AI Tools for Lawyers: A New Era of Legal Practice

You didn’t take this role so you could spend your day looking at similar non-disclosure agreements over and over.

What if you didn’t have to do the repetitive, tedious legal tasks that take up so much of your time?

The rapid advancement of artificial intelligence (AI) technology in recent years offers legal teams powerful new tools to enhance efficiency, productivity, and client service. The right AI tool can free your team to conduct the kind of impactful legal work that makes them remember why they wanted to be a lawyer in the first place.

As AI continues to evolve, here’s how legal professionals can understand both the capabilities and limitations of these technologies, and how to ethically and effectively integrate them into their work.

Legal AI tools are a set of software tools designed to handle common legal workflows like document or contract review, case law summarization, memo drafting, contract analysis, or handling in-depth legal research. While the types of legal AI tools available for lawyers vary, many use a combination of predictive analytics, machine learning, and large language models (LLM) to analyze massive amounts of legal data.

Adding AI into traditional legal software like a contract lifecycle management (CLM) tool superpowers already robust capabilities to streamline your contract process. AI adds to those capabilities by:

• Analyzing, tagging, extracting, and reporting on contract data.
• Creating standardized templates and automatically highlighting red-flag items in a new contract and suggesting alternative, preferred language.
• Generating new, simple contracts quickly and efficiently.

When we asked legal professionals how often they used AI tools for our State of AI in Legal Report, 69% of legal professionals said they used AI for legal work—96% of which say it’s helped them achieve business objectives more easily.

For decades, lawyers have relied on traditional research methods, including scouring through volumes of case law, legislation, and scholarly articles to build their arguments. This process, while critical to the practice of law, takes significant time and energy. With the emergence of AI tools, you no longer need to spend hours on manual, low-level tasks.

When we asked lawyers what kinds of tasks lawyers hoped to offload to AI, it was two of the most time-consuming ones that popped up the most: metadata and flagging contract clauses for replacement. These are both well-suited for AI to complete, as doing so manually takes hundreds of hours, with varying degrees of impact to the business’ bottom line.

Today, over half of lawyers are unsatisfied with their work, according to our research. And a recent EY Law Survey revealed that 99% of organizations report that managing current contracting workloads is a challenge, highlighting the potential impact of data-driven resource allocation. Business cycles move faster than ever, and legal teams are increasingly asked to do more with less. 57% of lawyers we surveyed remained optimistic that AI can help alleviate some of this dissatisfaction by removing tedious tasks from their to-do lists.

Adding AI into your legal workflow can help you:

• Rapidly sift through vast databases of legal information, identifying relevant precedents, statutes, and scholarly commentary with unprecedented speed and accuracy, allowing you to make better, more data-driven decisions.
• Parse through large volumes of contracts, pleadings, and other legal documents, identifying key terms, clauses, and anomalies with remarkable efficiency. This not only reduces the time and cost associated with manual document review but also helps lawyers to uncover insights and patterns that might otherwise be overlooked.
• Assist in creating customized wills, contracts, and other legal documents tailored to specific needs, and building re-usable templates to standardize those same contracts for future use.
• 24/7 availability helps you meet tight deadlines and manage high volumes of work without needing a break (or sleep. Remember that?)

By adding AI assistance to many of the routine research tasks that consume a significant portion of a lawyer’s workday, these platforms free up valuable time that can be redirected toward higher-level strategic and analytical work.

Download the Legal AI Handbook

The term “artificial intelligence” actually refers to a wide range of potential tools. It’s similar to lumping together Instagram, Excel, and Tripadvisor as “applications.” They do completely different things.

The four categories of AI are:

• Reactive. This kind of machine learning is programmed only to respond to certain prompts, and is designed to analyze data and deliver set outputs.
• Limited memory. Deep learning allows these programs to “remember” patterns and change what it produces over time, like in a chatbot conversation.
• Theory of mind. Conversational AI like ChatGPT falls into this category, mimicking human patterns of speech and appearing to “think.”
• Self-aware. We’re a ways away from bringing fully autonomous, self-aware AI like HAL-9000 or the Terminator to life.

