From risk to ROI: The business case for AI governance

10
Jun
2025

Antony Wells

Artificial intelligence has emerged as a transformative force in the legal industry, promising increased efficiency, reduced costs and enhanced service delivery. From contract analysis to legal research, AI tools are reshaping the way we work. Yet amid the innovation rush, a critical success factor is often overlooked: Information governance (IG). Without robust governance frameworks, organisations risk not only diminished returns on their AI investments but also significant compliance failures and ethical breaches. As AI adoption accelerates, the business case for implementing strong information governance has never been more compelling.

AI governance is a financial necessity

The economic argument for AI in legal operations is straightforward: automation reduces labour costs, speeds processes and allows highly skilled professionals to focus on high-value work. However, these financial benefits can quickly evaporate without proper information governance.

Consider the potential hidden costs of ungoverned AI implementations. Poor data quality, inconsistently formatted documents, inadequate metadata, or siloed information forces AI systems to work with incomplete or inaccurate inputs. The result? Reduced accuracy, additional human review and ultimately, diminished ROI. 

Regulatory penalties present another significant financial risk. The evolving patchwork of AI regulations internationally is creating a complex compliance landscape. The European Union's AI Act proposes penalties of up to €20 million or 4% of a company's global revenue for non-compliance with AI regulations.2 This substantial financial risk emphasises the necessity to establish comprehensive AI governance frameworks to ensure adherence to evolving regulatory standards. Meanwhile, privacy frameworks like GDPR impose penalties of up to 4% of global revenue for data protection violations. With this expanding regulatory environment, the financial stakes of proper AI governance are unmistakable.

Information governance provides the foundation for maximising AI's financial returns by:

• Ensuring data quality and standardisation before AI implementation
• Creating consistent taxonomies that enhance AI accuracy and reduce false positives
• Establishing clear data retention policies that reduce storage costs while maintaining compliance
• Implementing audit trails that demonstrate regulatory adherence and reduce compliance costs

Operational excellence through structured governance

Beyond direct financial implications, information governance drives operational improvements that enhance AI's effectiveness. A structured governance approach:

1. Reduces deployment bottlenecks: Poor data governance is a major contributor to AI project failures and delays. By establishing clear data policies and governance structures before implementation you can avoid setbacks caused by inconsistent data, regulatory concerns, or integration issues.
2. Improves AI accuracy: AI systems rely on high-quality, standardised data to deliver consistent and reliable results. Studies show that well-structured data governance practices enhance AI performance by reducing inconsistencies, improving prediction accuracy and minimising errors in legal document classification and information extraction. According to Forbes Insights, organisations that implement strong data standards enable AI systems to generate more precise outcomes by ensuring data consistency and integrity.3
3. Lowers integration challenges: Well-governed information environments experience fewer interoperability issues when introducing AI tools, reducing IT support costs and user frustration.
4. Enhances scalability: As AI use cases expand, governed environments can more readily apply successful approaches across practice areas without reinventing governance processes.

When implemented within recognised frameworks like NIST AI Risk Management Framework or ISO 42001 for AI management systems, governance becomes a strategic advantage rather than a compliance burden. These frameworks provide structured approaches to risk assessment, transparency requirements and human oversight that align with legal industry standards.

Doing the right thing: Ethics and professional standards

Perhaps most critically, information governance addresses the unique ethical dimensions of AI:

• Client confidentiality: Without proper governance controls, AI systems may inadvertently expose privileged information or commingle client data. Information governance establishes boundaries that protect client confidentiality.
• Privilege protection: AI systems that process privileged communications without appropriate safeguards risk privilege waiver. Governance policies that clearly delineate privilege protection protocols preserve this essential protection.
• Bias mitigation: Unexamined AI can perpetuate or amplify biases in legal reasoning or outcomes. Information governance frameworks include testing protocols and evaluation criteria that identify and address potential bias, protecting firms from reputational damage and potential liability.
• Transparency requirements: As courts increasingly examine AI use in legal proceedings, the ability to explain AI processes and decisions becomes crucial. Governance documentation provides the necessary transparency when AI methodologies are questioned.

The path forward: Act now to lead with confidence

Leaders must act decisively to ensure AI success is built on a foundation of strong information governance. Before advancing major AI initiatives, firms should:

1. Assess the current state of information governance to identify gaps.
2. Align AI governance policies with established frameworks like NIST AI RMF or ISO 42001.
3. Establish cross-functional governance teams including legal, IT and compliance stakeholders.
4. Implement clear, measurable governance metrics tied to both risk management and business value.

AI is already reshaping legal practice, but it’s not just about automation. Success hinges on control and how data is structured, secured and governed. Firms that invest in governance early will operate with greater efficiency, accuracy and trust. Those that don’t risk falling behind, exposed to compliance gaps, inconsistent outcomes and ethical pitfalls.

Conclusion: Information governance as a strategic advantage

AI’s impact is undeniable. But the firms that will lead are those that view information governance as a strategic enabler, not a regulatory checkbox. The business case is clear:

• Financial: Higher ROI through cleaner data and reduced exposure to fines.
• Operational: Better-performing AI models powered by structured, reliable information.
• Ethical: Alignment with professional responsibilities while reducing reputational risk.

Governance cannot be an afterthought. It must be foundational and built into AI strategies from day one. That’s how firms will unlock the full value of AI while staying compliant, ethical and competitive.

LegalRM have hosted many educational webinars over the last few months on this topic and other related information governance subjects. These webinars are all available free of charge and on demand by clicking here. 

If you would like to find out how iCompli, from LegalRM can help your firm manage and govern data more efficiently and compliantly then do not hesitate to get in touch.