Responsible AI in practice: managing risk across global operations | LexisNexis
Responsible AI is no longer a theoretical discussion for large law firms. As AI tools are embedded into research, drafting, knowledge management and client delivery across multiple jurisdictions, firms face growing reputational and operational exposure if these systems are not governed consistently and transparently. This article explores how large, multinational legal practices can apply reputation risk management best practices to AI adoption while aligning global operations with regulatory and client expectations.
Why responsible AI is now a reputational risk issue for global law firms
For large law firms, AI adoption increasingly sits at the intersection of strategic and reputational risk. Clients expect innovation, efficiency and speed, but they also expect discretion, explainability and regulatory compliance. A single AI-related failure, such as inappropriate data use, opaque outputs or embedded bias, can quickly escalate into a firmwide reputational issue.
AI risks scale more rapidly than traditional technology risks. A system deployed across offices in London, Frankfurt and Singapore may engage different data protection regimes, professional obligations and cultural expectations. This makes responsible AI a central component of legal industry risk management rather than a narrow technology concern.
Effective reputation risk management plans therefore treat AI governance as a leadership issue, embedded into firmwide frameworks and aligned with existing law firm risk management policies.
Building a reputational risk management framework for AI
Large firms benefit from adopting a clear reputational risk management framework that applies consistently across global operations while allowing for local nuance. At its core, this framework should define accountability, approved use cases and clear escalation routes where AI outputs raise ethical, legal or client concerns.
The Information Commissioner’s Office provides a practical reference point through its AI and data protection risk toolkit, which helps organisations assess and mitigate risks to individuals’ rights and freedoms before AI systems are deployed. Although grounded in UK GDPR, the toolkit aligns closely with law firm risk management practices by encouraging proportionality, documentation and senior oversight.
The ICO’s guidance on explaining decisions made with artificial intelligence reinforces the importance of transparency. For law firms, reputational exposure does not stem solely from whether an AI output is accurate, but whether lawyers can explain how it was generated and justify its use to clients, courts and regulators. These expectations apply equally across multinational legal practices, regardless of where the underlying technology is hosted.
The ICO’s broader strategy, Preventing harm, promoting trust: our AI and biometrics strategy, further highlights how trust, governance and accountability are now central to managing AI-related reputational risk at scale.
Managing global consistency without losing local control
One of the most persistent challenges for multinational legal practices is balancing global consistency with jurisdiction-specific regulation. AI governance that is overly fragmented increases operational and reputational risk, while highly centralised approaches can fail to account for local legal and cultural requirements.
A pragmatic approach is to establish global law firm risk management regulations for AI that set minimum standards on data use, human oversight and auditability. Local offices can then supplement these standards with jurisdiction-specific controls. This mirrors approaches taken by regulators such as the Financial Conduct Authority (FCA).
Through initiatives including the FCA AI Lab and its live AI testing services, the FCA has demonstrated how AI systems can be trialled in real-world conditions while maintaining regulatory oversight and continuous risk monitoring. For law firms, the lesson lies in adopting similar disciplines. Controlled testing, documented assumptions and ongoing review reduce the likelihood that AI failures develop into reputational crises, particularly where AI tools support client-facing work.
Aligning AI governance with client expectations and market trust
Client scrutiny of AI use is increasing, particularly among regulated, multinational and public sector clients. Many now expect their advisers to explain how AI tools are governed, how client data is protected and how bias or errors are identified and mitigated.
Embedding AI governance into formal law firm risk management practices helps firms respond confidently and consistently to these questions. It also reduces the risk that different offices provide conflicting assurances, which can undermine trust at a global level.
LexisNexis research on measuring the success of AI across the law shows that firms achieving the greatest value from AI are those that connect adoption to defined business outcomes supported by clear governance and risk controls. This reinforces that responsible AI is not a constraint on innovation, but an enabler of sustainable growth across complex operations.
Solutions such as Lexis+ AI support this approach by combining fast and accurate generative legal AI with trusted content, explainability and audit trails, helping firms manage both operational efficiency and reputational exposure while adding measurable value for clients.
Turning responsible AI into a competitive advantage
Responsible AI should be viewed as a strategic differentiator rather than a compliance exercise. Firms that can demonstrate strong reputation risk management best practices in their use of AI are better positioned to win work from risk-aware clients and to expand confidently across borders.
This requires investment in governance, training and tools that align with existing law firm risk management regulations and policies. It also requires sustained engagement from senior leadership to ensure AI risks are assessed alongside other strategic and reputational risks facing the firm.
As regulatory scrutiny and client expectations continue to evolve, firms that embed responsible AI today will be better placed to protect trust, reputation and long-term growth across their global operations.
