Rather than being a cause for frustration, these limitations are actually valuable for exploring how generative AI can be useful.
The best way to understand and evaluate specialized legal generative AI is to first explore general-purpose AI—not because it works perfectly, but precisely because it doesn’t. Its shortcomings help you identify exactly what domain-specific AI providers are trying to fix.
The imperfections of general-purpose AI are not failures; they’re opportunities. They give you a direct pathway to understanding what you really need from a specialized legal tool.
General-Purpose AI vs. Domain-Specific AI
To fully appreciate the difference, let’s briefly clarify:
- General-purpose AI (developed by companies like OpenAI or Anthropic) is frontier technology designed to handle a wide variety of tasks. It can summarize documents, generate text, analyze data from multiple sources, and even reason out loud to improve its answers. But it also frequently fabricates plausible-sounding yet entirely incorrect information—which is particularly dangerous in legal contexts.
- Domain-specific AI (provided by legal-focused vendors like Jurisage, Casetext, Harvey, CoCounsel, Spellbook, etc.) takes these powerful general-purpose models (sometimes in combination!) and tailors them specifically for legal work. These tools often address key frustrations, such as improving accuracy, reliably handling legal citations, and offering interfaces designed around actual legal workflows rather than just “adding a chatbot.”
The relationship between these two AI types is symbiotic. Understanding general-purpose AI’s limitations clarifies the specific value domain-specific tools provide.
For Legal AI, Let Frustration Be Your Guide
When experimenting with general-purpose AI, you’ll inevitably encounter frustrations. ChatGPT might confidently present you with fictional cases or statutes; a flashy legal AI demo might disappointingly turn out to be just another superficial chatbox bolted onto an existing product.
These frustrations are exactly the experiences you need to identify the kind of tools that will actually deliver value.
For instance, my own breakthrough moment came precisely when I realized that I couldn’t trust ChatGPT to deliver accurate legal facts. Paradoxically, that limitation was liberating. Once I stopped expecting accuracy from ChatGPT, I learned to leverage its real strength: reorganizing my own facts and ideas into coherent, flowing narratives. The flaw became my guide.
In turn, that gave me the clarity to understand what I would need as a litigator leveraging AI — tools that would understand the totality of the documents I dealt with, and that would integrate facts and case law while still helping me assemble my thoughts.
Good News: Traditional Acquisition Frameworks Still Apply
For law firm administrators and tech buyers, here’s the reassuring part: although curiosity is an essential part of the evaluation process, it doesn’t mean that you should spend a lot of money on lots of tools just to see what works. Despite the rapid evolution of AI, the core principles of technology acquisition haven’t changed.
The widely accepted People-Process-Technology framework remains valid. Understanding the processes that tech needs to improve and knowing how your people will engage with new tools remains the critical first step. AI doesn’t disrupt these fundamentals—it just underscores their continued importance.
AI may be revolutionary, but good technology purchasing habits remain reassuringly stable. What is new—and now necessary—is coupling this trusted approach with intentional curiosity-driven exploration.
Questions to Guide Your Exploration of AI for Lawyers
Your best approach to AI exploration is to channel curiosity deliberately. Here’s a practical set of questions you should ask yourself as you engage with general-purpose tools:
- What specific frustrations have I experienced using general-purpose AI (like ChatGPT)?
- What do these frustrations suggest about the capabilities I genuinely need from a specialized legal AI tool?
- Could I achieve similar outcomes with general-purpose AI, or does the specialized tool truly offer meaningful advantages, such as improved accuracy, citation handling, or workflow integration?
- When is an imperfect, “almost-always-right” output acceptable, or even beneficial, and when does it become too risky?
To illustrate, one Jurisage customer shared with us how our AI-generated case summaries, despite occasionally needing minor edits, proved incredibly valuable precisely because the lawyers already knew the cases and primarily wanted quick, editable drafts to streamline their work.
Curiosity, rather than caution, unlocks these insights.
Embrace Curiosity—It’s Your Best Asset
It’s completely okay—even necessary—to slow down, experiment, and explore. Nobody fully knows yet exactly how generative AI will reshape legal practice. Precisely because of this uncertainty, curiosity-driven exploration is essential.
The rapid evolution of AI favors legal professionals and administrators who remain curious, flexible, and open-minded. Rather than chasing vague promises, slow down enough to thoughtfully experiment and learn firsthand where and how AI can add real, practical value to your daily work.
Turning down the hype means turning curiosity up. After all, curiosity is precisely what’s going to position your firm to adapt confidently in a rapidly changing AI landscape.