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Legal IT

Using AI for legal research

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How safe is using AI for legal research? On the one hand, AI is making quick progress and keeps getting better. The arrival of a new generation of AI agents will only speed up that process. But on the other hand, we keep getting headlines where law firms are being fined for using AI that referred to non-existing legislation and jurisprudence. In this article, we look at a) how AI is reshaping legal research, b) at the risks and accuracy concerns of using AI in legal research, c) at possible mitigation strategies. Finally, d) we look at using AI for legal research on non-US law.

How is AI reshaping legal research – benefits

AI has been having a significant impact on legal research, and generative AI has certainly sped up that process. Many law firms are using generative AI to assist them with their legal research. It is easy and convenient, as they can ask questions in natural language, rather than having to study some query language. And now that most generative AIs have started offering more advanced research agents that can provide sources, AI has become even more attractive. So, AI is significantly reshaping legal research in several impactful ways. Most of those are beneficial.

One of the most noticeable changes is the enhanced speed and efficiency it brings. AI tools are capable of sifting through vast volumes of legal data in seconds, identifying relevant information much faster than a human could. This efficiency saves lawyers considerable time and resources.

Beyond speed, AI can also improve the accuracy and depth of insight in legal research. By analysing large datasets, AI can detect patterns and extract insights that might go unnoticed by human researchers. It can also flag potential errors or inconsistencies in legal documents, helping to ensure the accuracy and reliability of the information used. But caution is needed, as we will discuss below.

Another major advantage is the broader access to legal information that AI provides. These tools can draw from a wide array of sources, including statutes, case law, legal journals, and specialized databases. This comprehensive reach allows lawyers to develop a fuller understanding of the legal issues they face.

Natural Language Processing (NLP) and machine learning further enhance AI’s capabilities in the legal field. NLP enables AI to comprehend the meaning within legal texts. This allows it to extract key information and identify relevant precedents. Meanwhile, machine learning algorithms can analyse historical case data to predict outcomes. This gives lawyers valuable insights into the strengths and weaknesses of their cases.

AI is also increasingly being integrated into established legal research platforms. This integration improves the efficiency and comprehensiveness of legal research.

However, as AI becomes more embedded in legal practice, responsible usage is essential. Ensuring accuracy, upholding ethical standards, and maintaining regulatory compliance are critical. Lawyers must treat AI as a supportive tool rather than a standalone solution, and it remains vital to verify any information generated by AI systems. Because there are still considerable risks involved in using AI for legal research.

Risks and accuracy concerns of using AI in legal research

In a recent case in California, a judge found that nine out of the twenty-seven quoted sources were non-existent. The two law firms involved (one had delegated research to the other) were fined 31 000 USD. If you follow the news on legal AI, it is a common problem. Apart from that, AI still often is biased, too. Let’s have a closer look at both issues.

Accuracy concerns

AI systems can produce inaccurate, incomplete, or misleading legal information. This is particularly the case when dealing with complex cases, with nuanced legal concepts, or when legislation or jurisprudence has changed recently.

Even worse are AI “Hallucinations”. As witnessed in the example above, AI can generate plausible but factually incorrect information. It is therefore crucial to verify all AI-generated output against credible sources. The Californian example above highlights how this is a serious risk, as one in three sources that were quoted did not exist.

The example also illustrates the risk of reliance on AI without oversight. You cannot assume the AI knows what it’s doing. Over-reliance on AI without thorough human review can lead to errors that compromise case outcomes and erode client trust.

Bias and ethical concerns

In previous articles, we pointed out that AI inherits and reflects all the biases of the data pool that it was trained upon. This can lead to unfair or discriminatory legal outcomes. So, bias in AI algorithms is a first concern.

Many AI systems cannot explain how they reached their conclusions, or they fail to mention sources. Lack of transparency and accountability, therefore, is a second issue. The algorithms used by AI systems can be opaque, making it difficult to understand how decisions are made and hold the AI system accountable.

Clients may not fully understand the role of AI in their legal representation. This can easily undermine their trust. Clear communication is essential.

As with any online tool lawyers use that share client information, there are data privacy and confidentiality concerns.

