LEXITUP’s Post

Not all legal AI is created equal. For in-house teams, it falls into 4 categories with each delivering very different outcomes. Here’s the breakdown from my research into how in-house legal teams are experimenting with GenAI: ⚙️ 1. General productivity AI Purpose: Workplace-wide efficiency boosters, already embedded into familiar tools. Tools: Microsoft Copilot, Google Gemini, ChatGPT, Slack GPT, Notion AI. Outcomes: Faster drafting of emails and board papers, meeting summaries auto-generated in Teams, Excel analysis done in minutes instead of hours. Low barrier to entry → “easy wins” that free up time immediately. 📑 2. Use-case specific legal AI Purpose: Point solutions designed for legal workflows like contracts, discovery, or practice management. Tools: Spellbook, RobinAI, LawGeex, Luminance (contracts); Ironclad, Evisort, ContractPodAI (CLM); RelativityOne, Reveal, DISCO (discovery); Clio, LEAP (practice management). Outcomes: Contract reviews cut from hours to minutes, with risk clauses flagged automatically. Intake, billing, and workflow tasks streamlined so lawyers spend less time on admin. ⚖️ 3. Multi-purpose legal AI Purpose: AI “legal assistants” trained on broad legal datasets, flexible across many tasks. Tools: Harvey.ai, Lexis+ AI, Thomson Reuters CoCounsel, vLex Vincent, Westlaw Precision. Outcomes: Drafting compliance memos, running legal research, or generating first-pass advice notes. These tools act like a “legal co-pilot,” giving lawyers more leverage, but with humans always doing the final check. 📊 4. Precision Analytics & Automation Purpose: Advanced AI for analytics, insights, and high-stakes drafting. Tools: LexisNexis, Thomson Reuters, Harvey.ai, vLex Vincent. Outcomes: Litigation teams predicting case outcomes with data-driven insights. Benchmarking risk exposure across large contract portfolios. Automated but auditable drafting of documents at scale. These tools demand more governance, but the payoff is sharper strategy and better decision support. Bottom line: General productivity AI is the low-hanging fruit. But the real game-changer comes when AI is embedded directly into legal workflows, no matter which category of AI it falls into. Turning administrative tasks and repetitive work such as contract reviews from bottlenecks into value drivers. 👉 Which of these categories feels most relevant for your legal team right now?

At Clario, we’re seeing first-hand how in-house legal teams are starting to explore generative AI, not just as a buzzword, but in practical, category-driven ways. This framework of 4 categories of legal AI is a useful way to cut through the noise. Productivity tools may be the easy wins, but the real transformation comes when specialised platforms are embedded directly into legal workflows. That’s where the conversation needs to shift: not if AI can help legal teams, but how it can be applied with the right guardrails. 👉 Which of these categories do you see making the biggest impact for your team?

Not so secret agent. My Financial Times article about AI agents in the legal sector. The software - also known as agentic AI - is tipped as the next-big-thing in artificial intelligence. It promises to handle ever more complex jobs autonomously and fast. But legal teams are cautious. My 48th article for the FT and my tenth or so about legal tech, which is becoming one of my main specialisms within tech. I spoke to company legal departments using AI agents, tech analysts and suppliers of the tech. There's a lot of hype about artificial intelligence tech in business, including the legal sector. Experts told me that it could be a transformative technology, but also that - as ever in tech - software suppliers' marketing pitches are typically at least two to three years ahead of the norm in business. For big gains in productivity and time savings, companies need to give AI agents autonomy. But few - if any companies - seem willing to do that. Humans fact checkers remain very much "in the loop". #legaltech #AgenticAI #legal https://lnkd.in/eM6gc4xH

From Artificial Lawyer: “Lake Merritt is a new, open source, custom AI evaluation system that helps legal, risk, and product leaders ‘define what good looks like’, or in other words: gauge whether an AI tool works as intended. It’s been developed by Dazza Greenwood, the well-known legal tech expert. “The initial version of Lake Merritt is an Alpha release and is aimed at law firms, inhouse counsel, and regulated industries ‘where risk, compliance, and trust cannot be left to generic benchmarks, [because] evaluation is not just a technical task – it is a strategic function’.” https://lnkd.in/edKtw8w8 #legaltechnology #legaltech Dazza Greenwood

When a law firm hires a new associate, trust doesn’t come overnight. You don’t hand them a client matter on day one and assume perfection. You build trust as they demonstrate accuracy, consistency, discretion, good judgment - and the courage to admit what they don’t know. Why should law firms treat AI different? Law firms face 5️⃣ big challenges with adopting AI today: ⚖️ Accuracy: models that sound right but aren’t. 🔒 Confidentiality: sensitive data sent into opaque clouds. 📑 Consistency: outputs that change from run to run. 🕹️ Control: tools lawyers can’t shape or fine-tune. 👀 Visibility: black boxes that can’t be audited. In my own work designing custom legal AI workflows and processes, I’ve seen these challenges frustrate legal professionals and derail adoption efforts. So how do we try and address this? Running open-source Small Language Models (SLMs) in agentic workflows has been revealing - they’re cheaper, faster, and most importantly predictable and controllable. I can fine-tune them quickly for their specific task, deploy them locally, and know exactly how client data is being handled. Recent research from NVIDIA backs this up: SLMs are often better suited to the repetitive, scoped tasks of agentic systems than massive general-purpose LLMs. (🔗 in comments) But SLMs are only half the puzzle. The other half is evaluation. A new paper from OpenAI and Georgia Tech shows why hallucinations persist: almost every model in use today has been pre-trained to guess rather than say “I don’t know.” Current benchmarks literally reward confident bluffing, which makes hallucinations inevitable. (🔗 in comments) The breakthrough for my workflows comes from putting the two together: • SLMs deliver control, confidentiality, and efficiency. • Better evaluation methods deliver accuracy, consistency, and trust. Together, they form the foundation for each custom Legal AI tool I am building - tools designed for the way lawyers actually work, and built on the principle that “I don’t know” is better than a confident fabrication. Just like a new associate, AI has to earn our trust over time before we should be willing to give it access to our most important and confidential information. I’m curious, 👀 for those already testing AI in practice, which of these five challenges has been the toughest to overcome? If you or your firm is ready to explore smaller, custom, modular, and honest AI systems, let’s connect! #SLMs #LegalAI #OpenSource

