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References & Bibliography

Complete research sources for Why AI Fails: The Leadership Discipline Behind the 5% Who Succeed

60 sources across academic research, management consulting, and technology industry analysis. Formatted per the Chicago Manual of Style, 17th Edition.

Section 1:Books

  • Agrawal, Ajay, Joshua Gans, and Avi Goldfarb. Prediction Machines: The Simple Economics of Artificial Intelligence. Boston: Harvard Business Review Press, 2018.

  • Iansiti, Marco, and Karim R. Lakhani. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Boston: Harvard Business Review Press, 2020.

  • Lee, Kai-Fu. AI Superpowers: China, Silicon Valley, and the New World Order. Boston: Houghton Mifflin Harcourt, 2018.

  • Minsky, Hyman P. Stabilizing an Unstable Economy. New Haven: Yale University Press, 1986.

  • Drucker, Peter F. The Practice of Management. New York: Harper & Brothers, 1954.

Section 2:Academic Research & Journals

MIT Research

MIT Initiative on the Digital Economy

  • MIT Initiative on the Digital Economy. Research on organizational AI adoption patterns and digital transformation. Multiple studies, 2022–2025.

    https://ide.mit.edu/
  • MIT Sloan School of Management. Research on learning curves and knowledge management in AI adoption. Multiple faculty publications, 2023–2025.

    https://mitsloan.mit.edu/

MIT Project NANDA

RAND Corporation

  • Ryseff, James, Brandon De Bruhl, and Sydne J. Newberry. "The Root Causes of Failure for Artificial Intelligence Projects and How They Can Succeed: Avoiding the Anti-Patterns of AI." RAND Corporation, 2024. RR-A2680-1. Based on interviews with 65 data scientists and engineers.

    https://www.rand.org/pubs/research_reports/RRA2680-1.html

Harvard Research

  • Harvard Business Review. "AI-First Leadership: Embracing the Future of Work." Harvard Business Impact, 2025.

    https://www.harvardbusiness.org/insight/ai-first-leadership-embracing-the-future-of-work/
  • Harvard Business School. "Competing in the Age of AI." Digital Data Design Institute at Harvard (D^3), 2020–2024. Research by Karim R. Lakhani, Tsedal Neeley, and Marco Iansiti on large-scale transformations and coalition dynamics.

    https://d3.harvard.edu/
  • Harvard Business Review. "6 Ways AI Changed Business in 2024, According to Executives." Harvard Business Review, January 2025.

    https://hbr.org/
  • Harvard Business School. Research on enterprise AI deployment scaling patterns, failure modes, and success factors. D^3 Institute Working Papers, 2023–2024.

    https://d3.harvard.edu/
  • Harvard Business School. Research on organizational learning and AI capability development. Multiple faculty publications, 2022–2025.

    https://www.hbs.edu/

Stanford Research

  • Stanford University Human-Centered AI Institute (HAI). "Artificial Intelligence Index Report 2024." Stanford University, April 2024.

    https://aiindex.stanford.edu/
  • Stanford University. AI implementation research and pattern analysis through the Stanford Digital Economy Lab. Multiple studies, 2023–2025.

    https://digitaleconomy.stanford.edu/

Center for Creative Leadership

  • Center for Creative Leadership. Research on AI leadership competencies and organizational transformation. Multiple publications, 2023–2025.

    https://www.ccl.org/

Stanford Medicine

  • Stanford Medicine. Stanford Medicine AI Program: clinical AI implementation research and outcomes tracking. Stanford University School of Medicine, 2022–2025.

    https://med.stanford.edu/ai.html

Section 3:Management Consulting Reports

McKinsey & Company

IBM Institute for Business Value

Boston Consulting Group (BCG)

Deloitte Insights

PricewaterhouseCoopers (PwC)

Accenture

Section 4:Technology Industry Research

Gartner

Forrester Research

IDC (International Data Corporation)

Section 5:Financial Institutions & Venture Capital

Bessemer Venture Partners

  • Bessemer Venture Partners. "The AI Upskilling Guide for Executives." Bessemer Venture Partners, 2025.

    https://www.bvp.com/

Section 6:White Papers & Technical Documents

Government & Standards

Industry Associations

  • World Economic Forum. AI reports and transformation insights. Multiple publications, 2023–2025.

    https://www.weforum.org/
  • IEEE (Institute of Electrical and Electronics Engineers). Standards and research on AI ethics and implementation. Multiple publications, 2023–2025.

    https://www.ieee.org/
  • ACM (Association for Computing Machinery). Publications on AI systems and computing. Multiple papers, 2023–2025.

    https://www.acm.org/

Section 7:News & Media

Business Publications

  • Fortune Magazine. References to Fortune 500 companies and industry analysis. Various articles, 2023–2025.

    https://fortune.com/

Technology Media

  • TechCrunch. Secondary source for technology industry news and analysis. Various articles, 2024–2025.

    https://techcrunch.com/

Explore the Research in Context

These sources underpin the Seven Pillar AI Adoption Framework and the practical leadership strategies detailed throughout the book.

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