Leveraging Legal Technology

You’re reviewing a contract. You pop open your favorite AI chat and type: “What’s a more aggressive indemnity clause here?” A few follow-ups, some back-and-forth, and you've got a solid draft. Fast-forward a few months. That contract is now in dispute. And guess what? Opposing counsel wants your AI chat history. Scary? It should be. In Tremblay v. OpenAI, a federal court confirmed what many feared: AI prompts and outputs can be discoverable. Courts are starting to treat AI transcripts just like emails or memos, i.e. business records subject to eDiscovery. And GenAI isn’t like traditional legal research tools Lexis or Westlaw. These chats often contain: - Client-specific facts - Draft language - Internal legal reasoning ...and are likely not formal work product Here’s what legal teams should do now: 1/ Create a GenAI retention policy, just like you have for emails 2/ Train staff to treat chats like email: intentional, professional, retrievable 3/ Avoid “scratchpad” use for sensitive or strategic work What do you folks think?

AI doesn’t replace legal professionals. It reveals what makes them indispensable. In every wave of disruption I’ve navigated—dot-com, mobile, cloud, now AI—the pattern is the same: technology reshapes how we work, and trust reshapes who leads. We’re entering a new chapter where execution is delegated to machines—and judgment, clarity, and trust become your core deliverables. Trust isn’t a soft skill. It’s a strategic asset. It closes deals. Moves negotiations forward. De-risks decisions at scale. Here’s how high-performing legal teams are making that shift: Certify what you stand for. Great teams don’t just say they’re rigorous—they prove it. Systematized quality builds credibility beyond individual interactions. Leverage AI to buy back time. Use tech for triage—so your attention stays on strategy, not syntax. Benchmark, then brief. Data-backed positions eliminate debate and accelerate alignment. Influence flows from insight, not just instinct. I explore all this in my latest newsletter: AI Doesn’t Build Trust. You Do. (Then Scale It.) It’s about the invisible shift happening in how legal teams lead—and why trust is the next great differentiator. How are you designing for trust at scale? Let’s compare notes. #AI #InHouseCounsel #StrategicLeadership -------- 🚀 Olga V. Mack 🔹 Building trust in commerce, contracts & products 🔹 Sales acceleration advocate 🔹 Keynote Speaker | AI & Business Strategist 📩 Let’s connect & collaborate 📰 Subscribe to Notes to My (Legal) Self

💡 Meet Jon Grainger, our CTO. His mantra: “Governance, not gadgets.” Every law firm says it’s “exploring AI.” In a meeting last week, Jon put it bluntly: “You all want to buy Ferrari engines… without checking if you have brakes.” He’s right. The challenge isn’t shiny tools. It’s trust. Safety. Not getting sued. Here are the 5 guardrails Jon makes us put in place before any AI rollout or pilot: 1️⃣ Safety Is client data truly protected? Where do prompts/outputs live? One leak = career over. 2️⃣ Trust Can lawyers explain outputs to clients and regulators? If you can’t audit it, don’t use it. 3️⃣ Transparency Audit trails: who used what model, when, and why. Optional? No. Survival. 4️⃣ Risk Who owns oversight when AI hallucinates? Define accountability now - or pay later. 5️⃣ Reputation Clients are watching. Regulators are watching. One headline can kill decades of trust. Jon’s built secure systems for 20+ years. His take: “AI can transform legal work – but only if you build the guardrails first.” ⚖️ Start with governance, not gadgets. ⚡ Build confidence before capability. Because when AI fails in law, it doesn’t fail quietly. It fails spectacularly. Publicly. Expensively. 👉 How are you making AI adoption safe and credible? 👉 Jon is at #LegalGeek - catch him at the #DWF stand today. #LegalTech #AI #LawFirmLeadership #Innovation #Governance

