AI for Lawyers: How It’s Changing the Legal Game in 2025

I come from a lawyer family– 4 lawyers across 3 generations. (How do you think I negotiated my way into this sweet job?)

And from speaking to them, the lawyer training trajectory appears to be, and I’m paraphrasing, years of law school, moot courts, internships, and then… paperwork.

Following the letter of the law is noble work, but boy can it be tedious. But it doesn’t have to be.

The use of AI agents is improving productivity across industries, and law is no exception. The legal AI market is projected to exceed $37 billion by the end of the year.

In fact, experts argue that AI has already changed legal practice, establishing itself as an indispensable tool for research and analysis.

In spite of this astronomical growth, there are some barriers. For one, you may be uneasy about adopting AI. It’s new and elusive, which can cause concern. 

On the other hand, you may be all aboard, but unsure about what to use it for or how to implement it.

This article is here to clear things up. I’ll talk about ways AI can benefit legal professionals, and how lawyers, attorneys, and legal professionals can benefit from AI.

Along the way, I hope to dispel some of your anxieties about the tech.

What are the use cases of AI for lawyers?

According to Professor David Wilkins, director of the Center on the Legal Profession at Harvard Law School:

Basic legal information is going to be more and more accessible through technology to more and more people. The problem is that access to basic legal information is just one step in the process of legal services. [source]

Legal practice involves irreplaceably nuanced judgement from experienced professionals.

It also involves menial, time-consuming labor. 

AI’s strength is in ploughing through repetitive tasks at break-neck speeds. There are a hand-full of tasks that AI is particularly well-suited for in legal practice.

1. Legal Chatbots

A chatbot is the obvious answer, and for good reason. Our legal Slack bot, JBT, saves the legal team hours by answering legal queries and citing its references.

If you’re not already using a chatbot of some kind, then your kids are almost certainly bugging you to get started. And with a market expected to grow to $27.3 billion by 2030, they’re certainly not going anywhere.

The question is: how do you keep it accurate for sensitive tasks like legal advice?

The answer is retrieval-augmented generation; users can force chatbots to adhere to specific documentation, and reference their sources. This has been a highly effective tool for mitigating hallucinations, or AI-generated fallacies.

Chatbots could be great for in-house use; feed it your documents, case information, etc. and let it summarize or advise. 

Bots can also be client facing. For example, they can gather preliminary information from potential clients to guarantee more productive face-to-face interaction.

Mullen Law Firm, a defamation firm based in New Jersey, managed to increase qualified lead conversion by 25% by integrating a chatbot in their website to filter irrelevant cases.

2. E-Discovery and Legal Research

A major bottleneck in case-law is E-Discovery: sifting through hoards of documents, databases, e-mails, and files for relevant information.

At its simplest, you can automate this with Control-F.

You can think of AI as a more flexible next step. Rather than being bound to specific keywords, natural language understanding (NLU) allows it to extrapolate meaning and sentiment from documents.

Rimon law implemented AI tools to flag relevant documents, reducing E-Discovery time by 50%.

3. Drafting and Templating

Generating boilerplate is one of the wonderfully effective use cases of generative AI.

AI is great with patterns, and boilerplate is nothing if not a pattern: repeated text with minor alterations.

With plain-language instructions– and maybe a few examples– large language models can come up with professional, accurate, and complete drafts of legal contracts.

It may not be perfect, but even a very imperfect result will have 90% of the work done. Your work is in cleaning and correcting the output. 

You were going to revise the draft anyway, so why not let AI take the first pass?

4. Reviewing Legal Documents

In scanning legal documents like bills and contracts, you know what you’re looking for. 

Large language models (LLMs) are highly effective at extracting information from large texts based on user prompts. You can streamline analyzing contracts by asking things like:

• “Are there arbitration or mediation requirements?”
• “What are the key deadlines in this contract?”

If that’s too specific, try big-picture summarizations:

• “Highlight all obligations of Party A.”
• “Flag any vague or ambiguous language.”

The same applies to litigation analysis: AI can quickly gather information and summarize narratives from case-law with surprising speed.

While there are certainly cases you’ll want to tackle yourself, it’s a great tool for gathering high level insights when you’re sifting through cases.

What are the benefits of using AI in law firms?

Academics are hard at work training AI on legal reasoning. These improvements mean new ways to help lawyers in their practice.

Better Client Experience

Implementing AI is about delegating repetitive tasks to free up time. That time can be allocated to important and sensitive tasks, like dealing with more complex cases and offering personalized experiences to your clients.

