How AI is impacting the legal profession and what it means for lawyers

How legal AI adoption has accelerated

A few years ago, only a small number of law firms were experimenting with AI tools. Today, most lawyers use some form of AI in their daily work. What changed was the cost - AI tools that once required large budgets are now available on affordable monthly subscriptions that even small practices can access.

This shift happened faster than most people expected.

Which law firms and departments are leading adoption

Large law firms were among the first to invest in AI. But legal teams inside large companies have followed quickly. They face pressure to reduce costs and can adopt new tools without the lengthy approval process that law firms often require.

According to Thomson Reuters, 41 percent of law firms and 47 percent of corporate legal departments now use generative AI - a number that has grown considerably from the previous year.

How AI is shifting the nature of legal work

Traditionally, junior lawyers spent much of their time researching, reviewing documents, and drafting basic agreements. These tasks helped young lawyers learn the profession. AI tools now handle many of them faster.

Experienced lawyers spend less time on common tasks and more time on strategy and client work. For junior lawyers, the challenge is building expertise when AI handles much of the basic work they once did.

Document review and finding digital evidence

In legal disputes, reviewing large volumes of documents to find relevant information can involve millions of files. Before AI, law firms assigned large teams to review them manually, a process that could take weeks or months.

Software can now review and categorize these documents in a fraction of the time, reducing client costs and freeing lawyers to focus on building their case.

Blackstone's legal and compliance team worked with McKinsey to deploy AI across around 25,000 annual document reviews, achieving a 30 percent improvement in reviewer productivity and an expected $5 million in annual run-rate savings by 2027, a result McKinsey attributes directly to AI handling first-pass document review.

Legal research and case summarization

Legal research - finding relevant laws and court decisions for a client's situation - used to take lawyers hours or days. AI tools now return a summary of the most relevant results within minutes.

However, AI research tools are not perfect.

They sometimes generate incorrect information that looks convincing. This is why lawyers must always verify what an AI tool produces before using it in any legal work. AI is a useful starting point, but a lawyer must always make the final judgment.

Contract analysis and clause review

Reviewing a contract means reading through every clause to understand what is agreed and what risks exist. For large transactions, a single deal might involve hundreds of contracts.

AI tools can scan through contracts quickly and flag clauses that look unusual or risky compared to standard terms. This gives lawyers a head start. But deciding whether a flagged clause is actually a problem in a deal's specific context still requires a lawyer's judgment and understanding of the client's situation.

Legal document drafting and automation

Many legal documents follow a standard format. AI tools can generate first drafts of non-disclosure agreements, basic contracts, and routine court filings based on a few inputs, saving lawyers significant time.

For more complex and high-stakes documents - such as agreements for a major business acquisition or a novel legal argument in a court case - AI is less reliable as a drafting tool. In these situations, lawyers use AI to help with research and structure but rely on their own expertise for the actual writing.

Litigation support and predictive analytics

AI tools can analyze past court decisions and give lawyers an idea of how a similar case might be decided, helping them advise clients on whether to settle or proceed to court.

These predictions offer useful guidance, not guarantees. Every case is different, and no AI tool can account for every factor that influences an outcome.

Efficiency gains and time savings for legal teams

Wolters Kluwer's 2026 Future Ready Lawyer survey found that 62 percent of lawyers save between 6 and 20 percent of their work week with AI - meaningful time that most redirect toward research, client communication, or higher-value drafting work.

The challenge is that saving time does not automatically mean earning more. Many law firms charge by the hour. When AI cuts the time needed for a task, the firm earns less for that task unless it adjusts how it prices work. This is one of the bigger structural questions facing law firms as they adopt AI.

More cost-effective legal services for clients

When lawyers can complete research and document review faster, the cost of legal services goes down - particularly significant for individuals and small businesses that often struggle to afford professional legal advice.

Clients who understand AI are increasingly asking about it, and expectations that routine tasks should cost as much as complex strategic advice are shifting.

Expanding access to justice through AI

Access to legal help has always been unequal, with better representation going to those who can afford it. AI tools are beginning to change this.

Organizations providing free or low-cost legal aid use AI to handle more cases without growing their teams. AI cannot replace human advocacy, but it helps more people access basic legal support who might otherwise receive none.

From administrative work to strategic value

Before AI, much of a lawyer's time went to necessary but routine tasks. AI now handles these, freeing lawyers to focus on work that requires their expertise.

For many lawyers, this shift is positive. It allows them to focus on understanding client problems, developing legal strategies, and building relationships - the parts of the job that drew many of them to the profession in the first place.

Accuracy, hallucinations, and false confidence in AI outputs

AI tools can produce wrong answers that sound completely confident and convincing - a problem sometimes called hallucination. An AI tool might generate a legal reference or piece of information that seems accurate but does not exist.

In legal work, a wrong AI output can lead to serious professional consequences, as the Australian case shows. Verifying AI output is not optional - it is a core part of using these tools responsibly.

Bias in legal algorithms and fairness concerns

AI tools learn from historical data. If that data contains bias, as past court decisions sometimes did, the AI tool may repeat those biases in its outputs.

When AI tools inform decisions about individuals, firms must understand and manage the potential for biased outputs.

Client data confidentiality and privacy obligations

Lawyers have a strict obligation to keep client information private. When an AI tool processes data on external servers, confidential client information may leave the firm's own systems.

This is why firms need to understand how any AI tool handles data. Some process it externally. Others deploy within the firm's own systems. Understanding this distinction matters.

Over-reliance and loss of junior lawyer development

Junior lawyers have traditionally learned by doing detailed hands-on work, researching cases, reviewing documents, and drafting agreements under supervision. This is how they build the foundational judgment that makes them effective lawyers over time.

When AI tools take over this work, junior lawyers may spend more time reviewing AI output than actually engaging with the underlying legal material. Many experienced lawyers and legal educators worry that this could produce a generation of lawyers who are less equipped to handle complex situations that require deep legal knowledge and independent judgment.

Regulatory standards and professional accountability

The rules governing how lawyers must behave have not yet caught up with AI. Most existing guidance tells lawyers they must understand the tools they use and remain responsible for any work they submit, even if AI helped produce it.

The rules do not yet clearly address whether lawyers need to tell clients when they used AI, what standard of checking AI output is required, or what happens when AI produces an error that harms a client. These questions are being worked out gradually, often through enforcement cases rather than formal rule changes.