Embracing Generative AI for Law

Key takeaways:

• High-performing legal teams gain their edge by embracing transformative technology.
• Generative AI automates repetitive tasks, freeing lawyers to focus on strategic work.
• Use cases include document generation and review, legal research, compliance monitoring, risk mitigation, and contract lifecycle management.

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What sets high-performing legal teams apart from those constantly playing catch-up?

It’s not about working longer hours, typing faster, or hiring more people.

The real difference is in their mindset. The most effective teams are the ones embracing technology that redefines how they work, starting with generative artificial intelligence (AI).

While some legal departments are still debating whether AI has a place in their workflow, others are already transforming theirs and reaping the many benefits. These teams are drafting contracts in minutes, reviewing complex documents with speed and accuracy, and researching case law with unmatched precision.

Why? Because they recognize what others haven’t yet: The legal field is uniquely positioned for AI-driven transformation, with 96% of legal professionals agreeing that AI has helped them achieve business outcomes more easily.

What is generative AI for law?

Generative AI for law is artificial intelligence that can draft legal documents, analyze contracts, research case law, and generate legal analysis—essentially automating the creation of legal documents that traditionally required hours of manual effort.

Unlike traditional legal software that simply stores and organizes information, generative AI creates new content from scratch. Think of it as having a brilliant legal assistant who can draft, analyze, and synthesize complex legal information in record time.

Here’s what makes generative AI particularly powerful for legal work: It combines the pattern recognition capabilities of machine learning with the creative output of natural language generation.

The result? AI that can draft employment agreements with state-specific variations, summarize complex depositions into actionable insights, research legal precedents across multiple jurisdictions, and generate legal arguments supported by relevant case law, all while maintaining the precision and accuracy that legal work demands.

Interestingly, Deloitte found that legal, compliance, and risk functions ranked second only to technology functions for areas of the business most actively pursuing opportunities to implement generative AI. While there’s definitely a rise in general ChatGPT and other model usage, we’re also seeing the emergence of a customized GPT for lawyers. This GPT is fine-tuned on vast amounts of legal data, helping lawyers perform specific tasks like drafting, reviewing, and analyzing documents.

By 2030, McKinsey predicts that 30 percent of current hours worked could be automated, and accelerated by generative AI, but that reality seems much closer for the legal industry.

How generative AI works in legal practice

Wondering how to get started with generative AI for legal work? These applications represent the most impactful starting points for legal teams ready to scale their output while maintaining precision.

The underlying technology

Generative AI relies on large language models (LLMs) trained on vast datasets of legal documents, case law, and legal precedents. These models learn patterns in legal language, understand context, and can generate new content that follows legal conventions and requirements.

Think of it like this: Instead of manually reading through every line of a contract until your eyes cross, AI has already analyzed millions of legal documents and learned the patterns that make contracts effective. It can then generate new documents that incorporate these learned patterns while adapting to your specific requirements. This type of AI content generation for legal workflows helps legal teams move faster without sacrificing accuracy.

How can I use generative AI in legal work?

In practical terms, generative AI for law refers to systems that can take a simple prompt like “draft a standard NDA for a technology vendor” and produce a complete, legally sound document in minutes. These systems can analyze a 50-page merger agreement and generate a detailed risk assessment highlighting potential issues with specific clause recommendations. They can review hundreds of contracts to identify non-standard terms, inconsistent language, or missing provisions, all tasks that would typically require days of manual review.

What is the best way to use generative AI for legal tasks? These use cases represent the most impactful starting points:

Contract generation

Use generative AI to draft contracts from scratch using pre-approved templates and clause libraries, reducing time spent on repetitive first drafts.

Contract review and redlining

Analyze incoming contracts to flag non-standard terms, suggest redlines, and ensure alignment with company policies and fallback positions. 28% of legal professionals who took our survey said that contract review is their most impactful AI use case.

Legal research

Summarize case law, regulations, and jurisdiction-specific rules in plain language to accelerate legal analysis and memo drafting. Quickly search for and reference contracts and other documents using a CLM repository.

Compliance monitoring

Automatically detect risky or non-compliant language, monitor for clauses like auto-renewals, and trigger workflows to meet internal and regulatory requirements.

