A new working paper proposes a novel executive management discipline called Go-To-Market Governance (GTMGO) to help organizations engineer trust into their growth strategies amid the rapid adoption of artificial intelligence. Published by Peter Q. John, JD, MBA, a communication and compliance executive, Working Paper No. 1 of the GTMGO Canon, titled 'Engineering Trust: Why the AI Economy May Require a New Executive Management Discipline,' argues that traditional governance structures, organized around independent functions, are failing to keep pace with innovation.
The paper introduces the concept of the Governance Velocity Gap™, which describes the lag between innovation and governance, and GTMGO Thermodynamic-Friction™, the organizational resistance that builds when governance evolves more slowly than enterprise change. Rather than rehashing existing compliance frameworks, the paper proposes recurring engineering principles drawn from fields such as aviation, legal practice, professional sports labor relations, entertainment, broadcasting, healthcare-adjacent governance, privacy, cybersecurity, and enterprise leadership. These observations are synthesized through management science, systems thinking, and engineering methodology to create a unified governance discipline for AI-enabled enterprises.
The GTMGO Canon is being released as a series of working papers to encourage disciplined inquiry and refinement. The Version 1.0 Freeze preserves the foundational architecture, including the role of a Go-To-Market Governance Officer responsible for applying Governance Engineering to achieve Trusted Growth. The paper emphasizes that governance must be built into growth processes, not applied after the fact, to maintain trust as innovation accelerates.
Executives, directors, governance professionals, lawyers, technologists, engineers, cybersecurity practitioners, privacy leaders, healthcare administrators, financial institutions, regulators, researchers, and academics are invited to review the paper and provide feedback through a Research Notes process. The paper, to be released in the coming weeks, aims to spark dialogue across industries on how to preserve trust in the AI economy.
For more information, visit the author's LinkedIn profile.
