Practical AI Guide to Project Management: To Achieve Greater Job Performance and Corporate ROI
Language: English
Published by Independently published, 2025
- Softcover
- New

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- Title
- Practical AI Guide to Project Management: To Achieve Greater Job Performance and Corporate ROI
- Author
- Sunn, Stephan
- Publisher
- Independently published
- Publication year
- 2025
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798268681345
This practical guide addresses a critical reality: artificial intelligence will not replace project managers, but it will fundamentally reshape what success looks like in our field. Drawing from real-world implementations across global markets—from London banks to Singapore fintech startups—the book demonstrates how AI serves as a force multiplier rather than a replacement, amplifying human judgment while automating routine tasks.
The core methodology centers on four key shifts: data-first project planning, predictive analytics for risk management, AI-powered task triaging, and ethical governance frameworks. The authors provide concrete tools and workflows, from using Otter.ai for meeting transcription to implementing machine learning models for budget forecasting. What sets this approach apart is its emphasis on human leadership—teaching teams to work alongside AI while maintaining critical thinking and ethical oversight.
The book's strength lies in its actionable 90-day implementation plans tailored for different career stages, from students to executives. Rather than abstract theory, it offers specific tactics for building AI literacy, managing algorithm aversion among team members, and translating technical capabilities into business value. For professionals navigating this transition, it provides both the strategic framework and practical roadmap needed to thrive in an AI-enhanced workplace.
The core methodology centers on four key shifts: data-first project planning, predictive analytics for risk management, AI-powered task triaging, and ethical governance frameworks. The authors provide concrete tools and workflows, from using Otter.ai for meeting transcription to implementing machine learning models for budget forecasting. What sets this approach apart is its emphasis on human leadership—teaching teams to work alongside AI while maintaining critical thinking and ethical oversight.
The book's strength lies in its actionable 90-day implementation plans tailored for different career stages, from students to executives. Rather than abstract theory, it offers specific tactics for building AI literacy, managing algorithm aversion among team members, and translating technical capabilities into business value. For professionals navigating this transition, it provides both the strategic framework and practical roadmap needed to thrive in an AI-enhanced workplace.
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California Books
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