The rapid advancement of artificial intelligence has created a critical challenge for organizations: how to maintain trust while accelerating innovation. A new working paper proposes a solution through an emerging executive management discipline called Go-To-Market Governance (GTMGO). Published by Peter Q. John, the paper titled 'Engineering Trust: Why the AI Economy May Require a New Executive Management Discipline' argues that traditional governance structures, organized around independent functional disciplines, are no longer sufficient in an era where innovation outpaces governance.
Working Paper No. 1 of the GTMGO Canon establishes the foundational concepts of this discipline, including Governance Engineering as the scientific methodology, and the Go-To-Market Governance Officer as the executive accountable for achieving Trusted Growth. The paper introduces two key metrics: the Governance Velocity Gap™, which measures the lag between innovation and governance, and GTMGO Thermodynamic-Friction™, which describes the organizational resistance that builds when governance evolves slowly. These concepts are designed to help organizations engineer governance proactively rather than retroactively.
The paper draws insights from multiple regulated industries and professions, including aviation, legal practice, professional sports, entertainment, healthcare, and cybersecurity. By synthesizing management science, systems thinking, and engineering methodology, the GTMGO Canon proposes a unified discipline applicable to AI-enabled enterprises. The author emphasizes that this is not a restatement of existing legal or compliance frameworks but a new approach to embedding governance into growth strategies.
The GTMGO Canon is being released as a series of working papers to encourage iterative refinement through practical application and scholarly discussion. The Version 1.0 Freeze preserves the core architecture while inviting feedback from executives, directors, governance professionals, and academics. Constructive observations will be documented in GTMGO Research Notes and considered for future papers, ensuring the discipline evolves through disciplined inquiry rather than declaration alone.
As organizations face increasing pressure to innovate rapidly, the question posed by the paper is timely: if the AI economy has transformed how organizations innovate, is it time to rethink how they govern innovation? The GTMGO framework offers a potential pathway to align growth with trust, making it a significant development for executives and governance professionals navigating the complexities of the AI era.
For further details, the working paper is available at LinkedIn.
