The ‘Governance Gap’: Nick Curum Warns of Unsupervised AI Decision-Making

In a recent LinkedIn post, Nick Curum discusses the critical and often overlooked challenge of corporate governance in the age of artificial intelligence, warning that companies may be unknowingly empowering autonomous executives without adequate oversight. Curum highlights a significant shift from traditional decision-making processes to those governed by opaque system parameters.

Curum begins by framing the issue starkly: “Your board thinks it just approved a new AI strategy. In reality, you just hired an autonomous executive—and left it completely unsupervised.” This provocative statement sets the stage for his analysis of how AI is fundamentally altering corporate governance.

The Shift from Visibility to Opacity

Traditionally, corporate governance has been built on a foundation of visibility. Decisions were made through human deliberation in boardrooms, debated in committees, documented meticulously, and recorded in official minutes. However, as Curum points out, the implementation of AI systems disrupts this established model.

“But the moment an AI system goes live, that visibility vanishes,” Curum writes. He elaborates on how decision-making functions previously handled by people are now embedded within system parameters. These include dynamic pricing thresholds, automated approval rules, and vendor selection logic that operate at a scale and speed far beyond human capacity for real-time review.

“For decades, corporate governance has relied on visibility. Decisions happened in boardrooms. They were debated in committees, documented in memos, and recorded in minutes.”

The Real-World Impact of Unsupervised AI

Curum emphasizes the tangible consequences of this shift. He provides examples of how an AI optimized for revenue might inadvertently erode profit margins by prioritizing volume, or how a procurement AI could approve suppliers meeting numerical targets but failing crucial compliance checks. These micro-decisions, made by algorithms thousands of times over, can have significant strategic implications.

“Months later, these algorithms are making thousands of micro-decisions at scale that used to require executive sign-off. And nobody is reviewing them,” Curum states. He attributes this lack of oversight not to malicious intent, but to the nature of automated actions, which do not typically appear on an agenda as distinct decisions requiring explicit board approval. The board approves the strategy, but the algorithm dictates the execution.

Identifying and Addressing the ‘Governance Gap’

This disconnect, which Curum terms the “Governance Gap,” is the central focus of his current work. He argues that if no one is explicitly responsible for setting or monitoring the operational thresholds of AI systems, the system itself effectively owns the decision-making outcome.

“If nobody owns the threshold, the system owns the decision.”

To address this critical issue, Curum announces a new initiative through his newsletter, “First Output.” Starting this week, he is making premium resources related to governance, compliance, and AI strategy available for free. This includes a breakdown of why the shift from ‘meetings to parameters’ is a significant blind spot, a framework for mapping the governance gap within an organization, and key questions to expose hidden AI decisions.

A Call to Action for Leaders

Curum urges business leaders to recognize that this unsupervised decision-making is likely already occurring within their organizations. He positions his free resources as a vital tool for those responsible for company strategy and governance to identify and mitigate these risks.

“This is the ‘Governance Gap.’ And it’s exactly what we are tackling in First Output.”

By offering these insights and tools, Nick Curum aims to equip businesses with the knowledge and frameworks needed to bridge the governance gap created by the rapid integration of AI, ensuring that strategic intent is aligned with algorithmic execution.