🚨 “Why Legal Teams Are Pumping the Brakes on AI Adoption – And What Consultants Can Do About It" 🚨 As a consultant working at the intersection of tech and law, I’ve seen firsthand the glaring gap between the promise of AI solutions (including generative AI) and the cautious reality of in-house legal teams. While AI could revolutionize contract review, compliance, and risk management, many legal departments remain skeptical—and their hesitations are far from irrational. Here’s what’s holding them back: 1. "We Can’t Afford a Hallucination Lawsuit" Legal teams live in a world where accuracy is non-negotiable. One AI-generated error (like the fake citations in the Mata v. Avianca case) could mean sanctions, reputational ruin, or regulatory blowback. Until AI tools consistently deliver flawless outputs, “trust but verify” will remain their mantra. 2. "Our Data Isn’t Just Sensitive – It’s Existential" Confidentiality is the lifeblood of legal work. The fear of leaks (remember Samsung’s ChatGPT code breach?) or adversarial hacks makes teams wary of inputting case strategies or client data into AI systems—even “secure” ones. 3. "Bias + Autonomy = Liability Nightmares" Legal ethics demand fairness, but AI’s hidden biases (e.g., flawed sentencing algorithms) and the “black box” nature of agentic AI clash with transparency requirements. As one GC mentioned recently: “How do I explain to a judge that an AI I can’t audit made the call?” 4. "Regulators Are Watching… and We’re in the Crosshairs" With the EU AI Act classifying legal AI as high-risk and global frameworks evolving daily, legal teams fear adopting tools that could become non-compliant overnight. Bridging the Trust Gap: A Consultant’s Playbook To move the needle, consultants must: ✅ Start small: Pilot AI on low-stakes tasks (NDA drafting, doc review) to prove reliability without existential risk. ✅ Demystify the tech: Offer bias audits, explainability frameworks, and clear liability protocols. ✅ Partner, don’t push: Co-design solutions with legal teams—they know their pain points better than anyone. The future isn’t about replacing lawyers with bots; it’s about augmenting human expertise with AI precision. But until we address these fears head-on, adoption will lag behind potential. Thoughts? How are you navigating the AI-legal trust gap?👇 #LegalTech #AIEthics #FutureOfLaw #LegalInnovation #cmclegalstrategies

Here's the most counterintuitive truth I've learned building AI for family law: The more we automate legal processes, the more 𝘩𝘶𝘮𝘢𝘯 legal services become. Sounds backwards, right? Let me explain: Traditional law firms spend 60% of their time on repetitive tasks: → Document preparation → Case research → Administrative work → Calendar management When AI handles these tasks, something fascinating happens: Lawyers suddenly have space to be... human. They can focus on: → Deep emotional support → Strategic guidance → Creative problem-solving → Building genuine trust The truth? Technology isn't replacing the human element in law. It's 𝘢𝘮𝘱𝘭𝘪𝘧𝘺𝘪𝘯𝘨 it. This is why our AI tools don't just process documents - they free up lawyers to have the difficult conversations, understand the nuanced family dynamics, and provide the emotional intelligence that no algorithm can replicate. What's your take: Could AI actually make professional services more personal, not less? #LegalTech #FamilyLaw #AI #Innovation #FutureOfLaw

Sunday morning thought: One of the more common responses to my viral AI posts has been "AI will get better. Give it time."   I’m not only hearing this from legal tech founders and investors, I’m also hearing it from some lawyers. The assumption is that accuracy improvements will eventually solve the AI trust problem.   But here's what that logic misses: The issue isn't just technological. It's structural.   Even if AI contract review reaches 99.9% accuracy, lawyers still face a binary professional responsibility problem. When you put your name on work, you're either right or you're wrong. There's no partial credit for "the AI was 99.9% accurate."   A medical analogy: A surgeon doesn't get to tell a patient's family "the AI diagnostic tool was 98% accurate, so you can't really blame me for the wrong diagnosis." Professional liability doesn't work on probability curves.   But there’s an even deeper problem: the AI decision-making process remains woefully opaque. Even perfect accuracy doesn't solve the fundamental question: "How do I explain to the state bar why I trusted a system I can't fully understand?"   I've been practicing law for 20+ years. The lawyers who sleep well at night aren't the ones using the most sophisticated tools. They're the ones who understand exactly how they reached every conclusion in their work.   "AI will get better" assumes lawyers are just waiting for higher accuracy rates. But what we really need is transparency in the decision-making process that lets us take full responsibility for the output.   Until AI can explain its reasoning in terms lawyers can verify and defend, the trust gap will persist regardless of accuracy improvements.   What matters more: tools that work 99% of the time, or tools we can defend 100% of the time? #LegalTech #AI #ProfessionalResponsibility  

