(Sponsored content). In last week's issue, we published Part 1 of the Small to Mid-Market AI Adoption Trends from D2LT's Akber Datoo. This week, Part 2 covers next steps and critical considerations for the road ahead
Next Steps: Measured Pilots, Clearer Governance
From our work with a number of small and medium sized law firms and Law Society members, most are planning next steps cautiously:
- Extending personal-use pilots under a formal AI-usage policy
- Engaging external experts to map opportunities and risks
- Running proofs-of-concept in low-stakes areas like internal knowledge management
- Building a phased roadmap rather than ad-hoc adoption
These steps can provide structure and accountability — both essential to building trust in AI’s role.
Surprising Insights: Clients Are Moving Faster
One surprising finding is that clients themselves are often further along in using AI and expect their counsel to keep pace. This creates a reputational pressure on firms to demonstrate AI capabilities. Equally revealing is the underutilisation of existing tools—many firms own sophisticated software but use less than 25% of features.
Critical Considerations for the Road Ahead
Looking forward, the opportunity lies in addressing broader strategic and operational issues:
- Governance & Risk:
Professional and regulatory bodies such as the SRA and ABA, plus insurers, and regulators (in the case of the EU AI Act) demand the right governance and controls. Firms must define who owns AI risk registers and implement “human-in- the-loop” sign-offs to mitigate risks from hallucination or bias.
- AI Policy and Strategy:
Establish clear guidelines for AI use, covering everything from acceptable tools and use cases to data handling protocols and approval processes for client-facing applications.
- Data Quality:
AI is only as reliable as the data it sees. Precedent banks must be clean, deduplicated, and tagged by jurisdiction.
- Change Management:
Adoption will stall without aligned incentives.
A tech-champion network or dedicated “legal engineer” roles can drive momentum.
- Commercial Impact:
AI affects matter staffing, pricing, and profitability.
Firms should explore alternative pricing models to enhance competitiveness.
- Measurement & KPIs:
Success must be quantified—time saved, error rates, client NPS, and revenue per FTE.
- Vendor Strategy:
Firms face a choice: platform ecosystems or point solutions? Lock-in and flexibility are key considerations.
- Ethics & Bias:
Courts have sanctioned “hallucinated” citations.
Red-teaming and stress-testing AI outputs are crucial.
- Cybersecurity:
Generative AI expands the attack surface.
Independent security reviews (e.g., ISO 27001, SOC 2) are now table stakes.
- Sector-Specific Opportunities:
Litigation analytics, e-discovery, and due diligence already embed AI at scale. Practices like IP and investigations could benefit first.
- Talent Attraction:
Junior lawyers expect modern tools. Firms should showcase AI roadmaps to retain and attract tech-savvy talent.
Conclusion: Momentum Builds
The direction is clear. 90% of Am Law 200 leaders expect generative AI investments to rise over the next five years. To thrive, firms must balance innovation with governance, experimentation with guidance, technology with humanity—and above all, listen closely to both clients and staff.
Important to note: The threat is not AI replacing lawyers—it's AI proficient lawyers replacing those who resist change.
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