By Lars Mahler + Buddy Broussard, LegalSifter.
As generative AI becomes more accessible and widely adopted, it’s tempting to believe a tool like ChatGPT can handle just about everything, including contract review. After all, it can draft, summarize, and translate language quickly and convincingly.
But reviewing contracts isn’t just about processing language. It’s about enforcing standards, managing risk, and scaling legal operations with confidence. Reducing exposure, accelerating business, and handling contract volume at scale isn’t just a legal challenge; it’s an operational one. And solving it takes more than a generalist AI.
Consistency in Contract Review Is Non-Negotiable
Contracts govern how your business operates: revenue recognition, liability limitations, service obligations, and more. Reviewing them consistently isn’t just a legal best practice; it’s a business imperative.
General-purpose AI tools introduce variability, not structure. Five users might prompt ChatGPT with the same task and get five slightly different answers, some of which could be incomplete or misaligned with internal policies. Inconsistent reviews create delays, missed obligations, and unintentional risk.
That’s why consistency, often taken for granted in mature legal workflows, becomes one of the first casualties when AI is implemented without discipline.
Why General-Purpose AI Falls Short in Contract Review
Even advanced generative AI has limitations when applied to high-stakes legal processes:
No Organizational Context: These models don’t understand your specific risk posture or contracting strategy.
No Playbook Enforcement: While you can provide guidelines, enforcement is not built in. The AI “guesses” how to apply them.
No Repeatability: Ask the same question twice and get different answers.
No Audit Trail: There’s no way to trace how a decision was made or ensure it aligns with compliance standards.
Data Security Concerns: Using public tools may raise issues around confidentiality, compliance, and data governance.
And while some legal tech providers attempt to bridge gaps in general-purpose AI by layering on plugins, crafting custom prompts, or applying fine-tuning, these workarounds often introduce complexity without delivering consistent results. They require ongoing maintenance and still lack the integrated logic and legal domain expertise needed for contract-specific reliability.
In short, applying inherently variable tools to processes that require consistent, explainable outputs undermines trust, repeatability, and control.
What to Look for in a Contract-Specific AI Solution
The most effective contract review systems are built with legal precision, operational scale, and business reliability in mind. Here’s what sets them apart:
1. Time-Tested, Contract-Specific AI
Look for contract-specific AI that combines years of legal domain expertise with modern prompt-based techniques. These tools should identify, flag, and suggest edits with 95%+ accuracy, aligned to your own legal playbooks.
A mature AI solution should, for example, be able to distinguish a warranty clause from an indemnity obligation, understand typical risk markers, and adapt to a broad range of contract types without missing nuance.
2. Embedded Playbook Logic
A true enterprise-grade solution allows your playbook to be formally encoded into the system, ensuring that every contract is reviewed against the same standards, without relying on individuals to remember or interpret policies on their own. This eliminates ambiguity and delivers consistency at scale.
The best tools don’t just suggest edits; they apply your organization’s positions directly from your playbook, producing redlines that are aligned with policy from the very first review.
3. Operational Guardrails
The right platform should offer explainable outputs and traceable decisions. This means users can understand not just what the AI recommends, but why. This transparency supports better governance and more confident decision-making.
Think of it as moving from “AI guesswork” to “AI you can govern,” where every redline is backed by reasoning.
4. Enterprise-Grade Security
Contract data is sensitive by nature. Ensure any platform you use meets enterprise standards for data security, confidentiality, and compliance, and that your data isn’t used to train third-party models.
Security should be more than a checkbox; it should be a cornerstone.
5. Human-in-the-Loop Expertise
Even with powerful AI, legal expertise remains essential. A robust solution keeps legal professionals at the center of the process, augmenting their review capabilities rather than replacing their judgment.
AI should act as a co-pilot, not an autopilot.
💡Use the checklist to evaluate whether a solution offers the control, consistency, accuracy, and transparency your team needs: What to Look for in an AI Redline Solution
Consistency Is a Business Advantage
Inconsistent contract review doesn’t just create legal risk. It also:
Slows down negotiations
Increases time to onboard new team members
Contributes to missed obligations and financial exposure
By choosing a purpose-built, contract-specific solution, organizations gain speed and control, ensuring every contract aligns with internal standards, no matter who’s reviewing it. This consistency isn’t just operationally efficient; it’s a strategic asset. When everyone plays by the same rules, you reduce confusion, accelerate deals, and establish greater trust with internal and external stakeholders alike.
Tools like ChatGPT offer promise, but in high-stakes contract review—where clarity, consistency, and compliance are non-negotiable—general-purpose AI falls short. Only platforms purpose-built for legal work deliver measurable value where it matters most: faster turnaround times and more predictable outcomes.
Contract Review at Scale Requires Purpose-Built AI — Meet LegalSifter ReviewPro™
Generative AI has made it easy to suggest edits, but hard to trust them. Most tools rely on improvisational chat or flashy demos. LegalSifter ReviewPro is different: it’s purpose-built for contract review, combining domain-specific intelligence, structured playbooks, and controlled use of generative AI.
The result? Redlines professionals can explain, defend, and rely on, delivering the speed of automation with the rigor of human judgment.
Learn how ReviewPro delivers redlines that are fast, fluent, and always in your control.
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About the Authors:
Lars Mahler – As Chief Science Officer and Co-Founder of LegalSifter, Lars has shaped the evolution of AI-powered contract review through his visionary leadership and deep expertise in natural language processing. The architect behind ReviewPro, LegalSifter’s proprietary AI redlining tool, Lars combines over a decade of contract-specific AI research with rigorous enterprise-grade engineering.
Buddy Broussard – As Vice President of Solution Architecture and ReviewPro at LegalSifter, Buddy brings more than three decades of experience transforming how organizations manage contracts. His current focus is on ensuring clients get immediate value from ReviewPro by delivering playbooks that are thoughtfully crafted, clearly positioned, and ready to perform out of the box.
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[ This is a sponsored thought leadership article for Artificial Lawyer by LegalSifter. ]
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