The conventional approach to enterprise Artificial Intelligence (AI) strategies often involves IT departments leading the charge, with committees offering advice and broad input from across the organization. This often results in strategies that are meticulously documented in slide decks but falter during execution. Eric Dodson Greenberg, Cox Media Group’s Chief Legal Officer, argues that an integrated legal and IT model, while not an immediately intuitive solution, may be the most effective path forward for many General Counsels seeking to navigate the complexities of AI adoption.
"We talk about AI for hours and make no decisions," lamented a senior executive at a Fortune 50 company, articulating her frustration with an interdisciplinary AI committee. The executive’s experience, characterized by endless discussions weighing capabilities against costs and interfaces against risks, led to stagnation rather than progress. This sentiment is not an isolated anecdote; it reflects a systemic challenge within large organizations. A recent Sedgwick survey of Fortune 500 executives revealed that while 70% of companies have established AI risk committees, a mere 14% report being fully prepared for AI deployment. The proliferation of committees, it seems, has not automatically translated into effective governance.
The formation of dedicated AI committees by boards and CEOs, while appearing decisive, can inadvertently fragment oversight. Such structures can allow board committees to diffuse accountability, scattering responsibility across strategy, risk management, and compliance. Furthermore, these committees often struggle to keep pace with AI’s rapid development cycles, which can be measured in weeks, contrasting sharply with the quarterly cadence of board meetings. This temporal mismatch can render governance frameworks, while proactive on paper, obsolete by the time decisions are made. Without clear ownership, even well-intentioned committees often lack the cohesion to act decisively.
The Limits of Conventional Solutions
The search for effective AI leadership often leads to reflexive, yet ultimately insufficient, answers. One tempting proposal is the creation of a dedicated AI leadership role. However, the elegance of this idea on a whiteboard rarely survives the competing priorities and political realities of daily corporate operations. Such a role, particularly without an existing portfolio, established relationships, or institutional credibility, can replicate the very structural problem it aims to solve: distributed ownership requiring a new position to impose coherence. A Chief AI Officer (CAIO) without a clear mandate or established trust can easily find themselves navigating turf battles with existing C-suite executives, such as the Chief Technology Officer, and facing governance conflicts with the legal department, all while struggling to gain the necessary buy-in from a leadership team that may not have explicitly requested another peer.
An equally intuitive alternative is to assign AI oversight to the IT department, leveraging their existing technical expertise, infrastructure knowledge, and vendor relationships. However, IT departments are already engaged in a constant battle for enterprise survival. A recent Logicalis survey indicated that 77% of CIOs reported their organizations had experienced a cyberattack in the preceding year, and 35% stated that AI was making it harder, not easier, to detect breaches and attempted attacks. The very AI capabilities that offer opportunities for enterprise advancement are simultaneously multiplying the attack vectors. Consequently, diverting IT leadership from critical cybersecurity responsibilities to spearhead AI transformation is not a strategic move; it is a strategy that creates exposure on both fronts. Maintaining IT’s focus on security, therefore, is not a limitation but a fundamental aspect of good governance.
The Visibility Gap: An Underlying Challenge
Beyond the structural issues of leadership and committee effectiveness, a deeper challenge hinders successful enterprise AI adoption: the problem of corporate visibility. Enterprise AI is not solely a technology deployment issue; it is fundamentally a challenge of understanding how an organization truly operates. The greatest value of AI lies in its ability to adapt to the unique idiosyncrasies of departmental workflows – how procurement routes approvals, how marketing clears compliance, and how HR manages onboarding across diverse jurisdictions. The opportunity for AI is bespoke, not generic. The most impactful AI implementations do not merely automate existing processes; they reveal hidden inefficiencies that the organization may not have even recognized.
IT departments, while masters of infrastructure, typically lack the granular visibility into these intricate departmental workflows. They understand the systems and networks but do not necessarily inhabit the business problems that AI is intended to solve, nor do they possess deep insight into cross-functional friction, varying risk tolerances, or the nuanced decision-making patterns that differ across departments and geographies.