Cross-functional communication

Generate clear, legally accurate summaries or guidance for business teams to support faster decision-making without overloading legal.

When asked about their most frequent AI use case, here’s what legal professionals, both in-house and private law, had to say:

With contract review, creation, and analysis emerging as the most impactful use cases, it’s clear that legal teams are consistently seeing meaningful benefits from generative AI across the contract lifecycle.

What are the benefits of generative AI for legal teams?

Maybe you’re thinking, “This sounds impressive, but what are the real-world benefits?” Let’s explore how generative AI solves actual challenges that legal teams face every day.

Using AI for legal content generation

Drafting contracts from scratch is one of the most time-consuming tasks legal teams face, especially when the agreements are routine, like NDAs, vendor agreements, or employment contracts. Generative AI dramatically speeds up this process by using pre-approved templates and clause libraries to produce high-quality first drafts in minutes.

Instead of starting with a blank document, you can simply input a few key variables—like jurisdiction, party names, or agreement type—and AI content generation creates a tailored draft based on your organization’s standards. It’s like having a virtual legal assistant that knows your playbook and never misses a detail.

This not only reduces the time spent on repetitive contract generation, but also lowers the risk of inconsistent language, missed clauses, or outdated terms. For busy legal teams, it means fewer bottlenecks, faster turnaround times, and more capacity to focus on strategic work.

Using AI to improve contract review accuracy

To improve accuracy, legal teams train generative AI on their contract playbooks—collections of preferred clauses, fallback positions, required terms, and redlines. Once trained, the AI can consistently apply these standards across every contract it reviews.

For example, you can configure the system to identify:

• Preferred language, like specific indemnity and limitation of liability clauses
• Required terms, such as data privacy or termination for convenience
• Prohibited clauses, including auto-renewals or uncapped liability
• Pre-approved fallback positions to use during negotiations if preferred terms aren’t accepted

Once these rules are in place, the AI acts as a first line of defense. It flags deviations from your policy, suggests edits, and ensures formatting and structure are consistent, helping you catch issues that might be missed in manual reviews. This level of consistency improves quality and reduces risk across your contract portfolio.

Using generative AI to save time on reviewing contracts

Once the AI system is trained on your organization’s standards, it can drastically reduce review time by handling the initial screening process.
For instance, if you have a backlog of third-party vendor contracts, you can upload them into the system for review. The AI scans each contract, compares it to your playbook, and flags any discrepancies, such as unusual payment terms or missing compliance language. It can also generate summaries of key risks so your legal team can quickly prioritize where human review is most needed.

By automating these early review steps, generative AI allows you to move through contracts in a fraction of the time, reduce bottlenecks, and keep pace with business demands, all without sacrificing precision.

To see how your contract processing times compare to others in your industry, download our 2025 Contracting Benchmark Report.

Using generative AI to improve client and cross-functional relationships

Think about what’s top of mind for your company this year—likely it includes delivering faster, more efficient service to internal clients and becoming less of a bottleneck for cross-functional partners. Generative AI strengthens internal relationships by helping legal teams respond to business requests more quickly and communicate more thoughtfully. Instead of delivering dense legal language or long turnaround times, legal can use AI to draft responses that are clear, tailored, and aligned with the needs of internal clients.

For example, AI can help you:

• Translate legal guidance into plain language that is easier for business partners to understand and act on
• Craft collaborative language that preserves positive relationships, even when pushing back
• Respond faster to questions or contract feedback, reducing legal bottlenecks during sales or procurement cycles

This means your stakeholders don’t just get faster answers—They get better ones. In fact, 64% of legal professionals report that AI helps them communicate better with stakeholders.tion. Automation and integration make the work feel cohesive, and the emergence of artificial intelligence (AI) in legal tools is the next wave of development.

By offering legally sound alternatives and helping reframe complex messages, AI does more than save time. It helps legal show up as a collaborative, solutions-oriented partner across the business.

Using generative AI to scale your team

Here’s what every general counsel wants to hear: it is possible to manage growing legal workloads without constantly increasing your team’s headcount.

