path to production with Product Management, DataOps and MLOps work in small batches, focus on the right metrics, and ship models, agents, and insights that keep delivering after launch.\u003c\/p\u003e\n\u003cp\u003eAs AI investment grows, many programs still stall at pilot purgatory. \u003cem\u003eThe Lean AI Handbook \u003c\/em\u003eoffers a practical People-Process-Tools guide for putting AI into everyday products. Combining Lean and Agile with DataOps and MLOps, it shows you how to remove bottlenecks, build simpler and faster models, and use automation, observability, and feedback loops to scale with confidence. It also covers the last mile, communicating insights clearly, building stakeholder trust, reducing delivery risk, and leading teams that grow with the business.\u003c\/p\u003e\n\u003cp\u003e\u003cspan style=\"color: rgb(252, 34, 34);\"\u003e\u003cstrong\u003eKey Benefits \u0026amp; Topics Covered:\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eOvercome the AI delivery bottleneck: \u003c\/strong\u003eIdentify the reasons for delayed delivery and necessary changes to increase speed.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eApply Lean thinking and Agile building and shipping AI:\u003c\/strong\u003e Work in small batches, learn fast, keep effort aligned with measurable business outcomes.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eUse DataOps as the backbone of Lean AI: \u003c\/strong\u003eAutomate pipelines, make data reliable, and deliver AI at scale with modern continuous delivery focused engineering practices.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaster the last mile from modeling to production: \u003c\/strong\u003eGet your models out of prototype theater and deployed to production where they drive real business decisions and customer value.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eLead high-performing AI engineering teams: \u003c\/strong\u003eScale teams effectively by structuring roles, workflows, and expectations to deliver continuous value to people, processes, and technology.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eShip and monitor models that stay reliable:\u003c\/strong\u003e Use MLOps, observability, and model monitoring to deploy AI safely, catch drift, and minimize blast radius before it erodes customer confidence and damages company brand.\u003c\/p\u003e\n\u003ch3\u003eAbout the Author\u003c\/h3\u003e\n\u003cdiv class=\"a-section a-spacing-small a-padding-small\"\u003e\n\u003cp\u003e\u003cspan class=\"a-text-bold\"\u003eKen Johnston\u003c\/span\u003e\u003cspan\u003e is co-founder of the AiGovOps Foundation, advancing AI governance-as-code for the enterprise. He was CEO of Autonomic.ai and VP of Cloud Platforms and Telematics Development at Ford Motor Company. Previously spent 25 years at Microsoft in senior engineering, data science, and cloud leadership roles, and is a recognized speaker, trainer, and coauthor on software testing and data science.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan class=\"a-text-bold\"\u003eAnkit Srivastava\u003c\/span\u003e\u003cspan\u003e is a Principal Data Science Manager at Microsoft with 15+ years of work experience in business analytics, applied ML, developing generative AI solutions. He has led growth initiatives on Windows 10, and Intune, and now leads work on AI agents. He holds patents in AI\/ML and has published research and contributed to open-source work in differential privacy. Before Microsoft, he worked at organizations such as Sun Microsystems, Qualcomm, and Deloitte.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan class=\"a-text-bold\"\u003eHuibin (Mary) Hu\u003c\/span\u003e\u003cspan\u003e is an experienced data science leader specializing in large-scale experimentation and A\/B testing. She is an Engineering Manager at Etsy and previously worked at Microsoft on client-side experimentation, where she also co-founded the Women in Data Science community to support and connect professionals in the field.\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Pearson Education","offers":[{"title":"Default Title","offer_id":50814241177670,"sku":"9780135582985","price":5023.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/8125FMu0fAL._SL1500.jpg?v=1793084561","url":"https:\/\/cb-india.com\/products\/the-lean-ai-handbook-building-deploying-and-scaling-ai-for-business-value","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}