Fewer Errors

In addition to saving time, AI can help produce more accurate, cleaner work.

Studies show that automating tasks has the tendency to reduce errors. This can help establish trust with partners and clients, and avoid the headache of fixing mistakes.

Space for Skill Building

The world is changing, and so is the legal industry. Keeping up with those changes is a must in legal practice. That’s not my opinion, it’s evidenced by  jurisdictions mandating continuous legal education (CLE).

Freeing up time by automating tasks with AI lets you fully engage with the learning material, and focus on honing your craft.

Embracing Change

Beyond freeing space to enhance your own professional skills, adopting AI demonstrates a commitment to innovation. It shows your team, clients, and broader community that your practice is proactive and adaptable.

It signals that you’re focused on delivering modern, efficient legal services.

How can AI be applies to legal expertise?

Elusive as the technology may be, using AI is a skill like any other, and there is no shortage of ways to improve at it.

Skills across many disciplines are needed to keep AI-powered tools running smoothly– not just research and engineering.

‍Prompt engineering and familiarizing yourself with your industry’s AI tools are some examples, but more industry-specific knowledge is important as well.

Human in the Loop

Human in the loop– human oversight over AI outputs– is yet another example of where skilled people are indispensable in ensuring proper AI performance.

Few-Shot Prompting

For example, Few-shot prompting is a method of prompting where you ask an AI to perform a task and give examples of correct outputs.

So, you might take a prompt like:

Extract the following information from each indemnity clause:
- Parties involved
- Scope of indemnity
- Triggering events
- Duration (if specified)

support it with examples such as:

Extraction:  
- Parties: Vendor (indemnifier), Purchaser (indemnitee)  
- Scope: Any and all claims, damages, or liabilities  
- Triggering events: Vendor’s breach of any representation or warranty  
- Duration: Not specified
‍
Clause:  
"Each Party shall indemnify the other against losses resulting from third-party claims arising due to negligence or willful misconduct during the term of this Agreement."
‍
Extraction:  
- Parties: Each Party (mutual indemnity)  
- Scope: Losses resulting from third-party claims  
- Triggering events: Negligence or willful misconduct  
- Duration: During the term of the Agreement

 And then cue it with your example:

Clause:  
"The Consultant shall indemnify the Client from costs incurred due to intellectual property infringement related to the Deliverables."
‍
Extraction:

This is as much a legal problem as it is an AI one. What are illustrative examples? How do you modify the examples if the AI doesn’t extract the right information?

With no-code AI tools becoming more available, industry-specific skills are rapidly becoming as much an asset in AI as research and engineering.

Improve Productivity with Legal AI

It’s time to start automating. You’ve got the knowledge, and the tools are out there.

Whether you want a bot to answer questions, or an all-around agent automating your workflow, Botpress has you covered. With human-in-the-loop integration, built-in RAG capabilities, and deployment across popular channels like WhatsApp and web.

Start building today. It’s free.

FAQs

How do I know if my law firm is ready to start using AI tools?

Your law firm is ready to start using AI tools if you’re spending significant time on repetitive tasks like document review, research, or drafting, have digital documents you can feed into AI systems, and are open to training your team on new technology to improve efficiency and client service.

Does using AI mean lawyers will be replaced in the future?

 Using AI doesn’t mean lawyers will be replaced; instead, AI handles repetitive or data-heavy tasks so lawyers can focus on complex legal reasoning, strategy, and client relationships, making it a tool for augmentation rather than a replacement for human expertise.

Are there specific areas of law where AI is more useful than others?

AI is particularly useful in areas of law involving large volumes of documents or standardized processes — like contract law, e-discovery, compliance, and due diligence — where it can quickly analyze text or generate drafts, while highly nuanced fields like courtroom litigation still rely heavily on human judgment.

How expensive is it to adopt AI tools for a small or medium-sized law firm?

Adopting AI tools for a small or medium-sized law firm can start as low as free for basic tools or range from $30 to $500 per month for more robust solutions, with enterprise-level systems costing over ten thousand, but many firms recoup the expense quickly through saved billable hours and increased productivity.

How can I ensure my legal AI tools stay compliant with client confidentiality and privacy laws?

To ensure legal AI tools stay compliant with client confidentiality and privacy laws, choose vendors who offer strong encryption and clear data handling policies, confirm the tools meet legal and ethical standards in your jurisdiction, and maintain human oversight to review AI outputs for sensitive matters.