A senior executive from a Fortune 50 company described the ongoing struggle with her AI committee. Lawyers Should Lead AI Governance. Meetings would last hours, discussions would swirl, yet no concrete decisions would emerge. The problem didn’t lie with the people involved, the tools at their disposal, or the data being analyzed. The issue was the structure of the committee itself.
AI strategy committees are often created to appear proactive. They get added to board agendas and detailed in presentation decks. However, a survey by Sedgwick reveals that while 70% of Fortune 500 companies have these committees in place, only 14% feel fully prepared for AI deployment. This highlights a significant gap between the intention behind these groups and their actual effectiveness.
A structural dead end
These committees are meant to offer oversight and strategic direction. However, they often spread responsibility across strategy, risk, and compliance, leading to fragmented decision-making. Meanwhile, AI technology evolves rapidly, often developing in weeks, while board meetings occur in quarters. The result is a governance system that seems solid on paper but produces outdated and ineffective decisions.
The challenges run deeper than surface-level inefficiencies. Committees lacking clear ownership struggle to take action. They debate topics such as capabilities versus costs or interfaces versus risks — discussions that frequently lead to no forward progress. The executive’s frustration is not an isolated incident. It reflects a structural flaw that prevents any real movement.
No new role, no new problem
The idea of creating a new chief AI officer may seem like an appealing solution. However, such a role would inherit a complex set of challenges. A title alone cannot resolve these issues. This new executive would need to navigate turf battles with the CTO, face governance conflicts with legal departments, and earn credibility within the C-suite.
Assigning AI leadership responsibilities to the IT department seems like another option. But this overlooks the current pressures on IT. In fact, 35% of CIOs surveyed by Logicalis believe AI is making it harder for their organizations to detect cyber threats and breaches. This perception highlights a critical risk.
Shifting IT leadership away from cybersecurity duties to focus on AI transformation is not a strategic move. It could instead lead to increased vulnerabilities in both cybersecurity and AI initiatives. Letting IT continue to focus on safeguarding the company's data remains the best course of action.
The invisible problem
AI governance is more than a technical issue. It's fundamentally a visibility problem. Effective AI implementations do more than run processes — they uncover inefficiencies that organizations have not recognized or addressed.
IT departments are well-versed in infrastructure. However, they are not immersed in the business operations where AI solutions need to be applied. IT does not fully grasp the nuances of departmental workflows, such as the friction points that arise, the varied risk thresholds, or the decision-making patterns that differ across regions and functions.
What enterprises need is a department that can blend three key qualities: structural neutrality, cross-functional insight, and governance fluency. Only one C-suite office consistently provides all three: the legal department.
General counsel are already stepping into AI governance by default. They manage legal exposure when tools are deployed without proper consideration, they fill gaps that committees fail to address, and they act decisively when others are hesitant. But when legal ownership is assumed without formal recognition, it leads to a reactive posture — where legal teams chase problems instead of proactively shaping strategy.
Assigning the legal team to lead AI governance is not an unusual concept. It acknowledges what legal teams already do and what other departments cannot. It’s about recognizing the unique role the legal function already plays.
It’s time for organizations to shift from endless committee discussions to a model with clear ownership. This means moving away from endless strategy meetings toward a function that can map out and implement the strategy. It also means transitioning from distributed responsibility to a single office that has a comprehensive view of the entire enterprise.
This executive found a way to break out of the AI committee cycle. Her solution wasn’t a new title but rather an existing one with new responsibilities, redefining the way her organization approaches AI governance.