You can scale your team by using generative AI to automate workstreams that normally require extra hires, like bulk contract generation, mass edits, and managing routine approvals. Instead of having someone on your team manually create the same contract with every new opportunity, AI can produce, populate, and prepare drafts for review based on your input variables, like party names or contract type. The result is more output without burning out your team or extending turnaround times. 76% of legal professionals say that AI reduced their feelings of burnout, a number that will likely increase as more companies adopt AI legal tools.

Generative AI also gives legal teams the flexibility to expand their capacity during busy periods such as mergers, funding rounds, or contract renewal season, without the cost or delay of hiring additional full-time employees.

NEXT Insurance is a great example of this in action. After implementing a contract lifecycle management system with generative AI tools, they were able to keep pace with contract volume despite being short-staffed. As Nadia Louis Hermez, their Legal Operations Manager, shared, the AI was “helping us review contracts quickly and efficiently, even though we are down a headcount.”

For legal teams looking to stay lean while meeting rising demands, generative AI offers a practical and scalable solution.

Using AI to mitigate risk and improve compliance

Generative AI helps enforce compliance by learning the rules and requirements your legal team sets, such as preferred terms, clause placement, and approval thresholds. Once trained, the AI checks each incoming contract to make sure it follows these standards. It can identify missing protections, out-of-policy language, or risky clauses, and then trigger workflows to prevent those contracts from moving forward until they are corrected. This allows your team to identify risks before they escalate, automate compliance reviews, and create a clear audit trail for every decision.

Using generative AI to create strategic value

Because AI can handle high-volume, repetitive tasks like contract generation and review, legal professionals are empowered to shift their time and energy toward more impactful work. Instead of getting buried in routine work like document review or redlining, lawyers can focus on shaping legal strategy for major deals, advising leadership on risk, strengthening client relationships, or improving internal processes like contract turnaround times. By handling the repetitive work, AI gives lawyers more capacity to think creatively and act as true business partners.

Using generative AI to make data-backed decisions

To make smarter decisions, legal teams can use generative AI to extract and analyze patterns from contracts, negotiations, and operational data. AI can surface contract benchmark metrics like:

• Percent negotiated
• Percent on counterparty paper
• Amount of legal involvement
• Average days to execute

It can also help identify common redline points, frequently negotiated clauses, and which contract terms are most often rejected. These insights help teams identify bottlenecks, reduce friction in the deal cycle, and proactively manage risk.

AI can also analyze performance across vendors, partners, and contract types to help with forecasting and resource planning. For example, it might highlight that contracts with a particular supplier consistently trigger escalations or delays, helping your team decide where to focus negotiation or process improvements.

AI generates insights from your legal data that would be near impossible to identify manually. It can analyze contract performance, identify trends in legal issues, and provide metrics that help legal teams make more informed decisions about resource allocation and risk management.

Real-life use cases of generative AI for law

With the right setup, generative AI becomes more than a productivity tool. It becomes a safeguard, helping legal teams manage risk across the entire contract portfolio—without relying on manual review alone.

Preventing revenue leakage

Organizations lose an average of 8.6% of total spending annually to cost leakage in contracts, so it’s no surprise that revenue protection and cost control are top of mind. Generative AI helps tackle both by identifying and fixing contract terms that could result in lost income or excess spend, making AI-powered contract management a critical priority for modern legal and procurement teams.

AI helps prevent revenue leakage by scanning contracts for identifying and fixing contract terms that could lead to lost income. This includes spotting pricing errors, outdated terms, and catching auto-renewal clauses. Then, it can recommend edits or trigger the correct approval flow before the contract goes out the door, helping ensure no money is left on the table.

For example, Docker used a CLM with AI to gain better visibility into their contract portfolio, which ultimately helped prevent deals from going through with outdated pricing and terms.

“It could have come back to bite us if we missed those details that [a CLM with generative AI] now catches automatically,” said Becca Soch, CLM Data and Automation Manager at Docker.

For any team handling recurring agreements, evolving SKUs, or complex approval rules, AI-powered contract editing can improve both speed and control while protecting against revenue leakage.

