The publication of Working Paper No. 1 of the GTMGO Canon, titled 'Engineering Trust: Why the AI Economy May Require a New Executive Management Discipline,' marks a significant step in rethinking organizational governance in the age of artificial intelligence. Released on July 6, 2026, the paper argues that while enterprises have excelled in customer acquisition, digital platforms, and operational efficiency, governance remains fragmented across independent functional disciplines. This gap, termed the Governance Velocity Gap™, creates challenges as innovation outpaces the evolution of governance structures.
The paper introduces Go-To-Market Governance (GTMGO) as a proposed executive management discipline designed to engineer governance into growth proactively, rather than retroactively applying it after issues arise. Key concepts include Governance Engineering as the scientific methodology, the Go-To-Market Governance Officer as the accountable executive, and GTMGO Thermodynamic-Friction™, which describes organizational resistance when governance lags behind change. The framework draws insights from aviation, legal practice, professional sports, entertainment, broadcasting, healthcare, privacy, cybersecurity, and enterprise leadership, synthesized through management science and systems thinking.
The GTMGO Canon is being released as a series of Working Papers to allow for iterative refinement through disciplined inquiry and practical application. The Version 1.0 Freeze preserves the foundational architecture while inviting constructive feedback from executives, directors, governance professionals, technologists, and academics. Feedback will be documented via the GTMGO Research Notes process and considered for future papers without altering the historical integrity of Version 1.0.
Peter Q. John, JD, MBA, the founder of the GTMGO Canon, emphasizes that the paper does not restate existing legal or regulatory frameworks but instead proposes recurring engineering principles across trusted professions. The initiative aims to answer whether the AI economy, which has transformed how organizations innovate, also requires a new approach to governing that innovation. The full paper is expected to be released in the coming weeks.
