5 books on AI for Project Management [PDF]

October 23, 2024

These books are covering various aspects of AI's role in automating project workflows, enhancing team collaboration and improving decision-making.

1. The AI Revolution in Project Management: Unlocking Success Secrets with AI
2024 by Peter F. Schindler



"The AI Revolution in Project Management: Unlocking Success Secrets with AI" delves into the profound impact of artificial intelligence on reshaping project management practices. Authored by Peter F. Schindler, this book explores how AI can revolutionize project efficiency, streamline operations across both traditional and agile frameworks and surmount conventional hurdles. It serves as an indispensable resource for decision-makers eager to harness AI's potential for driving profitable advancements in project execution, offering practical insights, strategies and industry case studies. By providing a comprehensive guide to integrating AI into project management, this book equips professionals with the knowledge to navigate and capitalize on technological advancements in today's dynamic business environment. Ideal for those seeking to stay competitive, it empowers readers to leverage AI effectively, turning challenges into opportunities for unprecedented project success.
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2. Innovation Project Management: Methods, Case Studies, and Tools for Managing Innovation Projects
2022 by Harold Kerzner



"Innovation Project Management" equips both students and seasoned professionals with the essential tools, methodologies and performance metrics necessary for the effective management of innovation-driven projects. This comprehensive resource introduces value-focused innovation project management metrics and offers guidance on establishing a robust metrics management program. Authored by a highly knowledgeable expert, the book takes a holistic view of innovation, prompting a reevaluation of traditional project management approaches and advocating for a specialized approach to innovation project management. Key concepts covered in "Innovation Project Management" encompass a range of perspectives, including continuous versus discontinuous innovation, incremental versus radical innovation, the nuanced distinctions within innovation and the differentiation between incremental innovation and new product development. Additionally, it delves into advanced topics like leveraging AI, identifying core competencies through techniques such as SWOT analysis and the use of agreements like nondisclosure, secrecy and confidentiality agreements to safeguard innovative endeavors.
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3. Project Management Next Generation: The Pillars for Organizational Excellence
2022 by Harold Kerzner, Al Zeitoun, Ricardo Viana Vargas



"In 'Project Management Next Generation: The Pillars for Organizational Excellence,' a distinguished group of project management experts offers an in-depth exploration of project management integration within diverse organizational settings. This book delves into ten pivotal pillars of project management, essential for the evolving needs of companies, including the role of AI. It compiles insights from influential figures and trailblazers in the industry, providing a well-rounded blend of hands-on experience across various programs, projects and transformative endeavors. This resource is indispensable for practicing project managers seeking practical guidance, accompanied by insightful case studies enriched with discussion prompts and teaching materials. These materials encompass PowerPoint lecture slides and a comprehensive Instructor's Manual, accessible through the companion website. In addition to insights from prominent commercial organizations worldwide regarding the future of the project management field, readers will find comprehensive introductions to project management as a strategic competence and the cultivation of a corporate project management culture."
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4. Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects
2020 by Neal Fishman, Cole Stryker



"Smarter Data Science: Succeeding with Enterprise-Grade Data and AI Projects" unveils the path to making data science an efficient, reliable tool that empowers business professionals to extract maximum value from their data. Enterprise-level data and AI initiatives often suffer from fragmentation, inadequate planning, isolation and an inability to adapt to evolving business needs, leading to their high failure rates. This book offers a precise roadmap to sidestep these costly pitfalls. Data science is no longer the exclusive domain of data scientists; it has become a practical resource for business professionals, including managers, directors, IT leaders and analysts. To maintain a competitive edge, organizations must broaden their utilization of data science capabilities and "Smarter Data Science" equips them to achieve their ambitions in enterprise-level data projects and AI endeavors. It serves as a comprehensive guide for establishing a robust information architecture program that facilitates sustainable and scalable AI implementations. By mastering data management, organizations can transform their data science initiatives into fully scalable functions that are both prescriptive and reproducible. Armed with an understanding of data science fundamentals, practitioners are empowered to lead their organizations in the successful development and deployment of viable AI solutions.
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5. Succeeding with AI: How to make AI work for your business
2020 by Veljko Krunic



"Succeeding with AI" presents a structured framework for strategically planning and executing cost-efficient AI initiatives that yield tangible business benefits. Drawing from the author's extensive experience with startups, established enterprises and Fortune 500 companies, this pragmatic guide unveils invaluable insights that will guide you in establishing clear, attainable objectives. Inside, you'll master a replicable process to optimize the productivity of data scientists and implement performance metrics to maintain project alignment and resilience. Amid the current surge of AI projects, encompassing organizations of all sizes and substantial investments in software, developers and data science expertise, the book addresses a critical issue: many AI endeavors emphasize technology while neglecting actionable business outcomes, resulting in haphazard results and wasted resources. "Succeeding with AI" provides a blueprint for AI initiatives to ensure predictability, success and profitability, offering practical strategies for managing data science initiatives that are not only cost-effective but also tightly aligned with essential business objectives.
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