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AI Contract Review: Brilliant, Flawed, and Absolutely Essential
Why GLS swears by it — and why you shouldn’t believe the hype without caveats.
5 minutes • 15 Jan 26
Introduction: The Reality Behind the Buzz
AI Contract Review is one of the most exciting developments in legal tech. It promises to accelerate contract analysis, flag risks, and extract key terms at scale. For legal teams under pressure to deliver speed and consistency, the pitch sounds irresistible.
But here’s the truth: most AI contract review tools are brilliant in concept, flawed in execution, and absolutely essential if used correctly. At GLS, we use AI review for every major managed service account — but not in the way vendors want you to believe. We don’t outsource judgment to AI. We use it as a scalpel, not a surgeon.
This piece will tell you:
◼️Why adoption has been slow.
◼️Why generative mark-up isn’t ready.
◼️Why playbooks are the secret weapon.
◼️How GLS uses AI review in practice (and why senior lawyers love it).
◼️Why every legal team should have it — but work within its limits.
The Promise vs Reality
The Promise:
◼️Speed: Review contracts in minutes, not hours.
◼️Risk Detection: Flag deviations from standard positions.
◼️Consistency: Apply playbook rules uniformly.
◼️Scalability: Handle hundreds of contracts simultaneously.
The Reality:
◼️Adoption Lag: Lawyers take time to trust AI outputs.
◼️Generative Mark-Up: Not mature enough for reliable edits.
◼️Playbook Dependency: AI is only as good as the rules you give it.
◼️Training Curve: Productivity gains take months, not weeks.
◼️Cost Sensitivity: Tools only make sense if they’re fabulously cheap.
◼️Human Oversight: PI policies won’t cover AI-only reviews.
Why GLS Thinks It’s Marvellous (But Uses It Differently)
At GLS, we never review a contract without running it through AI tools. Why? Because AI is unbeatable at locating issues scattered throughout a document — indemnities, liability caps, governing law, termination rights. It’s like having a second set of eyes that never blinks.
But here’s the nuance:
◼️We don’t rely on AI for analysis. We use it for issue location and triage.
◼️We deploy it with senior lawyers only — because they know when AI is wrong.
◼️We combine AI with Copilot and ChatGPT, guided by a robust playbook.
◼️We use AI to track patterns across portfolios, not to make judgment calls.
This approach means AI delivers real value without compromising quality.
The Adoption Curve: Why Gains Take Time
AI tools are not plug-and-play. They require:
◼️Configuration: Aligning AI with your playbook.
◼️Training: Lawyers must learn how to interpret outputs.
◼️Iteration: Continuous feedback to improve accuracy.
Expect a lag before ROI. Gains come, but they take patience.
The Risks of Over-Reliance
AI can dull the instincts of junior lawyers. If they stop thinking critically and start trusting AI blindly, quality suffers. AI should augment judgment, not replace it.
PAA:
Does AI review affect junior lawyer development?
Yes, over-reliance can erode critical thinking skills.
Compliance Reality: AI Alone Is Not Enough
Professional indemnity policies won’t cover AI-only reviews. Regulators and courts expect human oversight. AI can assist, but the final call must be made by a qualified lawyer.
The Future: Where AI Needs to Go
For AI contract review to fulfil its promise, it must:
◼️Deliver Generative Mark-Up: Reliable, context-aware edits.
◼️Support Multilingual Review: Beyond English and common law.
◼️Integrate Seamlessly: Plug-and-play with CLMS and workflow tools.
◼️Embed Intelligence: Risk scoring and negotiation suggestions.
Until then, expect incremental progress — not perfection.
Practical Advice for Legal Teams
◼️Start Small: Pilot AI review on NDAs or low-risk contracts.
◼️Build a Playbook: Without it, AI is blind.
◼️Train Your Team: Focus on interpretation, not blind trust.
◼️Combine Tools: AI + Copilot + ChatGPT = best results.
◼️Monitor ROI: Ensure cost aligns with value delivered.
◼️Avoid All-in-One Platforms: Dedicated AI review tools outperform bundled features.
Why Every Legal Team Should Have It
Despite its flaws, AI contract review is essential. Why?
◼️It saves time on repetitive tasks.
◼️It improves consistency across portfolios.
◼️It provides a safety net for risk spotting.
But only if you use it intelligently. Think augmentation, not automation.
GLS Insider Tips: How We Maximise Value
◼️Senior Lawyers Only: They know when AI is wrong.
◼️Playbook Precision: We feed AI detailed risk positions.
◼️Portfolio Tracking: We use AI to spot patterns across hundreds of contracts.
◼️Copilot Combo: AI + ChatGPT + human judgment = unbeatable.
◼️Security Confidence: Data security concerns? Overblown. Major providers invest more in security than most clients ever will.
People Also Ask (PAAs)
1. What is AI contract review?
Technology that uses AI to analyse contracts for risks, deviations, and key terms.
2. Does AI replace lawyers in contract review?
No. AI assists but cannot replace human judgment.
3. Why is adoption of AI contract review slow?
Because lawyers need time to trust outputs and tools require playbook integration.
4. What is playbook-driven AI review?
AI configured with organisational risk positions for accurate analysis.
5. Can AI contract review integrate with CLMS?
Yes, most platforms offer APIs for seamless connectivity.
6. Is generative AI ready for contract mark-up?
Not yet — reliability and accuracy remain issues.
7. What is the ROI of AI contract review?
Depends on volume and adoption; gains take time to materialise.
8. Are AI contract review tools expensive?
They only make sense if priced very competitively.
9. Does AI review affect junior lawyer development?
Yes, over-reliance can dull critical thinking skills.
10. Will AI contract review become standard?
Yes, as tools mature and integrate with broader legal tech ecosystems.
Conclusion: The GLS View
AI contract review is exciting, useful, and here to stay — but it’s not a silver bullet. It accelerates analysis, improves consistency, and provides a powerful second set of eyes. But it requires playbooks, training, and human oversight. It will never replace legal judgment — and that’s a good thing.
Our advice? Adopt AI review, but work within its limitations. Use it for issue location, triage, and efficiency — not for final calls. Combine it with human expertise and complementary tools. And remember: AI is a tool, not a lawyer.
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© The GLS Group - Law Rewritten
Tips & Observations
◼️ AI Review Is Now Non-Optional: At scale, manual contract review cannot keep up with volume, speed, or consistency requirements, making AI assistance a baseline capability rather than an innovation.
◼️ Accuracy Is Context-Dependent: AI performs well on clause identification and deviation spotting, but struggles where risk tolerance, commercial context, or negotiated intent matters.
◼️ False Confidence Is the Real Risk: Over-reliance on AI outputs without human validation can create a misleading sense of assurance and mask genuine legal exposure.
◼️ Training Data Shapes Outcomes: AI review quality is only as good as the contract corpus, playbooks, and fallback positions it is trained against.
◼️ Standardisation Drives Value: The more standardised the templates and clause positions, the more reliable and defensible AI review becomes.
◼️ Edge Cases Break the Model: Bespoke deals, heavily negotiated terms, and novel risk allocations still require experienced legal judgment.
◼️ Speed Gains Are Uneven: AI accelerates first-pass review significantly, but overall cycle time improvements depend on escalation paths and decision ownership.
◼️ Explainability Matters: If lawyers cannot understand why an issue was flagged, trust and adoption deteriorate quickly.
◼️ AI Shifts, Not Removes, Legal Work: Review effort moves upstream into playbook design, risk calibration, and exception handling rather than disappearing.
◼️ Governance Determines Success: Without clear rules on when AI outputs can be relied upon and when human review is mandatory, value erodes fast.
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