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Welcome to episode 342 of Grow Your Law Firm, hosted by Ken Hardison. In this episode, Ken sits down with Timothy Hiller, Partner at Hiller Comerford Injury & Disability Law. Tim shares how his firm is using AI to support a high-volume Social Security disability and VA practice while continuing to grow its personal injury department.
The conversation explores how AI can help law firms build custom tools, streamline document-heavy work, improve financial forecasting, and reduce repetitive operational tasks. Tim also explains why firms need clear policies around data privacy and attorney review, how to communicate AI adoption to employees, and why he sees AI as a way to increase capacity and compete, not as a reason to reduce staff.
What you'll learn in this episode:
1. How to Start Using AI in Your Firm
- Why law firm owners should experiment with AI tools before deciding to implement them
- How everyday use helps leaders understand what AI can and cannot do
2. Building Custom AI Tools Without a Large Development Team
- How Claude Code can help firms create custom lead-generation tools, calculators, and dashboards
- Why firms can use AI to build solutions that better fit their specific practice areas
3. Using AI for High-Volume, Document-Heavy Cases
- How AI can help summarize and organize large medical and administrative records
- Why attorney review remains essential before submitting AI-assisted work to a court
4. Protecting Client Data and Managing Risk
- Why firms should understand enterprise agreements and data privacy before using AI with client information
- How internal AI policies can help prevent inaccurate filings and avoidable mistakes
5. Helping Employees Adopt AI
- Why firms should present AI as a capacity-building tool rather
How AI Helps Law Firms Handle More Cases With Timothy Hiller
This episode is about how one large disability law firm is using artificial intelligence, or AI, as a practical work tool rather than as a futuristic gimmick.
Aron Hiller explains that his firm is not mainly using AI to replace lawyers or staff. Instead, they are using it to help them do more work, build internal software faster, sort through huge amounts of legal records, and reduce repetitive tasks. He also talks about the risks, especially privacy concerns and the danger of trusting AI output without checking it.
A second big theme is management: how do you introduce AI to employees without making them think, "This machine is here to take my job?"
AI is helping this law firm build custom tools without depending so much on outside vendors or software consultants. Aron says tools like Claude Code let even non-programmers create useful internal software by describing what they want in plain language. That means the firm can make things like lead-generation tools, dashboards, and case-screening tools much faster and more cheaply than before.
The most important legal use case he describes is handling giant case records. In disability law, especially in federal court appeals, lawyers may have to review transcripts that are 1,000 to 3,000 pages long, and sometimes much more. AI helps turn those huge records into a usable written summary called a statement of facts, which is a standard part of a court filing. That saves lawyers from one of the most painful and time-consuming parts of the job.
But Aron is very clear about one limit: AI cannot be trusted blindly. His firm has a rule that no AI-generated work can be submitted unless a human independently checks that it is accurate. That matters because lawyers can get in serious trouble if they file false or invented information.
He also believes AI may change the whole software landscape for law firms. Today, many firms rely on rigid case-management systems where people click through menus and forms. In the future, he imagines a setup where much of the firm’s information sits inside an AI-powered system, and people simply ask questions in normal language to get what they need.
Another key point is that AI may change hiring, but not always through layoffs. Aron frames it as a growth tool. If a firm becomes more efficient, it may serve more clients and expand faster, rather than just cutting staff. That is an important business point: efficiency does not always mean fewer jobs; sometimes it means more output with the same team.
He also emphasizes that law firm owners should personally experiment with AI. His view is that leaders should not outsource their understanding of it. By using the tools themselves, they learn what AI is good at, what it is bad at, and how to explain it responsibly to employees.
Finally, the episode treats AI as something ordinary and usable, not magical. Aron’s basic message is: if you know how to ask a question, you can start using AI.
This episode matters because it shows a realistic version of AI adoption in professional work. It is not about robots replacing everyone overnight. It is about using AI to reduce drudgery, speed up internal software building, and help skilled professionals handle large, repetitive information problems.
It also matters because law is a high-stakes field. If AI can help with huge records and repetitive drafting, that is valuable. But if lawyers trust it without checking, the consequences can be serious. So the episode lands on a practical middle ground: use AI aggressively where it helps, but keep humans accountable.
More broadly, the interview suggests that the biggest advantage may go to firms that learn early, experiment carefully, and stay flexible. In plain English: the people who understand these tools first will probably work faster, make better decisions, and compete better than the people who keep ignoring them.