Over the last six weeks or so, four separate surveys have come out, all reporting on generative AI adoption within the legal profession. I’ve reported on all four separately, but wondered how their findings compared when stacked up against each other.
To help me in this, I turned to — you guessed it — generative AI. Using ChatGPT 4.5, I uploaded the four survey reports and asked it to create a comparative analysis.
Because the reports cover more than just AI adoption, I instructed it to keep its comparison to the issue of AI adoption. I asked it to look at who the reports surveyed, what they found, and how their findings aligned or differed.
Based on the comparison it generated, I then went through and made sure it aligned with what the surveys actually said. Once I did that, I edited and adapted the comparison for the purpose of publishing it here.
The four reports I analyzed are:
So how did these surveys compare in their findings? Read on to find out what I and my friend ChatGPT found.
Who They Surveyed
Smokeball report: Primarily surveyed small firms and solo practitioners across the U.S., focusing on firm owners, lawyers, and office managers.
ABA report: Conducted among ABA-member attorneys in private practice across varying firm sizes, including solo practitioners, small (2-9), mid-sized (10-49), and large firms (100+ attorneys). The respondents averaged 28 years in practice, predominantly older (average age of 57 years).
AffiniPay report: Surveyed over 2,800 legal professionals, with respondents distributed across various practice areas, firm sizes, and roles, including a notable segment in immigration, personal injury, family law, criminal law, and estate planning. A significant proportion of respondents were from small firms or solo practitioners, but it also included larger firms (51+ lawyers).
Thomson Reuters report: 1,702 professionals across legal, tax, corporate and government sectors globally (42% in U.S.), including lawyers at firms, in-house departments, and government legal departments.
AI Adoption Rates and Trends
Smokeball:
AI adoption rose significantly from 27% (2023) to 53% (2024) among small firms.
Strong personal enthusiasm for learning AI tools.
ABA:
Notable rise in AI adoption, from 11% in 2023 to 30% in 2024.
Higher adoption in larger firms (39% for firms with 51+ attorneys), lower among small firms (~20%).
AffiniPay:
Personal AI use increased to 31%, up from 27% the prior year. Firm-wide adoption was lower at 21%, a drop from the prior year’s 24%.
Growth in adoption cautious and incremental, with 29% of non-users planning adoption within a year.
Thomson Reuters:
Significant jump in AI usage by legal organizations: 26% are now actively using gen AI, up from 14% in 2024.
41% personally using public gen AI tools (ChatGPT, etc.), 17% using industry-specific tools.
95% believe gen AI will be central to workflow within five years.
Common Use Cases for AI
Smokeball:
Primarily legal research (78%), document creation (75%), and e-discovery.
ABA:
Legal research is dominant application for AI tools, used by 35% of respondents. Next most common were case or matter strategy development (23%), understanding judges (17%), and predicting outcomes (13%).
AffiniPay:
Drafting correspondence (54%), brainstorming (47%), general research (46%) and drafting documents (40%).
Thomson Reuters:
Top uses include document review (77%), legal research (74%), summarization (74%), brief/memo drafting (59%), contract drafting (58%).
Barriers to AI Adoption
Common across all reports: Ethical concerns, trust and accuracy issues, confidentiality concerns, regulatory uncertainty.
Smokeball: Ethical concerns prominent (53%), regulatory uncertainty also highlighted.
ABA: Accuracy of AI was the top concern (75%), followed by reliability (56%) and data privacy and security concerns (47%).
AffiniPay: Trustworthiness (42%), ethical issues (42%), privilege concerns (36%), and technological maturity (41%) are primary barriers.
Thomson Reuters: Accuracy and misinformation top concerns; also hesitation due to technology’s maturity level and potential for misuse or “hallucinations.”
Sentiment and Attitude towards AI
Smokeball and AffiniPay: Generally positive, particularly among younger and smaller firms, emphasizing efficiency and productivity improvements.
ABA: Mixed sentiment with notable caution, less enthusiastic compared to smaller firms surveyed by Smokeball.
Thomson Reuters:
Increasing positivity: 55% respondents feel excited or hopeful, up from previous year; declining fear and hesitation.
Professionals see gen AI as transformative, capable of increasing productivity and innovation.
Organizational Policies and Training
Smokeball: Few specifics, but indicated strong individual willingness to learn about AI.
ABA: Little emphasis on policy and training, primarily individual attorney experimentation.
AffiniPay: Policy and training largely absent; 60% unsure when their firms will adopt AI due to training and policy gaps.
Thomson Reuters:
Significant gaps remain; 52% reported no AI policies in place.
Training notably lacking; 64% received no gen AI training at work.
Calls for better governance and systematic training as adoption broadens.
Impact on Business and Client Relationships
Smokeball and ABA: Limited direct discussion of client impact, largely focused on internal efficiency.
AffiniPay: Firms cautious about integrating AI into client work, recognizing potential productivity but uncertain about direct client interactions.
Thomson Reuters:
Many firms haven’t addressed AI’s impact on client pricing or measured ROI (only 20% measure ROI).
Most clients (71% law, 59% tax) unaware whether their firms are using gen AI; substantial gap in client-firm AI discussions.
Indicates potential future friction or lost opportunities in client relationships due to lack of transparency on AI usage.
Alignment Across Surveys
Adoption increasing: All surveys consistently show increasing familiarity and integration of AI into legal workflows.
Use-cases consistent: Legal research, document drafting, and administrative tasks are universally identified as leading applications.
Ethical concerns universal: Ethics, confidentiality, and reliability remain persistent and prominent barriers.
Differences Across Surveys
Adoption pace: Thomson Reuters and Smokeball depict quicker growth and optimism, especially among smaller and younger demographics, while ABA shows slower, more cautious adoption.
Sentiment variability: Thomson Reuters data shows optimism rapidly increasing, whereas ABA respondents remain somewhat skeptical or cautious.
Client interaction: Thomson Reuters highlights a significant gap in communication about AI between firms and clients—a topic not deeply explored in other surveys.
Comparative Summary
Overall, the four surveys paint a coherent picture of a legal profession steadily integrating generative AI into workflows, with smaller firms and younger practitioners typically adopting faster and showing more enthusiasm. Ethical and regulatory concerns are consistent hurdles across all segments. While the Thomson Reuters and Smokeball reports underscore growing excitement and robust adoption, the ABA survey maintains a narrative of caution and slower integration among senior lawyers and larger firms.
Importantly, Thomson Reuters adds a unique perspective on client-firm dynamics, underscoring a critical gap that could impact future adoption strategies and client expectations. As AI becomes increasingly central, strategic implementation, comprehensive training, clear policies, and transparency with clients are identified as necessary next steps across the profession.
This comparative view suggests that while adoption is broadening, meaningful integration into firm strategies and client-facing value propositions remains an important area for growth and improvement.
