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Leading Enterprise AI Programs - Patrick Bangert

Leading Enterprise AI Programs

Optimize AI Teams for Value Creation

(Autor)

Buch | Hardcover
264 Seiten
2026
Kogan Page Ltd (Verlag)
978-1-3986-2321-7 (ISBN)
CHF 97,75 inkl. MwSt
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Develop AI solutions that create real business value with this guide to leading a successful enterprise AI program.
Companies everywhere are investing significant resources into building AI products and services that they hope will transform their business. To deliver real results, AI and data leaders need to build a strong business-oriented enterprise AI program.

Leading Enterprise AI Programs is an essential guide to establishing and directing an agile, ethical and business-focussed AI strategy and program for the whole enterprise. It provides leaders with guidance on operating a portfolio of use cases delivering effective and lasting business value. You will learn how to set up the best operating model for an organization's goals and targets, find and prioritize the right use cases for the business, and build a community of citizen data scientists. This book explains how AI can drive business success through focusing on users and interfaces, with clarity on the challenges to be solved as the primary drivers of value.

This book provides practical frameworks and actionable advice to help leaders set up a program and project portfolio, assess costs and benefits and embed AI into an organization's value generation ecosystem. With real-world examples, Leading Enterprise AI Programs helps leaders steer an enterprise AI team to lasting success.

Patrick Bangert is an experienced technology executive who has led AI and machine learning teams and programs for over two decades. He is currently VP and Chief of AI at Occidental Petroleum. He was previously the VP of AI for Samsung SDS, the founder of algorithmica technologies and the SVP of Data, Analytics, AI at Searce. He lives in San Francisco, CA.

Chapter - 00: Introduction


Section - ONE: The optimal structure of the team for success


Chapter - 01: Setting up the right operational model
Chapter - 02: Building a community of citizen data scientists
Chapter - 03: Identifying and prioritizing uses cases
Chapter - 04: Creating common project platforms and organizational programs
Chapter - 05: Managing risk and a portfolio of projects


Section - TWO: Embedding the enterprise AI program into the value stream


Chapter - 06: Establishing a project charter and implementing design thinking
Chapter - 07: Project management and agile scrum
Chapter - 08: User experiences and interfaces
Chapter - 09: Change management and adoption
Chapter - 10: Managing costs and rewards


Section - THREE: Dependencies on other teams, companies and society


Chapter - 11: Ensuring high quality data
Chapter - 12: Conducting AI responsibly and ethically
Chapter - 13: Governing and maintaining AI models and applications over the long-term
Chapter - 14: Managing vendors and encouraging open innovation
Chapter - 15: Lifelong learning for the team and company
Chapter - 16: Further reading

Erscheint lt. Verlag 3.2.2026
Verlagsort London
Sprache englisch
Maße 156 x 234 mm
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Wirtschaft Betriebswirtschaft / Management Projektmanagement
Wirtschaft Betriebswirtschaft / Management Unternehmensführung / Management
ISBN-10 1-3986-2321-0 / 1398623210
ISBN-13 978-1-3986-2321-7 / 9781398623217
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
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