Finally, there is the aspect of professional responsibility. Lawyers have a duty to supervise AI-generated work, ensuring it is accurate and ethical. They also must communicate with clients about the use of AI tools.

Mitigation strategies

It is possible to counteract these risks by implementing some mitigation strategies.

  • Always verify AI-generated results against credible legal databases and primary sources.
  • Actively oversee and review AI-generated work to ensure accuracy, as well as ethical compliance.
  • Be transparent with clients about the use of AI tools.
  • Implement robust data security measures to protect client information and comply with privacy regulations.
  • Adhere to ethical guidelines and professional responsibilities when using AI in legal practice.

What about using AI for legal research on non-US law?

Most of the advances in generative AI are being made in the US, and the EU is catching up. How well do the generative AI platforms perform when it comes to non-US law? And are they available in other languages?

Let’s start with the language question: all the major generative AI engines are available in Dutch and French.

Then, what about non-US law? We did some test with European Law, more specifically about GDPR, and overall, these tests went well. We did not test on recent legislation or jurisprudence.

We also briefly did some tests with Belgian law. We thought art. 1382 of the Civil Code would be an interesting test case, given that it was recently replaced by a new book 6 on extra-contractual liability. We ran the test on ChatGPT, CoPilot, Gemini, Claude, Perplexity, Grok, and you.com. Only four out of seven pointed out that art. 1382 CC had been replaced. They were ChatGPT, CoPilot, Gemini and Grok. The other three, Claude, Perplexity, and You.Com, all did not mention book 6 on extracontractual liability at all.

So, while caution and supervision are already needed for US and EU law, it is even more the case for the law of EU member states, where several generative AI platforms were not (yet) aware of recent legislation.

Conclusion

Using AI for legal research holds promise, but supervision is still very much needed. The above examples show how they can still hallucinate, and that they may not be aware of recent changes in legislation or jurisprudence.

 

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Legal IT

AI Agents are the next big thing

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In our previous article, we looked at legal technology predictions for 2025. Several experts predicted that AI agents would be the most important evolution. So, let’s have a closer look. In this article, we will answer the following questions, “what are AI agents? “, and “why are they important?”. We will also talk about AI agents in legal technology.

What are AI Agents?

An artificial intelligence (AI) agent is a software program that can autonomously interact with its environment, collect data, and use the data to perform self-determined tasks to meet predetermined goals. Humans set goals, but an AI agent independently chooses the best actions it needs to perform to achieve those goals. So, it is a system or program that is capable of autonomously performing tasks on behalf of a user or another system by designing its workflow and utilizing available tools. AI agents may improve their performance with learning or acquiring knowledge.

IBM explains that “AI agents can encompass a wide range of functionalities beyond natural language processing including decision-making, problem-solving, interacting with external environments and executing actions. These agents can be deployed in various applications to solve complex tasks in various enterprise contexts from software design and IT automation to code-generation tools and conversational assistants. They use the advanced natural language processing techniques of large language models (LLMs) to comprehend and respond to user inputs step-by-step and determine when to call on external tools.”

Why are they important?

Some refer to agentic AI as the third wave of the AI revolution. The first wave was predictive analytics where AI could crunch large datasets to discover patterns and make predictions. The second wave was generative AI, that uses deep learning and large language models (LLM) that can perform natural language processing tasks. And now, the third wave consists of AI agents that can autonomously handle complex tasks.

Because they can autonomously handle complex tasks, and better than ever before, AI agents can change the way we work. One headline gives the example of an AI agent that can reduce programming from months to days. There already are E-commerce agents, sales and marketing agents, customer support agents, hospitality agents, as well as dynamic pricing systems, content recommendation systems, autonomous vehicles, and manufacturing robots, for example. And they all can do the work that was previously done by humans.

AI agents clearly offer several benefits. They can dramatically improve productivity, as they can handle complex tasks without human supervision or intervention. And because processes are automated, this also reduces the costs. AI agents can also be used to do research which in turn allows to make informed decisions. AI agents also lead to an improved customer experience because they can “personalize product recommendations, provide prompt responses, and innovate to improve customer engagement, conversion, and loyalty.”