I learned that the in-house legal team of a legal tech company doesn't trust their own AI software enough to use it themselves. During an interview, I chatted with an engineer who built AI contract review capabilities and an embedded Word add-in. These features complement their existing CLM, so I assumed their in-house legal team would be an ideal audience. This felt like a reasonable assumption, given how much marketing focus has been placed on AI capabilities over the past two years. Yet their legal team's usage was next to none. Not because the technology isn't valuable, but because building AI that legal teams actually trust is incredibly nuanced. Here's the truth: Creating AI for specialized legal workflows isn't just about having the technical capability. It's about deeply understanding how lawyers work, building features they can verify and trust, and earning their confidence through transparency and reliability. Simply being a large incumbent and "adding AI" doesn't automatically translate to user adoption. Trust has to be earned through purposeful design, workflow integration, and a deep appreciation for how lawyers and other business users actually work. At Docsum, this reality drives everything we build. We know that AI in legal tech isn't just a feature checkbox - it's a commitment to building solutions that lawyers will actually trust and use over time.

Will lawyers ever be able to trust AI enough to use it effectively? Really pleased to be featured in The Lawyer discussing with Lucie Cruz how UnlikelyAI is addressing one of the biggest barriers to AI adoption in legal: the hallucination problem. Law firms today are caught between the pressure to innovate and the reality that most AI systems can't explain their reasoning, which is a non-starter for a profession built on accountability. "Nobody wants to be the test case" - I think perfectly captures where the legal industry stands with AI today. At UnlikelyAI, we're taking a different approach by combining neural networks with symbolic reasoning to create systems that can either give you a traceable answer or admit when they don't know. For highly regulated industries, having that auditable trail isn't just nice to have, it's essential for building the trust needed to deploy AI in sensitive tasks. The goal isn't to replace human expertise, but to free lawyers from repetitive work so they can focus on the high-value strategic thinking that clients really need. Exciting to see growing recognition that the legal industry's cautious approach to AI isn't a weakness, it's exactly the kind of rigorous thinking we need to build AI systems worthy of professional trust. I really loved this conversation!! Read it via the link in the comments. #LegalTech #AI #LegalInnovation #FutureOfLaw

I found this compelling thread on Reddit that really resonated with me. If you want lawyers to use your AI product, confidentiality cannot be a side note. It has to be the foundation. A law firm manager shared their experience digging into legal AI tools. What they found was troubling: vague promises, buried disclaimers, and a lack of real security certifications. In legal practice, especially, this is not just a trust issue. It is an ethical one. ✅ Want lawyers to adopt your tool? You must show:  • You are not training on their data  • Data is encrypted at rest and in transit  • Ownership of data remains with the lawyer  • Data location and handling are clearly defined  • All of this is backed by actual audits and certifications My take? Legal AI startups often underestimate how deeply legal professionals scrutinize privacy. Flashy features are fine, but if your terms of service contradict your trust page, you have already lost the room. We are currently building a free data anonymization tool for lawyers. It is a small but necessary step to help legal teams experiment safely with AI. It will not solve everything, but it will reduce friction and build trust from the first interaction. If you are building for this space, ask yourself. Are you designing with real legal constraints in mind, or are you hoping for forgiveness later? #LegalTech #AI #Confidentiality #LegalEthics #Cybersecurity #Startups