Improving risk management and compliance across all contracts

For many legal teams, reducing risk starts with consistency. The best way to use generative AI to improve risk management is to train it on all approved and compliant terms your legal team puts together, and program it to flag anything that doesn’t match their training. When all contracts follow the same playbook of approved terms and clauses, it’s easier to catch red flags, enforce company policies, and stay audit-ready at scale.

That’s exactly how NEXT Insurance approached it. When they implemented a CLM, one of their top priorities was building a centralized, AI-enabled workflow that could automatically flag non-compliant terms. Their legal team trained the system on approved language and key risk areas, things like auto-renewal clauses or termination provisions, so that every agreement going through the system could be reviewed for compliance without requiring a lawyer’s eyes on every line.

This helped them enforce policies at scale. For instance, they have a strict stance on vendor agreements: “We do not accept auto-renewal clauses,” explained Legal Operations Manager Nadia Louis Hermez. “And if there’s no way to eliminate that, we add a termination clause.” By embedding this policy into the system, they ensured that exceptions weren’t slipping through the cracks.

Streamlining the contract lifecycle

Generative AI speeds up the entire contract lifecycle by reducing the time legal and procurement teams spend on routine tasks. It enables faster review, approval, and management of contracts by quickly identifying key dates, terms, and potential issues that typically cause delays.

Oklahoma’s Office of Management & Enterprise Services, for example, used AI to quickly flag inconsistencies in language and terms, ensuring all contracts aligned with their state’s preferred provisions. This allowed the team to avoid common errors, such as including another state’s choice-of-law clause, maintain compliance across a wide range of agreements, and execute contracts faster than before.

Beyond improving contract language, AI also helped speed up key parts of the contract lifecycle. Tasks that were once managed manually, often by both legal and procurement teams, are now handled automatically. With AI tools, the team can receive alerts about upcoming opt-out periods, get notified of renewal opportunities, track termination dates, and monitor other time-sensitive contract milestones. This early detection allows teams to act well ahead of time, avoiding last-minute rushes and ensuring contracts move smoothly through each stage.

Reducing obligation and renewal issues

Generative AI helps legal teams stay on top of critical contract obligations and renewal deadlines by continuously monitoring key dates and terms. The AI can send proactive alerts about upcoming renewal windows, termination rights, and compliance checkpoints, ensuring nothing slips through the cracks. This reduces the risk of unwanted auto-renewals, missed termination opportunities, or overlooked contractual obligations that could lead to financial penalties or strained business relationships. By maintaining diligent oversight, legal teams minimize costly errors and improve overall contract compliance.

Accelerating deal cycles

AI-powered contract management accelerates deal cycles by shortening the time spent on drafting, review, and negotiation. Generative AI rapidly analyzes contract drafts, flags potential issues, and suggests edits, enabling faster turnaround and fewer review rounds. Early identification of sticking points allows teams to address concerns proactively, reducing bottlenecks. With quicker approvals and streamlined workflows, businesses can close agreements faster, seize market opportunities sooner, and improve cash flow predictability.

Increasing no-legal-touch review rates

By training AI models on an organization’s approved contract templates and policies, legal teams empower the system to automatically review and approve low-risk contracts without manual intervention. This no-legal-touch process frees up legal resources to focus on complex or high-risk deals while routine contracts are processed swiftly. Increasing no-legal-touch review rates reduces bottlenecks, improves contract throughput, and lowers operational costs, enabling legal departments to deliver faster service without sacrificing accuracy or compliance.

Considerations for implementing generative AI for legal work

Generative AI can drive significant gains in speed, consistency, and strategic impact—but successful implementation requires thoughtful planning. Here are key factors legal teams should consider before adopting AI tools:

Data security

Ensure the AI solution complies with your organization’s security standards, especially around sensitive client data, privileged information, and privacy laws.

Integration with existing systems

Choose solutions that integrate seamlessly with your tech stack to avoid siloed workflows and maximize adoption across teams.

Training

Provide clear onboarding and education for legal and cross-functional users. Adoption improves when teams understand what AI can and can’t do, and how it supports their role.

Governance

Develop clear policies around how AI-generated content can be used, approved, and stored.

Download a free AI use policy template here. 