But, as with any breakthroughs in AI, it is important the remain aware that there always is a dark side, too. Already there are warnings about ransomware AI agents, which work autonomously, and are far more sophisticated than their predecessors.

AI Agents in legal technology

For quite a while now, legal technology has been using bots that automate certain processes. In a way, AI agents are the next generation of bots. Many legal technology experts predicted that 2025 would be the year of the legal AI agents.

A selection of predictions on AI agents in legal technology

The National Law Review, also quoted in last month’s article, interviewed more than sixty experts on legal technology. Several of them talked about AI agents in legal technology. Here is a selection of quotes.

Gabe Teninbaum stated that “The biggest surprise in legal AI in 2025 will be the emergence of agentic AI—systems capable of taking autonomous, goal-driven actions within set parameters. These tools won’t just assist lawyers but will independently draft contracts, conduct negotiations, and even manage compliance, pushing the profession to redefine what it means to “practice law.”” And “by 2025, legal AI will shift from supporting tools to decision-making partners, with agentic systems managing tasks like compliance monitoring and preliminary dispute resolution. The surprise won’t be AI’s capability—it will be the speed at which clients demand its adoption.”

Nicola Shaver said, “Agentic AI, with the capability to automate legal workflows end-to-end, will become more prevalent in 2025, as will AI-enabled workflows generally. We will see a move away from the chatbot model to generative AI that is built into the systems where lawyers work and that mimics the way lawyers work, making it easier to adopt. Lawyers should expect to access custom apps for their legal practice areas in places like their document management or practice management systems and will adopt the tools that they like at a deeper level. In 2025, some lawyers will be using generative AI on a daily basis without even noticing it, since it will be an enabler of so many systems in the back end with less of the prompting burden sitting with end users.”

Tom Martin echoes a similar sentiment, calling Agentic AI “a transformative leap in the direct provision of legal services, driven by strengthening multimodal AI models, agentic capabilities, seamless machine-level orchestration, and evolving regulations governing AI-driven legal entities. This shift won’t just streamline existing workflows; it will redefine the way legal services are conceived, delivered, and experienced.”

Jon M. Garon observes that, “The potential for user-operated agents will grow exponentially as these apps create the power to automate calendaring, meeting coordination, note-taking, work-out buddies, and much more, becoming true personal assistants. Lawyers will need to be careful that the agents do not disclose personal or client data, but with that problem solved, these will grow into a significant new market. ”

Evan Shenkman explains it as follows: “Think about tools that can listen in on depositions, trials, or client intake meetings, and provide the attorney — in real-time — with AI-powered guidance and assistance (issue spotting, identifying inconsistencies or falsehoods, etc.) based on the tool’s prior review and analysis of the entire case file. Or tools that can continually review the case docket, and then unilaterally alert the attorney of what just happened, what now needs to be done, and include GenAI-created proposed drafts based on prior firm samples. These tools are already in the works and will be mainstream soon enough. ”

Benefits of AI Agents in legal technology

The benefits AI Agents will bring to the field of legal technology apply not only to lawyers, but to all legal service providers, including alternative legal service providers.

One of the obvious primary advantages of AI agents in the legal field is their ability to enhance efficiency and reduce costs. Bots have already been doing that to a certain extent by automating repetitive tasks such as document review, legal research, and contract analysis. AI agents are expected to take this process of automating tasks to a new level where entire workflows and more complex tasks will be handled by them as well. This will free up valuable time for attorneys to focus on more complex and strategic aspects of their work. This not only increases productivity but also reduces the likelihood of human error, leading to more accurate outcomes.

The capability to process and analyse large volumes of data at speeds is particularly beneficial in legal research: AI can quickly sift through case law, statutes, and regulations to provide relevant information and insights.

Another significant benefit is the improved client service. By providing real-time updates and centralized document management, these agents encourage better collaboration within legal teams. This leads to more cohesive workflows and ensures that all team members are informed and aligned. All of this contributes to enhancing the client experience. (Several experts, some of whom are quoted above, predict that client demand will be a major factor in the adoption of AI agents).

AI agents also support transfer learning, which enables them to apply knowledge gained in one context to new, related tasks. This reduces the need for extensive retraining and allows legal professionals to leverage AI capabilities across various areas of law.

