Leading Enterprise AI Programs

Optimize AI Teams for Value Creation
1. Auflage 2026
ISBN: 978-1-3986-2319-4
Verlag: Kogan Page

Buch, Englisch, 296 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 667 g

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.

Autoren/Hrsg.

Bangert, Patrick

Fachgebiete

• Technische Wissenschaften Technik Allgemein Technik: Allgemeines
• Wirtschaftswissenschaften Betriebswirtschaft Management Unternehmensorganisation & Entwicklungsstrategien
• Wirtschaftswissenschaften Betriebswirtschaft Management Projektmanagement
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme

Inhaltsverzeichnis

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

Über Autor(innen)

Bangert, Patrick
Patrick Bangert is an experienced technology executive who has led AI and machine learning teams and programs for over two decades. He was named a Top 10 Influential Leader in AI and Big Data by CIOLook Magazine and is currently VP and Chief of AI at Occidental Petroleum. He was previously the SVP 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.

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.