What the enterprise truly requires is a function that integrates three critical elements: structural neutrality, cross-functional insight, and governance fluency. Most corporate departments, by their nature, possess inherent biases or are perceived to lack the structural neutrality necessary for impartial AI leadership. Each function typically operates with its own budget interests, territorial instincts, and a historical tendency to prioritize its own objectives. Cross-functional visibility entails a profound understanding of how departments actually function – their processes, their interdependencies, and the friction points that arise at the intersection of disciplines. Governance fluency, on the other hand, means possessing the capacity to manage risk, compliance, and institutional decision-making at the accelerated pace that AI demands. No single technology function inherently offers this comprehensive triad of capabilities. However, one C-suite office, often overlooked in AI discussions, possesses these attributes.
The General Counsel: An Unexpected Architect of AI Strategy
In the experience of many General Counsels (GCs), and in conversations with their peers, legal departments are already absorbing aspects of AI governance by default, not by design. GCs are increasingly stepping in when business units deploy AI tools that create legal exposure, managing risks that no other function claims responsibility for, and filling the vacuum that AI committees were intended to address. However, this default ownership, lacking a clear mandate, fosters a reactive posture. Legal departments find themselves playing catch-up or course-correcting rather than proactively mapping AI strategy.
This realization informed the advice given to the Fortune 50 executive struggling with unproductive AI meetings: the General Counsel should lead on AI adoption, not merely participate. This suggestion, while deliberately provocative, highlights a crucial point. The structural attributes that a GC brings to the table are systematically underweighted in conventional AI leadership discussions. The immediate reaction from the executive, "But legal is not a technology function," reflects a common, albeit limited, assumption that legal’s role in AI is solely defensive – focused on risk mitigation, compliance, and establishing guardrails. This framing overlooks the evolving market landscape and the inherent strengths that a GC offers.
The GC’s path to AI fluency is often more direct than initially perceived. The core competencies of risk assessment, navigating complex regulatory environments, and establishing ethical governance map directly onto AI’s most consequential challenges. This contrasts with the more significant technical retooling that other C-suite leaders might require. In an era where organizations often struggle with clear AI ownership and where Chief AI Officers are increasingly becoming scapegoats for deployment failures, the GC offers a rare asset: a leader whose existing expertise inherently aligns with AI’s governance demands, whose cross-functional credibility is already established, and who requires no wholesale professional reinvention.
Notably, proposals for a CAIO often overlook the General Counsel, creating a significant blind spot that fails to acknowledge where AI adoption and capital are actually flowing. A recent FTI/Relativity survey indicated that a substantial 87% of legal departments have already adopted generative AI in their operations. This suggests that legal is not merely experimenting with AI but is actively leading the adoption curve, doing so under real regulatory pressure rather than in a controlled sandbox environment.
The investment market reflects this trend. Private equity and venture capital have injected unprecedented sums into AI tools specifically designed for legal work, with over $2 billion invested in legal-related AI startups. This surge is driven by the nature of legal work: it is document-intensive, often repetitive yet high-value, and tightly regulated – precisely the areas where large language models excel. Sophisticated AI capabilities, such as contract analysis, document review, knowledge management, and risk modeling, are frequently emerging first within the legal market. The critical insight the market is beginning to absorb is that these tools have applications far beyond legal departments. A contract review engine, for instance, can be repurposed as a vendor risk assessment platform, and a document workflow system can evolve into an HR compliance tracker. Organizations that recognize this can strategically leverage their legal departments as a gateway for enterprise-wide AI transformation.
An Alliance Built for Functionality
The optimal solution lies not in legal departments displacing IT, but in a synergistic alliance between the General Counsel and IT. This seemingly unconventional partnership leverages the distinct strengths of each function rather than compelling one to assume the other’s responsibilities.
