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P E E R T O P E E R M A G A Z I N E · W I N T E R 2 0 2 5 37 work together. AI tools require clean, consistent, well-structured data to function effectively. Feed them duplicated files, inconsistent metadata, or poorly classified documents, and the outputs become unreliable—or worse, create new liability. Consider the ethical risks already emerging. High-profile cases have seen attorneys sanctioned for submitting AI-generated briefs containing hallucinated citations. These incidents have prompted the ABA to issue formal guidance reminding firms of their duties of competence, confidentiality, and supervision when deploying AI tools. Poor data governance doesn't just increase the likelihood of these errors—it undermines a firm's ability to respond defensibly when they occur. The intersection with privacy regulation makes governance even more critical. When state privacy laws grant consumers the right to opt out of automated decision-making that produces "legal or similarly significant effects," firms must be able to identify where such systems are deployed, what data they process, and how to honor opt-out requests. Without governance infrastructure, compliance becomes impossible. Corporate clients are becoming increasingly sophisticated about these requirements. 65% now include IG requirements in their outside counsel guidelines, according to the Mattern Associates survey. These include expectations around document retention, file ownership, digital security, and access protocols. Firms that cannot demonstrate governance maturity risk being excluded from panels and repeat engagements. The regulatory landscape is tightening rapidly. Gartner predicts that by 2027, fragmented AI regulation will cover 50% of the world's economies, driving $5 billion in compliance investment. For law firms, this means governance isn't just about internal policy—it is about meeting evolving client demands and regulatory requirements that will only intensify. The message is clear: governance isn't a barrier to innovation—it is a prerequisite. Firms that attempt AI adoption without first establishing information discipline will find themselves navigating ethical pitfalls, regulatory violations, client dissatisfaction, and operational instability. Those who build from a foundation of governed, reliable data will be positioned to lead. WHAT TECHNOLOGY LEADERS SHOULD BE DOING NOW For ILTA members navigating this landscape, the path forward requires shifting how governance is understood and prioritized. First, recognize that IG is not a back-office function. It is a strategic enabler that determines whether firms can respond to client audits, train AI tools confidently, comply with privacy regulations, and empower professionals with accurate information. Second, embrace digital governance as an integrated discipline. Organizations can no longer treat privacy, AI governance, cybersecurity, and information management as separate domains. This means establishing cross-functional governance councils that unify Legal, IT, Privacy, and Operations around shared objectives. Third, move from policy creation to implementation. Most firms do not need better policies—they need execution. Assign clear ownership and accountability for data assets. Ensure governance structures can respond to state privacy laws and AI regulations. Fourth, audit existing systems honestly. Identify where data lives, how it is used, whether automated decision-making systems are deployed, and whether policies align with practice. Closing gaps requires hands-on coordination—configuring systems, training users, documenting AI use cases, and creating mechanisms for sustained accountability. Fifth, align governance initiatives with regulatory compliance, client expectations, and technology roadmaps. IG work should not happen in isolation from AI adoption, privacy law compliance, or cybersecurity investments. These initiatives depend on well-governed data to succeed.

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