Reasons Legal Tech Implementations Fail

🚨 “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

⚠️ What’s Actually Getting in the Way of #GenAI in Legal? It’s not the tech. It’s not even the budget. And it’s definitely not about needing another demo. These are my observations after a couple of years in the trenches with law firms and legal departments immersed in #AI #changemanagement: 1. Plain old FEAR: If AI writes it, what is my value add? For many lawyers, their value is tied to the work product—the drafting, the arguments, the detail. GenAI feels like it chips away at that. But it does not. 💡 If done the only way that lawyers can ethically do it, then GenAI doesn’t replace you or your judgment—you control the technology, not the other way around. 2. Lack of STRATEGY: Who’s supposed to lead this? IT? Legal ops? The GC? Everyone assumes someone else is in charge, and nothing moves. 💡 Leaders must lead and assign clear ownership. Give that person or team a budget, a mandate, and the support to make real change. This isn’t just a tech trend—it’s a strategic decision. Vision from the top matters. 3. COMFORT: We’re doing fine as-is. We will ride this wave. The legal industry has been rewarded for inefficiency for a long time (hello, billable hours). But just because something works doesn’t mean it’s future-proof. 💡 The firms rethinking how they deliver legal services—not just how they bill—are the ones pulling ahead. 4. ABUNDANCE of options: We have looked at X, Y, and Z … we are still evaluating. With new tools popping up weekly, it’s easy to get stuck comparing instead of committing. 💡 Sorry, no. You have to start, even if it is with what you already use. Build one meaningful workflow. Learn. Then scale. 5. Not enough TRAINING: We gave people access, but they didn’t use it. Most GenAI pilots fail because training is generic, optional, or just not practical for how lawyers actually work. 💡 Train by role, not features. Show people exactly how it saves them time on their work. 6. Lack of EXPERTISE: We are lawyers, not tech experts. You don’t need a data scientist. But you do need someone who gets AI, prompting, and how to connect tools to real legal tasks. 💡 Upskill your team or hire for AI literacy. ➡️ Bring in help when needed—but aim to build internal capability. 7. RISK avoidance: What if the AI hallucinates? What if it exposes client data? These questions are the strangest concerns for me. Because if any attorney does not protect client data and evaluate output taking all reasonable measures, that attorney is committing malpractice. Period. Full stop. For example, if you are filing briefs without checking all your citations are correct, the problem is not AI, the problem is you. 💡 Don’t freeze—plan. Use sandboxes. Create guardrails. Build trust through policy, not avoidance. 🧩 Bottom Line: GenAI Isn’t a Tool. It’s a Mindset Shift.

Monday morning thought: Legal tech companies have convinced everyone that implementation failures are training problems.   "Your associates just need more training on the AI contract review system."   "Schedule additional sessions on how to use the document automation platform."   "The lawyers aren't getting the full value because they haven't learned all the features."   But what if the problem isn't that lawyers don't understand the tools? What if the tools don't understand the lawyers?   Firms spend months training their attorneys on AI platforms, only to see those same attorneys quietly revert to manual processes because the AI output requires more verification time than it saves.   The training focuses on technical functionality - which buttons to click, which prompts to use, how to interpret the dashboard. But it never addresses the fundamental question: "How do I trust this enough to put my professional license behind it?"   You can train someone to use a tool perfectly and still have them avoid it if the tool doesn't align with how they think and work.   When lawyers have to adapt their judgment, their decision-making process, to accommodate a tool's limitations, the implementation will fail regardless of how much training they receive. #LegalTech #Training #Implementation  

⚠️4 reasons why your legal ops initiative will fail before it begins By their very nature, legal ops projects tend to be high impact, high stakes where the margins for error are small. Yet, they can fall apart before they even get off the ground. Here’s why: 1/ The ‘Why’ Is Missing: Too many legal ops projects kick off with enthusiasm but lack a clear understanding of why they’re needed. It’s not enough to know something’s wrong; you need to pinpoint the problem and consider all options before deciding on a solution. What’s the root cause? Are you solving the right problem, or just addressing the symptoms? Without clarity here, your initiative is set up for failure. 2/ No Buy-In from Stakeholders: You see the value in your project, but what about everyone else? If your stakeholders aren’t convinced, you’re in trouble. They need to feel included, heard, and invested in the project. Without their support, expect resistance—and plenty of it.  Adoption will be a slog! 3/ Vague Expectations and Timelines: Ambiguity is the enemy of progress. Set clear expectations for both people and processes, and adhere to your timelines. Break the project down into manageable steps and demonstrate progress with data. Remember: You can’t improve what you don’t measure. 4/ Ignoring Feedback: Iteration is key. Without a feedback loop, you’re flying blind. Encourage feedback, act on it, and make iterative improvements. This is how good projects become great—and how great projects avoid becoming failures. ❓Ask yourself: Is your project set up for success, or are you heading straight for disaster? 🏆What steps do you take to make sure your initiative is a homerun? #LegalOps #StakeholderEngagement #FeedbackLoop #knowthewhy

😬 Lawyers at Morgan & Morgan got sanctioned in late February for citing non-existent cases generated by their in-house AI database. Of the nine cases cited in the motions, eight were non-existent. ⚒️ This isn't a lesson just about checking case citations— 🚨it's what happens when generative AI implementation goes bad. For in-house counsel 💼, the deeper issue goes beyond fact-checking. It's about how organizations roll out AI tools without proper guardrails. The attorneys admitted it was their first time using the system and didn't verify anything before filing with the court. What can in-house legal teams learn from this? 🧠 1️⃣ AI tools aren't second nature to use. Companies need clear intention behind the how, what, and why of generative AI usage. 2️⃣ If there's a risk someone will use it badly... expect it will happen. Work backwards with training to be proactive. ⚠️ 3️⃣ Change management isn't just for the "innovation team." Legal needs to be involved to spot compliance and operational challenges. 4️⃣ Learning AI fundamentals shouldn't be optional. You wouldn't supervise someone in an area where you lack knowledge—why treat AI differently? 🤔 5️⃣ If AI saved you time creating content, you HAVE enough time to check the sources. Many models can even organize source information in a chart for easier review. ⏱️ 🔖 Bookmark this for later. #InHouseCounsel #GenerativeAI #LegalTech #AIForLawyers #unboxingaiforlawyers #LegalInnovation #LawyersAndAI #AIAdoption #AIinLaw #generalcounsel