Hamid Kohan, President & CEO, Legal Soft, author of three books on law firm growth, & a frequent keynote speaker on AI and legal innovation.
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From intake systems to litigation support, AI tools are increasingly embedded in law firm workflows. Yet I think the critical question for firm owners is no longer what AI can do. Instead, the more strategic question right now is: Where does AI create measurable value, and how should firms evaluate it responsibly?
Recent labor data suggests that AI adoption is accelerating across industries. A 2025 survey reported that roughly 20% to 40% of workers are already using AI in some capacity. At the same time, research from the Massachusetts Institute of Technology examining AI and labor market impact found that legal jobs face relatively low direct automation risk and are often concentrated in firms that are actively deploying AI tools. In other words, AI appears to be augmenting legal work more than replacing it.
I see the opportunity, then, is strategic deployment, not blind adoption. Here is a framework for evaluating where AI can fit inside your modern law firm.
Start With Bottlenecks, Not Buzzwords
Before investing in any AI platform, firm owners can identify operational bottlenecks and workflow friction points by asking themselves some questions like: Where are we losing time? Where are we losing money? Where are we losing potential clients? Which tasks are repetitive, rules-based and process-driven?
I've found that AI performs best in structured environments. It struggles, however, in areas that require nuance, persuasion or ethical discretion. Therefore, for most firms, the highest-impact early use cases tend to be in areas like intake and lead response; document review and summarization; medical record collection; and demand drafting support. I recommend adoption beginning at these types of operational friction points rather than basing it on the most impressive demo.
AI-Powered Intake: Revenue Protection First
In high-volume practice areas like personal injury, potential clients often contact multiple firms before retaining counsel. AI intake systems are great for capturing calls 24/7, helping to gather structured lead information. They can also help route urgent matters to live staff and prequalify cases based on defined criteria.
Industry data supports the urgency here. A few years ago, the American Bar Association found that client expectations for rapid responsiveness are continuing to increase, while firms still cite staffing and time constraints as barriers to growth. That said, with these systems, you want to make sure you know how privileged information will be stored and encrypted. Who owns and controls intake data.
I find that intake is often the safest and highest-ROI starting point for AI because it expands availability without compromising legal judgment.
AI For Case Summaries And Document Review
As mentioned earlier, document review and summarization are other strong high-impact early use cases for AI. Attorneys spend a substantial portion of their time reviewing records, medical files and discovery materials.
The Thomson Reuters 2024 "Future of Professionals" report found that AI could save professionals between four and 12 hours, pointing to the fact that much of our current workload is administrative or low-leverage tasks. For example, AI-powered summarization tools can identify treatment gaps, flag missing documents, extract key dates and make large files searchable.
Before implementation, firms should confirm that outputs are auditable (and traceable), that attorneys can verify all extracted conclusions and that the system complies with confidentiality and HIPAA standards. Also make sure that your staff are trained in quality control oversight.
Medical Record Collection: Reducing Administrative Drag
In personal injury practices, record retrieval can take weeks. Automating request workflows and tracking reduces delays and internal labor strain. However, compliance remains critical. Firms should assess things like vendor security certifications, error-handling protocols, matching accuracy rates and audit trails for document requests. In other words, administrative acceleration only creates value if data integrity is preserved.
AI Demand Drafting: Augmentation, Not Automation
In line with AI's strengths, demand letters follow structured formats and rely heavily on precedent and valuation history. AI can assist by organizing case facts, referencing prior outcomes and generating structured drafts.
But, of course, like with the other AI use cases discussed above, valuation strategy requires human discretion. The Stanford Law School CodeX Center for Legal Informatics has consistently emphasized that generative AI performs best in drafting and information synthesis.
Therefore, I find best practice is to use AI for first drafts and factual assembly, maintaining attorney control over valuation and positioning.
Litigation Support: Efficiency Without Abdication
AI systems are increasingly supporting discovery review, deposition summaries and legal research by scanning vast legal databases. Still, overreliance presents risk. Firms should implement safeguards, including:
• Mandatory attorney review of research outputs
• Independent citation verification
• Clear documentation of AI involvement in drafting
• Internal policies governing acceptable AI use
In other words, be sure to treat AI as a research assistant, not trial counsel.
Where Firms Should Be Cautious
Not every legal function benefits from automation. High-risk areas include complex legal reasoning, ethical determinations, settlement negotiations and sensitive client counseling.
Clients retain attorneys for judgment, trust and advocacy, not algorithmic output. Therefore, I believe the firms that succeed will use AI to amplify human capacity rather than attempt to replace it.
A Practical Adoption Roadmap
With all of these use cases in mind, instead of asking, "Should we adopt AI?" firm owners can ask things like: What key performance indicator (KPI) are we trying to improve? Can we pilot this tool in one department first? Who will be accountable for oversight? How will we measure ROI? What is our cybersecurity exposure?
AI implementation should follow the same rigor as hiring a new attorney or opening a new office: clear metrics, supervision and accountability.
The Competitive Divide Ahead
AI is becoming a strategic infrastructure advantage, helping firms reduce administrative work, improve responsiveness and focus on higher-value tasks. The firms that struggle will not be those that avoided AI entirely. They will be those that adopted it without a plan.
Artificial intelligence can be a multiplier of operational efficiency when implemented deliberately. And in an increasingly competitive legal market, disciplined efficiency can be one of the strongest strategic advantages.
