Dr. David Swanagon

Chief Technology Officer, Artificial Intelligence at Machine Leadership

Dallas-Fort Worth Metroplex, United States

About Dr. David Swanagon

Dr. David Swanagon is Chief Technology Officer, Artificial Intelligence at Machine Leadership. Location: Dallas-Fort Worth Metroplex, United States.

I am a senior transformation leader for O&G, Manufacturing, Cyber Security, and Technology firms, a patent developer, data scientist, and professor. My research interests focus on the intersection between human capital, information theory, and applied mathematics. In my advisory engagements, I help organizations improve their AI adoption and workforce readiness, while optimizing the enterprise technology roadmap and governance. I specialize in generative AI, domain adapted LLMs, agentic AI, RAG architectures, and competency development. I have worked as a senior leader or consultant for multiple Fortune organizations, which included assignments in the US, Middle East, India, and Asia Pacific. My background includes executive and director level leadership roles at Ericsson, Saudi Aramco, and PPG. I have also served as a senior advisor for Trellix Cyber Security, Petro Rabigh Chemical, Luberef Base Oil, The Cosmopolitan of Las Vegas, and Venetian and Palazzo Resorts. Across these roles, I partnered closely with executive leadership teams on AI strategy, organizational design, technology optimization, and leadership effectiveness. I am the Editor in Chief of the Machine Leadership Journal and the creator of Relational Lysis Mathematics, a deterministic geometric framework that resolves intrinsic structure in complex systems at the point of ingestion, enabling exact reconstruction and computation without the need to operate on raw data. The work spans mathematics, theoretical physics, and computing infrastructure, with formal results addressing foundational limits in information theory, memory-bound architectures, and large-scale computation. I have proofs on the Yang Mills Mass Gap and Three Body problem currently under peer review. I also serve as a part-time Professor, teaching analytics and organizational behavior. My work has been published by leading academic and industry institutions (Columbia, Vanderbilt, CapGemini, CIPD, Forbes), and I regularly contribute to global forums on analytics, leadership, and transformation. I am open to senior advisory, board, and executive roles where enterprise judgment, AI fluency, and transformation experience are required.

Skills

  • Generative AI
  • Agentic AI Development
  • Theoretical Physics

Additional experience

  • Industry in Residence, Artificial Intelligence

    James Cook University

    Started January 2026

Education

  • Doctor of Education - EdD, Vanderbilt Peabody College
  • Master of Arts (M.A.), Harvard University