Law firms are now run through systems and data: client onboarding, conflicts, matter opening, pricing, billing, finance, CRM, knowledge management, credentials, risk, compliance, client portals and reporting. Increasingly, the way we advise clients, interact with them operationally, and supervise work is mediated through data.
It is not just about efficiency. It is about whether a law firm is fit to operate in a digital age.ย For mid-size firms in particular, governance failures can have a disproportionate impact because a single billing issue, confidentiality breach or failed conflicts process can damage both client trust and profitability far more quickly than in a larger institution.
The SRA may not use the phrase โdata governance programmeโ, but the Code of Conduct for Firms requires effective governance structures, arrangements, systems and controls to keep records demonstrating compliance; to remain accountable where work is carried out through others; and to identify, monitor and manage material risks to the business.
In other words, if the data is wrong, the process is unclear. The ownership is missing, the audit trail is weak, the firm cannot evidence what happened โ and the regulator is entitled to ask hard questions. Akber Datoo, CEO, and Daniel Heymann, Head of Law Firm Transformation, at D2 Legal Technology, say this is why firms must tackle IA (Information Assurance) before AI.
Weak controls, professional and regulatory exposure
Weak controls can create significant professional and regulatory exposure. Take client and matter data, for example. If client hierarchies, related parties or matter descriptions are wrong, a conflicts check may be incomplete. Confidential information may be exposed to the wrong team. A client may be described inaccurately in a pitch, report or credential. That is not โCRM hygieneโ. The SRA rules require firms to avoid acting where there is a conflict or significant risk of conflict unless the relevant conditions are met, and to keep current and former clientsโ affairs confidential unless disclosure is permitted or required.
When looking at pricing and billing, if a finance system applies the wrong rate because PQE, rank, role, jurisdiction or effective-date data is wrong, a client may be overcharged. A bill may be inaccurate. A partner may approve a pre-bill on a false basis. The SRA Accounts Rules require accurate, contemporaneous and chronological accounting records, reconciliations, and a central record of bills or written notifications of costs.
Itโs also dangerous if there are weak controls in knowledge management. After all, a firmโs knowledge base is not just a useful library. It is part of the professional infrastructure through which legal work is delivered. Precedents, research notes, playbooks, matter experience and legal updates need ownership, review dates, version control, jurisdictional scope and clear rules on what is approved, historic or merely contextual.
Clearly, if a lawyer relies on an outdated precedent, mislabelled authority or unreviewed research note, the problem may end up appearing in advice, drafting or a submission to court. With the individual Code requiring solicitors not to mislead clients, the court or others, and to make only assertions and submissions that are properly arguable, this becomes a significant issue.
Every firm needs a โgolden sourceโ
This is where the โgolden sourceโ point becomes critical. Not every source should carry the same weight. A law firm needs to know which system wins. Is the authoritative source the matter-management system, the finance system, the CRM, the signed engagement letter, the court document, the knowledge repository, or the lawyer-reviewed matter-status field?
Good data governance answers that before something goes wrong. Firms need to follow the right model, starting with the source of truth first, supporting evidence second, interpretation third and human legal judgement wherever legal judgement is required.
However, many firms are focusing on tools rather than strategy. Simply buying Harvey, Legora, Copilot or any other AI tool does not solve the problem. AI layered onto poor data governance will not make a firm safer. It may make the same weaknesses faster, more confident and harder to spot.
Recent incidents across the world, from SME enterprises to global firms such as Sullivan & Cromwell, highlight how AI hallucinations are a growing problem across the legal sector. Damien Charlotinโs database of AI hallucination cases demonstrates that no firm is immune to this issue, with cases emerging from organisations of all sizes, with the data also suggesting increasing frequency.
Often in these cases it is said that internal AI policies and secondary review processes had not been followed. While this is often described as an AI problem, it is also a governance issue. Before letting AI impact these decisions, firms need to ask themselves: What is the approved source? What is our review process? Who is responsible? What checks are required before filing? How will legal authority be verified? This is not simply a back-office problem.
Governance is becoming a leadership issue
Fee earners need to care about data. Not because they should become data administrators, but because only they can validate key legal and commercial judgements: matter scope, client identity, risk status, conflicts context, assumptions, advice given, pricing exceptions, experience claims and whether something is safe to communicate externally.
Managing partners and practice heads need to care, too. Governance is not a โbig firmโ discipline; every firm that holds confidential client information, sends bills, manages conflicts and relies on digital systems already depends on data governance, whether it formally recognises it or not. Data governance cannot be delegated entirely to IT, Finance, BD, Knowledge or Risk. Those teams can build the framework, but they cannot supply the legal and commercial judgement that makes the data reliable.
Conclusion
Getting data governance wrong is extremely dangerous. So, before asking, โWhat AI tool should we buy?โ, the questions should be: Who owns our critical data? What is our golden source? Are our definitions consistent? Who approves exceptions? What is the escalation route? Can we evidence the control? And, would we be comfortable if AI used this data at scale?
Ultimately, good data governance is not bureaucracy. It needs to be a priority to ensure law firms can protect clients, price accurately, bill correctly, manage conflicts, preserve confidentiality, improve knowledge, supervise work, evidence compliance and prepare responsibly for the implementation of new tools, such as AI.
These risks and issues will not go away on their own. And, thereโs potential they could escalate, becoming an SRA problem. More fundamentally, it may become a survival problem. Because, in a digital age, being a good law firm increasingly depends on being a well-governed data organisation, too. Ultimately, no law firm can sustain a credible AI strategy without credible data governance.