Measurable success metrics

Define success early. Whether it’s time saved, contract cycle time reduction, or compliance improvements, clear KPIs help demonstrate value and justify further investment.

Human oversight

Even the most advanced AI should support—not replace—legal judgment. Build in review checkpoints and approval workflows to maintain accountability and quality control.

Use case prioritization

Identify highly manual and repetitive use cases, like importing contracts or contract review, that align with AI’s strongest capabilities.

Selecting the best generative AI tool for you

Not all legal generative AI tools serve the same function. Before investing, legal teams should ask a key question: What part of our workflow needs the most support? Are you drafting high volumes of contracts? Managing a large library of executed agreements? Monitoring compliance? Handling legal research? Selecting the right AI solution starts with understanding your team’s specific pain points. Below is a breakdown of the top generative AI tools, organized by function, to help guide your decision, especially if you are just beginning to explore legal AI.

Common legal AI tools and when to use them

Legal research and litigation support tools

Legal research and litigation support tools leverage generative AI to help legal professionals quickly find relevant case law, analyze legal precedents, and prepare litigation materials, making them essential for lawyers focused on research-heavy or dispute resolution work.

Lexis+

Best for legal professionals looking for a research platform that pairs trusted sources with modern AI search tools.

Lexis+ combines traditional legal research tools with AI-powered features like brief analysis, case law summarization, and predictive insights. It helps lawyers streamline research, improve accuracy, and gain actionable intelligence to support case strategy and client advice.

Westlaw Precision

Best for legal teams who want accurate, court-ready results with built-in validation tools.

Westlaw Precision combines a vast library of traditional legal content with AI-powered features such as natural language search, KeyCite case validation, and AI-enhanced filters to quickly surface highly relevant case law, statutes, and precedents. Its generative summaries help streamline legal research and ensure court-ready accuracy.

Contract review and analysis tools

These AI-powered tools help lawyers and businesses quickly scan through contracts to spot important terms, potential problems, and risky language that might otherwise take hours to find manually.

Harvey

Best for law firms that want to speed up drafting, research, and analysis across multiple practice areas.

Harvey is designed for large generative AI law firms and supports a wide range of legal work, including drafting memos, reviewing contracts, conducting research, and summarizing legal content.

Litera Kira

Best for legal teams who need support reviewing a high volume of contracts.

Litera Kira uses advanced machine learning to quickly identify, extract, and analyze key contract clauses and provisions, helping teams reduce manual review time and improve accuracy. It supports customizable clause libraries and workflows, making it ideal for due diligence, compliance, and contract risk management.

Contract lifecycle management platforms

Contract lifecycle management platforms use generative AI to automate and optimize every stage of the contract process from creation and negotiation to approval and post-signature tracking. They are ideal for legal teams managing high volumes of contracts who need end-to-end efficiency and control.

Ironclad

Best for enterprise in-house legal teams managing large volumes of contracts across departments.

Ironclad is a comprehensive platform that supports the entire contract lifecycle from start to finish, including contract intake, generation, review, approval, signature, and post-signature tracking. Its AI features assist with drafting, suggesting redlines, enforcing internal policies, and extracting contract data.

Sirion

Best for teams prioritizing post-signature contract performance management and supplier relationship governance.

​​Sirion combines contract lifecycle management with AI-driven insights to monitor obligations, track deliverables, and analyze supplier performance. Its intelligent automation helps ensure compliance, reduce risk, and improve value realization throughout the contract term, making it ideal for complex, high-value service agreements and long-term vendor management.

Learn more about applying generative AI to your legal work

Every legal team has different needs, but the right AI tool should align with your workflows, reduce manual work, and help you deliver more value across the business. If you’re exploring how generative AI can support your legal team, download The Legal AI Handbook as a great jumping-off point for understanding where AI can fit into your existing workflows. Start putting generative AI to work in your business.

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Ironclad is not a law firm, and this post does not constitute or contain legal advice. To evaluate the accuracy, sufficiency, or reliability of the ideas and guidance reflected here, or the applicability of these materials to your business, you should consult with a licensed attorney. Use of and access to any of the resources contained within Ironclad’s site do not create an attorney-client relationship between the user and Ironclad.