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🇺🇸 22 Boston Wharf Rd, Boston, MA 02210
🇬🇧 2 Pear Tree Court, London EC1R 0DS
© 2025, Juro. All rights reserved.
🇺🇸 22 Boston Wharf Rd, Boston, MA 02210
🇬🇧 2 Pear Tree Court, London EC1R 0DS
© 2025, Juro. All rights reserved.
Artificial intelligence (AI) is reshaping the legal industry. From contract review and knowledge management to predictive analytics and compliance, legal AI promises faster turnaround times, reduced costs, and more strategic work for lawyers.
But while the opportunities are significant, the risks are also well-documented. Research from Gartner suggests that up to 85 per cent of AI projects fail to deliver business value. Legal is no exception.
Firms and in-house teams rushing to adopt AI often encounter stumbling blocks — and the fallout can be expensive, time-consuming, and at the expense of future confidence.
That isn’t to say you shouldn’t be adopting legal AI. Our view is that you absolutely should. It’s a competitive advantage, and one teams like yours can’t afford to neglect. But we are saying that you need to give legal AI implementations the love and care they deserve. Otherwise, you risk becoming part of those 85 per cent of failed deployments.
In this article, we’ll examine the seven deadly sins of legal AI adoption. For each, we’ll explore the underlying problem, share examples of how teams fall into the trap, and offer practical steps to ensure your legal AI initiative drives real, measurable value.
Legal AI is everywhere. It’s in conference agendas, boardroom conversations, and LinkedIn posts. With so much noise, it’s tempting for legal leaders to buy the first shiny product that promises to fix all of their problems with AI.
The problem is that hype-driven decisions rarely solve the real issues. Tools land in the workflow without a clear use case, and adoption fizzles. By failing to anchor legal AI to tangible business outcomes, legal ends up right back where it started, except with less budget and more skepticism to overcome next time.
In our recent podcast episode, Lucy Bassli, explained this brilliantly:
Even the most powerful AI won’t succeed if humans resist it. Lawyers are trained to be risk-averse, skeptical of black-box outputs, and protective of their methods. Without thoughtful change management, AI adoption can spark backlash, low usage, and wasted investment.
AI is only as good as the data you feed it. If your contracts are scattered across inboxes, shared drives, and half-baked PDFs, don’t expect accurate outputs. Poor data undermines trust, and when lawyers don’t trust the tool, they stop using it.
For most legal teams, the real challenge isn’t deploying AI — it’s getting their contract data into a clean, structured state first.
With Juro, you don’t have to wrestle your contracts into structure manually. Every agreement created and managed in Juro is stored as structured data from day one, and with AI Extract, key fields and dates are captured automatically. That means consistent, searchable, and trackable contract data — without hours lost to manual clean-up.
Hit the button below to see Juro’s AI extract functionality in action.
Too many AI initiatives stop at implementation. The tool is live, but nobody tracks whether it’s delivering real value. When budgets tighten, these unmeasured projects are the first to go. That’s why ROI can’t be an afterthought.
For AI to stick, legal teams need to show how it impacts the metrics the business actually cares about: faster revenue recognition, lower outside counsel spend, and fewer contracts slipping through unnoticed.
But whatever you do, be realistic about when ROI will become apparent. While some tools deliver significantly faster implementation than legacy CLM vendors, these workflows still deliver incremental value over time, and to measure ROI reliably, you need to factor this continuous upside into the equation.
As Stephanie Corey, Legal Ops expert, shares:
The legal AI market is evolving at breakneck speed. Tools that can’t scale or integrate with your broader tech stack risk becoming obsolete within a year, and you’ll be back to square one, except this time fighting for budget that’s locked into costly contracts with point solutions that no longer deliver the promised value.
The cost of switching tools — retraining staff, migrating data, rebuilding workflows — can be enormous. Future-proofing decisions today saves huge headaches tomorrow.
For example, imagine that a legal team chooses an AI tool that doesn’t integrate with Salesforce or Slack, despite these systems being the source of truth for their organization. Within 18 months, adoption collapses because the tool doesn’t fit how the business works, or it causes too much disruption.
Oftentimes, evaluating legal AI solutions is actually about going back to basics and understanding which foundations are needed for the AI element to excel. Integrations are a huge piece of the puzzle.
Contracts hold some of the most sensitive information a business has: pricing models, liability terms, customer details, employee agreements, and confidential IP. When you push this information through an AI tool, you’re trusting the vendor with data you simply cannot afford to compromise.
If you fail to scrutinize how AI tools handle that data, the risks are enormous. A vendor without robust controls could mishandle storage, transmit data through unsecured channels, or even use your contracts to train their models without consent. The fallout could include regulatory penalties, reputational damage, and a serious loss of trust from customers and counterparties.
That’s why security can’t be an afterthought — it has to be the very first conversation you have with any AI vendor.
AI is powerful, but it isn’t a lawyer. It can speed up repetitive work — flagging risky clauses, checking contracts against playbooks, extracting key terms — but it can’t negotiate with counterparties, interpret ambiguity, or weigh commercial risk.
The problem comes when teams buy into “lawyer in a box” marketing and expect automation to handle judgment-heavy work. Inevitably, the tool underdelivers, confidence erodes, and adoption collapses.
The legal teams who succeed are the ones who frame AI as an assistant. It takes on the heavy lifting, while humans stay in control of decisions. That balance builds trust and ensures adoption lasts.
Avoiding the seven deadly sins of legal AI adoption isn’t only about avoiding bad habits — it’s about building on the right foundation. AI is only as effective as the system it runs on. If your contracts are scattered, your processes inconsistent, and your data unstructured, even the smartest AI won’t deliver value.
That’s why legal teams who succeed with AI don’t start with AI. They start with a contract lifecycle management (CLM) platform that gives them control over their contracts, data, and workflows — then layer AI on top to accelerate what already works.
Juro is that foundation:
With Juro, legal teams aren’t gambling on hype-driven point solutions. They’re adopting AI with confidence — embedded into their contracting workflows, powered by clean data, and tied directly to business outcomes.
Book a demo below to discover how forward-thinking legal teams are embedding AI into their contracting foundations with Juro.