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Last month, I wrote about a question many general counsel are beginning to hear from business leadership: If our outside counsel is using AI, should our legal spend be going down?
Artificial Intelligence is deeply integrated into critical risk functions within organizations, including security monitoring, data classification, incident detection, compliance assessments, document review, and internal investigations. These AI-powered tools often operate in the background, assisting in decisions that carry significant legal weight. While AI undeniably enhances efficiency by processing vast amounts of data, operating continuously, and identifying issues much faster than manual methods, these improvements do not absolve the organization of accountability. When an AI system makes an error, misclassifies data, triggers an alert, or initiates a response, the organization remains fully responsible for the outcome, and the obligation to defend its actions remains unchanged.
A frequently overlooked aspect of AI's impact is its capacity to accelerate not only correct decisions but also incorrect ones. AI-driven systems possess the ability to act at unprecedented scale and speed. Consequently, a single classification error, a flawed underlying assumption, or an incomplete model can rapidly affect substantial volumes of data or trigger actions across numerous interconnected systems before any human oversight can intervene. This doesn't inherently imply that AI is unsafe; rather, it highlights that the propagation of mistakes operates differently in an AI-enabled environment. While legal and security teams may benefit from broader operational coverage, they simultaneously inherit greater and more far-reaching downstream consequences stemming from even isolated failures within the AI system. As AI expands the review and action capabilities of teams, the overall scope of potential impact expands proportionally.
With AI becoming increasingly embedded in routine operational workflows, a significant practical challenge arises in the aftermath of incidents or near misses: discerning precisely "how this decision was made." This question is crucial because regulatory bodies, auditors, corporate boards, and potential plaintiffs do not distinguish between decisions made solely by humans and those made with the assistance of AI. Their primary focus remains on whether the reliance on the AI system was reasonable, adequately supervised, and legally defensible. Legal teams are thus frequently tasked with explaining the rationale behind using an AI-enabled system, the methods used to validate its outputs, the known limitations at the time of its application, and the specific points where human oversight was implemented. These are fundamentally governance-related inquiries, not merely technical ones, and they consistently fall under the purview of legal leadership.
Artificial Intelligence fundamentally alters the economic landscape of decision-making. Once an AI system is deployed, the marginal cost associated with conducting additional analysis, performing reviews, or maintaining monitoring capabilities decreases substantially. This presents a genuine advantage, particularly for organizations operating with limited resources. However, this reduction in marginal cost also facilitates the making of more decisions, more frequently, and often with less human friction or deliberation. Over an extended period, this process leads to a concentration of risk, where a limited number of AI systems exert influence over a broad spectrum of organizational outcomes. While these systems, when performing optimally, can significantly enhance consistency and responsiveness across operations, their poor performance can result in impacts that are rarely confined, thus contributing to a paradoxical situation where organizations feel operationally stronger yet simultaneously more exposed to risk.
Legal departments are uniquely positioned at the critical juncture of cost control, operational reliance on technology, and ultimate organizational accountability. Although legal teams typically do not design the majority of AI systems, they frequently bear the responsibility for approving necessary disclosures, overseeing comprehensive incident response protocols, supporting internal and external audits, and effectively communicating evolving risks to senior leadership and the board of directors. As AI systems become progressively integrated into upstream business workflows, legal teams inherit not only the direct results generated by these systems but also the overarching obligation to stand firmly behind these outcomes, irrespective of whether the AI technology is developed and deployed internally or sourced through third-party vendors. The core message here is not to impede innovation but to ensure that the reliance placed on AI systems is meticulously matched by robust and evolving governance frameworks.
General counsel and legal leaders do not need to become AI technology experts to effectively navigate the paradigm shift introduced by artificial intelligence. Instead, their crucial role involves asking pertinent and insightful questions internally, which can profoundly influence how organizational risk is perceived and managed. Key questions include: identifying instances where AI outputs are relied upon without sufficient human validation; determining which AI-assisted decisions would be challenging to explain or defend following an adverse incident; evaluating the adequacy of documentation for oversight mechanisms and escalation paths; and establishing clear guidelines for when and where AI application is appropriate versus when it is not. These types of inquiries are analogous to those legal departments already apply to outside counsel and critical vendors; AI simply introduces a novel and complex context where these fundamental governance questions hold even greater significance.
Artificial Intelligence offers substantial benefits, capable of making legal, privacy, and cybersecurity functions significantly faster and more efficient. It can dramatically improve the scope of coverage, enhance consistency in operations, and boost responsiveness in increasingly complex and dynamic environments. However, it is vital to understand that efficiency does not equate directly to risk reduction, and the increased speed of AI operations does not eliminate the fundamental principle of accountability. In numerous scenarios, AI tends to shift existing risks rather than entirely remove them, concentrating responsibility into a smaller number of, but far more impactful, decision points. For legal leaders, the strategic imperative is not to oppose the adoption of AI but rather to conscientiously ensure that governance practices evolve in tandem with the growing reliance on these powerful technologies. When expectations are clearly defined and oversight is meticulously implemented, AI can indeed strengthen organizational outcomes without inadvertently expanding exposure to unforeseen liabilities.