IT can remain focused on its core strengths: infrastructure, security, and technical integration, areas where its expertise is both essential and irreplaceable. The General Counsel, meanwhile, brings governance oversight, cross-functional insight, and a proximity to the actual business problems that AI is intended to solve. In many organizations, the GC also serves as the corporate secretary, fostering a direct working relationship with the board of directors that few other C-suite executives possess. This provides a natural channel for ensuring board-level engagement with AI governance.
This mutual recognition is growing. The 2026 FTI/Relativity report, for the first time, included perspectives from Chief Information Officers (CIOs) who identified legal departments as "digital ambassadors" for AI and digital transformation. IT professionals are witnessing firsthand what the data already indicates: the legal department has become one of the most AI-fluent functions within the enterprise.
The legal department is no longer merely a collection of subject-matter experts. The proliferation of legal technology over the past decade has catalyzed the rise of legal operations professionals who combine technological fluency with a deep understanding of how the enterprise actually functions. The GC now has a critical right-hand advisor who is both schooled in emerging technologies and steeped in the operational realities of the organization. This individual can curate new tools, coordinate effectively with IT, and identify cross-functional needs and opportunities that neither function would likely discover independently. This unique combination of skills is rarely found elsewhere in the enterprise and is increasingly being prioritized and invested in by forward-thinking GCs.
Consider a practical example: three years ago, a legal team led the rollout of an AI-enabled contract management system. The officially stated scope was limited to centralizing agreements and improving version control. However, during the implementation process, the legal operations team mapped the entire vendor-contract journey. They discovered that the new system could effectively replace a cumbersome procurement workflow that typically took three weeks per vendor. Within six months, the cycle time for vendor onboarding dropped to under five days. While Finance retained control over spending, it no longer owned the protracted workflow. The Chief Financial Officer (CFO), far from feeling threatened, expressed relief. No committee, with its inherent layers of approval and diverse interests, could have orchestrated such an outcome; it emerged from focused ownership and proactive problem-solving.
Guidance for Boards and CEOs
The existing data unequivocally demonstrates that the current approach – characterized by committees lacking mandates and oversight without clear ownership – is failing to yield tangible results. To engage seriously with AI governance, boards must fundamentally rethink the architectural framework rather than simply adding another layer of complexity.
Boards should be posing critical questions: Who owns the AI strategy, and is that role clearly defined? Can non-technical leaders articulate the company’s AI strategy, its primary use cases, and the associated risks? Is there a discernible roadmap for scaling AI adoption across the organization?
In situations where accountability remains unclear, CEOs should consider granting the General Counsel a new, three-part mandate. This mandate would empower the GC to lead an AI steering group with explicit authority to recommend strategic priorities. In partnership with legal operations and IT, the GC would curate existing AI tools and identify cross-functional use cases that can be repurposed within the next year. Crucially, the GC would be responsible for defining the policies, guardrails, and training programs necessary to ensure that all AI deployments meet stringent legal, regulatory, reputational, and ethical obligations.
It is important to acknowledge that not every GC will be suited to this expanded role. Boards and CEOs must assess not only legal acumen but also operational fluency. The success of GC leadership in AI, and the essential partnership with a CIO or CTO, will hinge on nuanced dynamics and relationship-dependent factors. However, as a foundational framework, this model offers unparalleled structural potential for boards seeking a coherent AI strategy amidst the chaos of rapid technological advancements. It is also a valuable approach for CEOs who recognize operational instinct and legal sophistication in their GCs.
Where the right conditions are present, the GC offers a structural fit for AI leadership that other functions cannot readily match. Where these conditions do not exist, boards and CEOs must identify the function and leader capable of delivering the same combination of governance fluency, neutrality, and enterprise-wide insight through an alternative pathway.
The integrated model – with IT securing the necessary infrastructure, legal governing the overarching strategy, and legal operations coordinating and translating between vendors and the enterprise – represents a pragmatic solution to the complex challenge of enterprise AI strategy. In an era where AI’s greatest risk is governance failure and its most significant opportunity lies in cross-functional transformation, the pertinent question is not whether this alliance makes sense, but rather how long organizations can afford to operate without it.
