The pros, cons, and what actually works in law firms
Most law firms are rethinking how they govern data as they accelerate AI adoption, implement new tools, or try to operationalise long‑promised data governance programmes. One of the biggest early decisions involves choosing the right operating model. Typically, for a law firm, the choice is between:
- Data Domain-Based Governance, and
- Functional/System-Based Data Governance
1. Data Domain–Based Governance
Organising data ownership and stewardship around business‑meaningful areas of data, e.g., Client, Matter, People, Knowledge, Operations, etc.
| Pros | Cons |
| Builds business accountability Domains align closely with how legal work actually happens. Partners and business leaders understand the data because it reflects real‑world workflows (clients, matters, matter phases, work types). Easier to embed into BAU because roles match business responsibility. | Requires mature operating rhythms Without clear responsibilities, domain roles get fuzzy. Firms often appoint “domain owners” in name only, resulting in passive governance. |
| Enables AI-readiness and semantic consistency Cross-functional domains help establish shared definitions and taxonomies, which matter for AI training, data, retrieval, and governance. Reduces duplication and inconsistent metadata across systems. | Harder to stand up from scratch Needs solid foundational artefacts (taxonomy, glossary, RACI, lifecycle maps). Many firms struggle because they skip these steps. |
| Supports federated models Ideal for scaling governance without creating a central bottleneck. Domain stewards can be empowered without needing deep system knowledge. | Can feel abstract at the start People ask questions like: “What does it mean to be the owner of ‘Client Data’?” Needs strong change management and clear expectations. |
| Better for cross-system data quality Most legal workflows touch multiple systems (Intake → PMS → DMS → KM → BI). Domains cut across systems, so they’re closer to the real life-cycle. |
2. Functional/System-Based Governance
Organising ownership around systems or departments, e.g., PMS owner, DMS owner, CRM owner, Finance owner, HR owner, but system ownership doesn’t equal data ownership.
| Pros | Cons |
| Easy to launch Responsibilities map directly to existing system owners and roles. Governance can be stood up quickly without a major operating model change. | Reinforces silos Systems are siloed by design. Workflows and data quality issues often fall between systems (e.g., Intake ↔ PMS ↔ DMS). |
| Clear technical accountability Good for permissions, integrations, infrastructure, and vendor relationships. Helps with questions like: “Who can change this field?” or “Who signs off on this configuration?” | Poor alignment with real business processes Business outcomes depend on cross-system data—not individual systems. Harder to govern the semantic meaning or cross-firm standards. |
| Fits firms with low data maturity If the firm isn’t ready for complexity, system-based models avoid overwhelm. Allows central teams (IT, KM, Risk) to lead until business roles are ready. | Slows down AI adoption AI needs domain-aligned, semantically consistent data. System-based governance struggles to support cross-system training data or Firm taxonomies. |
| Leads to finger‑pointing “That’s a Finance system issue.” “No, it’s a Risk workflow issue.” “Actually, Marketing owns the client record.” |
Which model works best for modern law firms?
The short answer is that most firms ultimately need a domain model, but starting with system-based governance is often pragmatic until their data culture matures.
The longer answer is that in firms with a mature data culture, domain-based governance is a clear win. Firms with immature or unclear ownership structures start with system-based owners, then evolve into domain-based governance as their maturity grows. For firms implementing generative AI, search, or Firm data platforms, domain ownership becomes essential quickly.
The best-performing firms use a hybrid approach. Functions manage the technologies and operational processes. Domains own the meaning, quality, and business rules. This hybrid model is the hallmark of a federated data governance operating framework, which we recommend and regularly support law firms in building.
Recommendations for Law Firms
Most firms don’t switch models overnight. They evolve through a structured shift from function-led ownership to firm-led accountability, using a hybrid model. Based on Iron Carrot’s client engagements, the steps usually look like:
- Start with domains where the risk and the value are highest (Client, Matter, and People are usually the big three) and create a light-weight operating rhythm for your stakeholder groups.
- Create a data governance framework where a Centre of Excellence sets standards and supports the Domains to apply and enforce them. Systems implement them technically (system-based governance is still applicable for configuration and direct access questions)
- Create firm-wide artefacts early to make the domain model real:
- Business Glossary
- Data Dictionary
- Data Lifecycle Maps
- Cross-system Data Quality and Usage Rules
- Core Reference Lists
- Clarify the RACI for each domain, as most failures happen because domain ownership is unclear or overly vague. Shift decision rights incrementally; don’t try to do everything at once.
- Link governance to incentives. Stakeholder groups are more engaged when governance ties to the firm’s risk, revenue and efficiency, as well as personal objectives and remuneration.
Typical challenges faced by law firms implementing a hybrid data governance model and how to overcome them
Challenge 1: Confusion over roles and decision rights
Hybrid means System Owners are technical, Domain Owners are business-focused, Governance looks at standards, and IT is for enablement. But law firms often merge or misplace these responsibilities. This can be addressed by creating a 3-layer accountability model, documented in your RACI templates for each domain and supported by your firm’s data governance charter or policy.
Challenge 2: Silos and political friction
Domain-based governance is a cultural shift. Stakeholders may resist losing control, or Functions may defend their territory. Overcome it by modelling and planning the behavioural change. You will need to plan what people need to know differently, do differently, and use differently. As well as being able to explain the why behind each new activity.
You may find it valuable to start with 1 Domain. Demonstrating wins and ensuring cross-functional participation (slow and steady until everyone is on board). Link success messaging to the firm’s strategy and/or AI readiness since these are objectives people can understand.
Challenge 3: Lack of foundational artefacts
Most firms try to run domain governance without a firm taxonomy, business glossary with clear definitions, lifecycle maps, or quality rules. This creates chaos. Once you have the high-level domains in place, start work on sub-domains and critical data elements. Ensure the taxonomies and definitions required to explain the data within each domain are up to date and have cross-functional buy-in.
Challenge 4: Over-centralisation or over-delegation
Firms often get the operating cadence wrong. Either everything is routed through central data governance, creating a bottleneck, or everything is devolved to domain groups, leading to inconsistency. Finding the middle path where the central data governance team sets standards and templates, and domains use those standards and templates. Central teams can act as a neutral group to help facilitate cross-functional domain discussions.
In conclusion
Law firms must carefully consider their data governance approach as they navigate the complexities of modern legal work and the growing integration of AI technologies. While starting with a functional/system-based model may offer an immediate solution, transitioning to a data domain-based governance structure provides a more sustainable framework for long-term success. By fostering a culture of accountability and ensuring clear ownership, firms can enhance data quality and integrity, ultimately driving better business outcomes.
Embracing a hybrid model can leverage the strengths of both approaches, enabling firms to adapt and thrive in an evolving landscape. As data becomes an increasingly critical asset, investing in thoughtful governance frameworks will position law firms for a successful future.
Innovative law firms have big goals for improving the client experience through data innovation.
Through our extensive law firm background, we have developed a unique data governance road-mapping approach to help law firm leaders launch the proper foundation for their data strategy.
If you want to chat confidentially about how Iron Carrot can help your firm with its Data Strategy and Data Governance initiatives, then send me a Direct Message via my Profile, or book a call via the Iron Carrot Limited website.
