Using AI For Better Legal Analytics

Being the tech-forward lawyer that I am, of course, always exploring what AI can do. BUT I also use AI with my eyes wide-open because I don't want to redo work and don't want to rely on inaccurate improper content. Here are a few specific use cases that have worked for me and a checklist for getting started responsibly: 1. Drafting Routine Agreements Faster Take a simple NDA or basic MSA. I have a template, but often need to make adjustments based on negotiations or other factors. I use Malbek's AI to generate a new draft by giving it given explicit guidelines. Because the AI integrates with Word, I can make edits directly and align the language with our internal templates. It’s not a final product—but it’s a faster starting point, and it cuts down on manual work without compromising review quality. 2. Creating Plain-Language Legal Summaries When I need to explain a complex regulatory update or court decision to our product team, I’ll often use AI to produce a first-draft summary. Again, I never rely on this output blindly—but it speeds up the initial framing. I rewrite it with the business audience in mind, but I’m no longer stuck staring at a blank screen. 3. Reviewing Vendor Contracts for Key Terms When we onboard new vendors, I often review lengthy agreements under tight deadlines. I’ve used AI to extract core clauses—termination rights, notice periods, auto-renewals—into a structured summary. This lets me validate critical terms quickly and spot potential issues without hunting through 20 pages of dense legalese. It doesn’t eliminate the need for review, but it helps me prioritize my time and focus. What I don’t do (yet): -I don’t let AI write legal arguments or regulatory guidance. -I don’t input confidential or proprietary data unless it’s inside an enterprise or securely managed tool. My Checklist: -Choose legal-trained AI tools like one within a CLM like Malbek's. -Use secure, vetted platforms—or redact sensitive data. -Treat AI like a junior analyst: helpful, but not infallible -Always validate legal conclusions before internal or external distribution The bottom line: AI isn’t replacing legal judgment—but it can extend our reach. If it helps me deliver work faster without cutting corners, that’s a meaningful win. If you're experimenting with AI in your legal function, I'd like to know: Where have you seen real value? Where have the risks outweighed the benefits? #legaltech #innovation #law #business #learning

I've been researching ways to improve our Legal Embeddings at Iqidis and I found this really interesting paper, "DB-KSVD: Scalable Alternating Optimization for Disentangling High-Dimensional Embedding Spaces". The paper introduces DB-KSVD (Double-Batch K-SVD), a scalable dictionary learning algorithm designed to disentangle transformer embeddings into interpretable monosemantic features. Instead of sparse autoencoders (SAEs), which dominate the space, they revisit the old K-SVD alternating optimization method and retrofit it with batching, parallelism, and GPU acceleration. The Goal-- Learn an overcomplete dictionary D such that embeddings y = Dx, where x is sparse and ideally corresponds to “monosemantic” features. The fact that two orthogonal approaches (gradient descent SAEs vs. alternating KSVD) converge to similar ceilings hints that the real frontier is not optimization, but representation geometry — how embeddings actually superimpose features. The implications here are massive. DB-KSVD tackles the exact problem legal AI faces: embeddings are entangled and opaque, while law demands traceable, auditable reasoning. This method lets you decompose contracts and case law into sparse, monosemantic legal features (indemnity, jurisdiction, damages) rather than black-box vectors. This will let us show regulators, courts, and clients why the model made a classification, not just the output. In short, it’s a path to auditable, explainable legal AI. This approach can be game-changing for AI in any sensitive domains.

How I Use AI as In-House Counsel Are you one of those attorneys who uses checklists to review an agreement? First, good for you. You're so organized. Second, checklists are perfect for AI! Many attorneys don’t trust AI to review an entire contract yet. But even the most skeptical lawyer can save time by using AI for the more administrative parts of a review. Here’s a real prompt I use with my enterprise-grade Legal AI tool to do a preliminary review of an incoming agreement against my checklist. Step-by-step 1. Upload the contract and your checklist. If you’re using a public model, you might consider prepping the document and/or your system settings. 2. Prompt “# Instructions 1. Perform a comprehensive review of the attached contract using the checklist as a guide. The review should be from the perspective of [party name]. 2. Create a detailed analysis table with these columns: - Checklist Item: Summarize the requirement in one sentence - Contract Language: Exact quotes from the contract - Section: Where the language appears - Analysis: Whether the language satisfies the checklist item - Risk Level: 🔴 High / 🟡 Medium / 🟢 Low or None - Recommendation: How to fix or improve the clause [3. For each checklist item:    a. Identify relevant sections    b. Extract exact quotes with citations    c. Evaluate adequacy    d. Assess risk to [party designation]    e. Recommend improvements] 4. After the table, provide: a. Executive summary of top issues b. Prioritized list of recommended changes c. Any risks specific to [industry] business" 3. Review & Edit Nothing replaces your legal brain. I double-check the analysis, then use the table as a guide for redlining. 💡 Notes 1. Setting up a table in a prompt is a little more involved. Save the prompt so you can reuse the table structure next time. 2. You may not need [Number 3]. If you’re not getting a clear enough response, add in #3 which will give the model more specific instructions. ⚠️ Public Models This one is trickier to use with a public model like ChatGPT, or Claude since you're uploading an agreement. Consider doing the following: 1. Turn off training. For ChatGPT, consider using a temporary chat. 2. Thoroughly redact names and sensitive info and replace them with generic terms. 3. Persona Prompt at the start: “You are an experienced in-house counsel who is an expert contract reviewer.” 4. Consider using a generic account where you haven't already indicated where you work.  5. Use your own judgement as an attorney. Unfortunately, you might not be able to upload an entire contract into a public AI model and protect your data and confidentiality. It might depend on the type of agreement or how well you can redact it. Ultimately, you need to use your judgement as an attorney to determine how extensively you can use AI for this use case. Want help building your own prompt or refining your workflow? Drop a comment.👇 #LegalAI #InHouseCounsel #ContractReview #LegalTech #AI