As the Financial Times highlights, AI agents are showing strong potential in legal tech—accelerating processes like compliance checks and contract reviews. But challenges around accuracy and liability mean legal teams still insist on human oversight. This reflects a broader truth: in order for AI to scale across the enterprise, it must be both powerful and trustworthy. That’s why at Mindbreeze, we place accuracy, transparency, and context at the center of our AI-powered knowledge management solutions. By grounding responses in enterprise data, we ensure organizations can rely on AI to support critical decisions. Full article available here: https://lnkd.in/ebHGRWqR? #Mindbreeze #EnterpriseAI #DigitalTransformation

Many law firms are now grappling with the growing complexity of piecing together third-party AI tools-because their practice management systems don't include AI natively. This fractured approach-juggling multiple vendors, logins, and workflows-not only increases the risk of inefficiencies but also interrupts seamless legal delivery. LEAP Legal Software ANZ offers a powerful suite of integrated AI tools, all built directly into the platform, eliminating reliance on external add‑ons and keeping efficiency intact. What makes LEAP’s approach stand out: 👩⚖️ LawY - Your trusted AI legal assistant: Draft letters, prepare court documents, conduct legal research and more. Best of all, every answer is verified by qualified Australian lawyers, ensuring accuracy and protecting confidentiality. 📁 Matter AI – Instant insights from your matters: Ask questions, search correspondence, compare documents, summarize folders-and even draft emails or extract key terms-all in seconds, directly within a matter. OCR capability also handles scanned documents and handwritten notes. ✍ Generator & AI Prompts - Matter-specific, high-quality document drafting: Choose from 200+ best-practice templates (affidavits, declarations, letters & more) that auto-fill with matter data. Draft directly in Microsoft Word, refine with chat-style editing, and let AI handle annexures, formatting, and legal structure-fast, accurate, and all in-platform With these tools fully integrated into one cloud-based platform LEAP empowers law firms to achieve increased efficiencies and utilize the power of AI at no extra cost.

Are you using a practice management system that encourages you to use 3rd party AI tools? This can be a dangerous practice for a law firm. Read Jamie’s insightful post below for information on how you can negate your firms risk by using in house built AI by a trusted provider with 30 years of experience. Any questions please reach out to Jamie Ford or myself.

Generative AI hit legal technology a couple of years ago; now AI agents are emerging as a new subset to think about. Agentic AI can perform series of tasks on its own — make decisions, take action or solve problems — and could help hard-pressed legal teams. At least, that is the promise - as this Financial Times piece by Nick Huber puts it; plus oberservations from Salesforce, Eudia, Legora What is the role of the human lawyers? Is the legal industry ready? #legaltech #agenticAI https://lnkd.in/eAyQCsp9

Everyone's been focused on document review in legal AI... But the real “needle pushers” are happening in places you wouldn't expect. Here's what caught my attention from legal AI news this week (sources in the comments and slides): 1️⃣ "Eudia Counsel" launched as an AI-augmented law firm. They're embedding AI directly into legal service delivery, which could reshape how legal work gets done and priced (will hourly billing go extinct?). 2️⃣ GC AI upgraded the Exact Quote feature. When you click on a citation bubble, the original PDF source document slides into the sidebar "like butter" 🧈 to display the original quote. Great way to verify citations. And they welcomed Mary Williams as Head of Marketing to their growing team! 3️⃣ I've been loving the GC legal AI series by Eric Dodson Greenberg on Bloomberg Law. In the 3-part series, Eric breaks down how GCs can leverage AI for their in-house team to become essential drivers of the business. 4️⃣ Exterro rolled out AI agents that work independently on PII detection and compliance tasks. These are autonomous agents operating within defined parameters for GDPR and HIPAA compliance. 5️⃣ Another article I found myself nodding along to (hello legal team metrics!) is titled "Legal Is Already Ahead on AI—It’s Time to Track It with Legal AI KPIs", by Noga Rosenthal. This is how to lead with solid metrics in measuring AI impact. 6️⃣ LexisNexis unveiled Protégé™ AI in PatentSight+. This will helping legal teams make complex patent strategy decisions using plain language queries. 7️⃣ The Legal Engineer role is quickly evolving. Nir Golan from Definely posted a job opening for the first Legal Engineer to join their product team in London. Dream job alert! + More news in the deck. The common thread here is that AI is moving from "helpful tool"… To strategic decision-maker… To autonomous co-worker. We have some ways to go before it's 100% flawless, but I find it interesting to see legal AI develop week over week. Check the slides for more info that signal where legal is headed and don’t forget to get your spot to our virtual Legal + AI summit in October. PS: In a true example of humans "hallucinate" too, I forgot to attach the slideshow the first time around. Here it goes again!