When you’re thinking of AI tools, you’re probably thinking of the theory of mind category—conversational AI, like Claude, ChatGPT, and Gemini. It’s this type of artificial intelligence that’s truly unlocked the potential for transforming how lawyers get their work done. But we don’t recommend just chatting with AI—instead, use targeted prompts and tools trained specifically in legal affairs, on your business. This may involve investing in legal research platforms, document automation software, or AI-powered legal assistants.

For example, you can train an AI system on an organization’s preferred clauses, creating a custom clause library for your day-to-day legal needs or for bigger legal projects, like mergers and acquisitions (M&A). To do this, AI would analyze thousands of past deals to suggest optimal clauses based on transaction type, jurisdiction, and client industry.

To choose a legal AI tool, adopt a thoughtful, strategic approach that prioritizes ethical considerations and maintains a healthy balance between automation and human judgment. Take the time to thoroughly vet any potential AI tool, evaluating its accuracy, reliability, and data privacy and security measures:

Ethical considerations

As the adoption of AI in legal practice continues to grow, lawyers must grapple with a host of ethical and practical considerations. Chief among these is the issue of professional responsibility and the duty of competence.

The American Bar Association’s Model Rules of Professional Conduct requires lawyers to provide competent representation to clients. This means not only possessing the requisite legal knowledge and skill but also maintaining the legal knowledge, skill, thoroughness, and preparation reasonably necessary for representation. As AI tools for lawyers become more sophisticated, attorneys need to understand the capabilities and limitations of these technologies. That’s the only way they’ll be able to effectively leverage them while upholding their ethical obligations to their clients.

This obligation includes understanding how AI systems reach their conclusions, the potential for bias, hallucinations, or error in their outputs, and the need for ongoing monitoring and adjustment. Lawyers must also be mindful of client confidentiality and the security of any client data that is uploaded to or processed by AI platforms. Failure to do so could result in serious ethical breaches, potential malpractice liability, and possible disbarment.

Another key consideration is the issue of transparency and explainability. As AI systems become more complex and opaque, it can be challenging for lawyers to fully understand the reasoning behind the outputs they generate. This can be particularly problematic in the context of legal proceedings, where the reliability and defensibility of evidence and arguments is crucial.

The ABA provided further guidance in Formal Opinion 512, released earlier this year, advising lawyers to consider their ethical obligations when operating AI.

Security, compliance, and regulatory considerations

When we talk about the risks with AI, security comes up again and again, with nearly half respondents from the 2025 State of AI in Legal Report citing it as a key barrier to AI adoption. That includes the outputs—the potential for bias or hallucinations—but also, the inputs. Who can access the data you’re adding to the system? Will sensitive client information be protected if I feed it to AI for analysis? Will my company’s intellectual property be used in training and recommendations for competitors? Will using AI risk violating legal frameworks for data privacy like GDPR?

A potential piece of technology for your business should be able to answer those questions, and provide you with a full rundown of their cybersecurity apparatus to prevent malicious actors from accessing your data. Look for data encryption (TLS 1.2 or higher) and implementation of industry standard protocols like SOC 1, SOC 2, and ISO 27001.

Internal policy considerations

In addition to vetting individual AI tools, lawyers must also ensure that their overall approach to integrating these technologies into their practice aligns with their ethical obligations. This may involve developing comprehensive policies and procedures around the use of AI, including guidelines for data handling, client communication, and quality assurance. You might:

• Develop cross-functional AI evaluation teams
• Create flexible, forward-looking technology roadmaps
• Invest in comprehensive professional development
• Maintain rigorous ethical oversight
• Foster a culture of technological curiosity and critical evaluation

As legal teams continue to grapple with this new era of AI-powered digital transformation, it’s important to set a code of conduct your entire team can follow.

Download a free AI use policy template

Right now, AI is just at the beginning of its technological evolution, which means it will only become more useful over time. Your clients today may not want AI as part of your work, but as it becomes more sophisticated (and more reliable), that will change. As you look to the future of what your legal team will need, choose a tool based not just on the technological capabilities, but whether or not the technology gels with the way your team already works.

Here’s what to evaluate:

Technical evaluation criteria

Modern legal AI tools must transcend basic automation, but it’s important to strike a balance between need-to-have and nice-to-have capabilities. Do you deal with many different contract types? Do you need the AI to be excellent at parsing unstructured data? Make a list of the tasks you’ll want to unload to AI first and then use the list as a rubric against the tools you’re evaluating.

