What AI Actually Does in LegalTech: 5 Misconceptions We Hear All the Time

AI is a hot topic in the legal field, but it's still shrouded in mystery for many legal professionals. While most understand AI's potential to boost efficiency, the specifics remain unclear. How can legal teams distinguish between AI hype and truly helpful AI solutions?

This post addresses five common myths about AI in legal tech and clarifies the realities.

1. Myth: AI is a chatbot and needs prompts to work.

Reality: Not all AI tools require prompt engineering or chat interfaces. Pattern Data operates behind the scenes, automatically extracting key insights from medical records and legal documents without users needing to type questions. This means less time spent inputting prompts and more time reviewing results that matter.

2. Myth: AI tools make things up (a.k.a. "hallucinate").

Reality: General-purpose AI models can hallucinate, especially when asked to summarize legal rulings or generate citations without reliable sources. Pattern Data addresses this risk through a combination of strategies: grounding outputs directly in case documents, using retrieval techniques to surface the most relevant information, and applying guardrails that catch and correct errors before results are delivered.

3. Myth: AI-generated citations can't be trusted.

Reality: It is true that citations from general-purpose AI tools are often unreliable. Pattern Data takes a different approach. All outputs are tied directly to specific, reviewable sections of your firm's real documents. Nothing is invented, nothing is pulled from the open internet, and every insight can be easily traced back to its source.

4. Myth: AI-generated citations can be trusted once grounded. 

Reality: Grounding is critical, but it is not enough on its own. Even when AI is reading from the correct document, it can still misinterpret or misapply information. Pattern Data strengthens reliability by layering additional guardrails and verification steps on top of the initial outputs. This extra validation helps ensure the information you receive is both accurate and defensible.

5. Myth: AI will replace human reviewers.

Reality: AI can make legal review much faster and more manageable, but it does not replace legal expertise. Pattern Data is built around a human plus AI approach. The AI handles the tedious work, like sorting through thousands of records and identifying key data points, while your team remains in charge of final review and judgment.

In the end, human plus AI is better than human only, which is better than AI only. Combining legal expertise with automation leads to better outcomes, lower costs, and faster case resolution.

How Pattern Data’s AI is Trained

Let’s go a level deeper, because how AI is trained matters just as much as what it does.

• Domain-Specific Training: Pattern Data is trained using real legal and medical records from mass tort cases. That includes diagnosis codes, treatment histories, product names, and timelines that matter for qualifying a claim.
  
  
• Structured Data Extraction: It’s designed to pull structured insights from messy, unstructured files like PDFs and scanned records, transforming what would take hours into usable summaries.
  
  
• Human-in-the-Loop Validation: Humans remain part of the process, reviewing outputs, correcting misclassifications, and ensuring that results are accurate and context-aware. AI gets smarter with every round of feedback.
  
  
• Real-Time Adaptation: As litigation criteria shift or scientific updates emerge, Pattern Data can be updated accordingly, giving your team flexibility without sacrificing accuracy.
  
  
• No External Data Sources: We don’t pull from the internet or generic legal databases. Everything the system processes comes directly from your case files. That keeps outputs reliable, traceable, and private.
  
  

Final Thoughts

It’s easy to think of AI as either magical or unreliable. In truth, it’s neither. The real value of legal AI tools lies in their ability to speed up what humans already do well – without guessing, hallucinating, or taking over your role.

The key is finding the right tool for your workflow. One that’s trained for your case types. One that keeps humans involved. And one that works quietly in the background, so your team can focus on the strategy, not the spreadsheets.

Want to see how this works in practice? Let’s talk.