Key considerations include:

• Precision of legal research and document analysis
• Ability to understand nuanced legal language
• Adaptive learning capabilities
• Comprehensive coverage across legal domains and jurisdictions

Legal teams need tools that can process information quickly, accurately, and with contextual understanding. If an AI tool can’t cite sources or is still struggling with hallucinations, it’s not for you.

System integration requirements

Having an AI tool that works is step one. But if it can’t drop into your team’s legal workflow, then what’s the point? The most powerful AI tools integrate seamlessly into your process, so check to make sure it will “talk” to the rest of your team’s everyday tools.

Critical integration factors include:

• Compatibility with existing case management systems
• Smooth data migration capabilities
• Real-time collaboration features
• Flexible API architectures

Tools are only one piece of a successful integration, though. Make sure you’re thinking about your team’s process overall, and where their pain points are. AI is pretty impressive, but even the smartest bot can’t fix a broken process to start with.

Security and compliance architecture

The security of your proprietary and client data is non-negotiable for any tool you plan to implement, not just AI. No one wants to get an apologetic data breach email, especially for legal teams like yours that handle sensitive data on a daily basis.

Critical security and compliance dimensions include:

• End-to-end encryption
• Granular access controls
• Comprehensive audit trails
• Compliance with international data protection regulations
• Continuous compliance monitoring
• Adaptable governance frameworks

More importantly, can it handle a changing regulatory landscape? What does it do with all of that data it collects, and how is it trained? Because legal teams handle so much sensitive data, you’ll need to make sure a potential tool keeps data secure and follows regulations like GDPR.

Read How to Start Mitigating AI-Related Security Risks

Investment and operational impact analysis

The up-front cost to installing a new tool is just one business impact to consider. As you evaluate potential tools, you must balance these costs against the positive impact of the investment. How much of your day will you get back by outsourcing work to AI? What kind of productivity gains will you see long-term, once the team is trained? Will this AI tool help you decrease time to completion or free up time for your team to be more strategic?

Business evaluation parameters:

• Initial implementation costs
• Ongoing maintenance expenses
• Projected efficiency improvements
• Potential competitive differentiation
• Continuous learning opportunities for your team
• Performance measurement protocols

To be truly successful, consider your overall change management strategy as part of this investment. A tool that isn’t used or constantly requires workarounds by your team just adds busy work and makes it difficult for your investment to pay dividends.

Download Understanding the Total Cost of Ownership

Professional conduct and ethical alignment

More than any other piece of technology in recent years, AI brings up the most significant ethics issues. A way to make sure you’re following professional standards is to choose a tool built with legal professionals in mind. That way your software enhances, rather than challenges, existing ethical frameworks.

Alignment strategies include:

• Comprehensive training on ethical AI use
• Preserving attorney-client privileged communication
• Preventing algorithmic bias
• Regular ethical impact assessments
• Mechanism for human intervention

As AI becomes more sophisticated, maintaining human-centric ethical standards becomes paramount. Remember, there’s no substitute for your own experience, expertise, and judgement.

So, which legal AI tools should you choose? First, conduct a careful assessment of the specific needs and pain points within your practice. If you don’t already have a CLM, choosing one with AI capabilities will certainly help your business in the future. But you may need a simpler tool that solves one part of your workflow, like an AI red-liner. Here are a few legal AI tools to consider:

• CoCounsel: Thompson Reuter’s generative AI tool can research and create detailed briefs, generate contracts, and conduct document review.
• Lex Machina: Analyze your existing deals, legal documents, and complex data sets for case insights.
• Clio Duo: Manage casework like contract analysis, client communication, and summarize your cases with their AI assistant.
• EvenUp: Casework management with a personal injury focus.
• Ironclad: An end-to-end CLM platform with deeply embedded AI. It’s designed with legal teams in mind, so you can easily handle everything from document review to case management. (We’d be remiss if we didn’t include our own technology).

While the potential benefits of AI tools for lawyers are significant, attorneys should maintain a clear-eyed understanding of the technology’s limitations. Never hand off critical tasks to an AI system without understanding how it works and verifying the quality of its outputs.

There needs to be a human in the loop, actively monitoring the performance and reviewing outputs of these tools, ready to intervene or override them if necessary. AI can be a powerful force multiplier, but it should never be treated as a substitute for a lawyer’s own judgment and expertise.