 

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Legal IT

Legal technology predictions for 2025

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At the end of the year and the beginning of a new one, many publications give their predictions for the new year. In this article, we will go over a selection of legal technology predictions for 2025. We can group them in four categories: legal technology predictions that do not involve AI, predictions on legal issues involving AI, predictions on AI in legal services, and finally, some other legal technology predictions on AI.

Legal technology predictions that do not involve AI

While most of the authors focus on the growing impact of AI, there also are legal technology predictions that do not involve it.

A first set of predictions has to do with client demands. Authors anticipate a significant further proliferation of blockchain, cryptocurrencies, and smart contracts. This will result in a growing demand for lawyers who are versed in these matters. Experts also predict that clients’ expectations will keep on rising, and that law firms will have to adapt to that demand. Already, the legal industry is witnessing a shift towards more client-centric services. Overall, experts also predict a growing demand for legal services for SMBs.

A second set of predictions has to do with the investments law firms will be making. Experts predict an overall increase in investments in technology, and more specifically, apart from AI, increases in spending on knowledge management and on cybersecurity.

Cybersecurity remains a critical concern for law firms, especially with the growing reliance on digital tools and AI. The sector is expected to invest more in cyber resilience strategies to counter potential threats, ensuring the protection of sensitive legal data and maintaining client trust. General counsels and Chief Legal Officer need to up their game when it comes to cybersecurity.

Finally, experts expect the billable hour to further decline, and fixed fees and subscription billing to increase.

Predictions on legal issues involving AI

Several authors also focus on legal issues involving AI. On the one hand, there is the topic of regulating AI, and on the other hand, there is the topic of litigation.

Both the EU and the Council of Europe (CoE) published their frameworks on regulating AI. Unlike the EU AI Act, the Council of Europe’s Treaty is open to all countries who want to sign up. More sign-ups are expected. When it comes to the US, the situation is unclear, as the incoming Trump administration may withdraw from the CoE Treaty. Most experts do not expect the Trump administration to impose its own framework. Several authors do see initiatives on both a state level and on the level of local bar associations. The latter may impose ethical rules regarding the use of AI in law firms, especially when it comes to lawyers using generative AI.

There also is an anticipated increase in litigation related to AI tools and practices. One of the areas where experts predict more litigation involves the disputes over unauthorized use of copyrighted materials for AI training. They also expect an increase of product liability lawsuits involving AI-systems. And an increase in litigation is also anticipated when it comes to AI-induced biases in processes like job screening, and potential antitrust violations stemming from AI-driven pricing tools.

Predictions on AI in legal services

Most of the predictions, however, focus on how Artificial Intelligence will impact the delivery of legal services. And the topic that is most talked about is the introduction of AI agents in the delivery of legal service. Some call it the most important evolution for 2025.

So, what are we talking about? An AI agent is a software program designed to operate independently, perceiving its environment, analysing information, and taking actions to achieve specific goals. It gathers data through sensors or input systems, processes this data using logic or machine learning models, and performs tasks or interacts with its surroundings based on its objectives. These agents are widely used in applications such as virtual assistants, self-driving cars, and automated decision-making systems, allowing them to function without constant human intervention. So, you can think of them as the next generation, more advanced and more versatile bots. And in 2025, they’re expected to have a huge impact on the delivery of legal services and on the way that law firms and legal departments operate. We will discuss AI agents more in depth in a follow-up article.

AI is also become more integrated in all aspects of the delivery of legal services, from optimizing and automating workflows, enhancing knowledge management, and handling specific tasks autonomously. Most experts anticipate that all cloud-based software for lawyers and law firms will be integrating more AI into their systems. Overall, authors also predict that generative AI will become better and more specialized in specific legal areas.

Several authors talk about how artificial intelligence is already leading to a sharp increase in productizing legal services. This applies to law firms, legal departments, but also to alternative legal service providers. Some expect hybrid lawyers and/or self-service legal platforms to become as ubiquitous as online banking. Some even anticipate that more and more lawyers will start collaborating with robot lawyers. And for the first time, some even predict that within 5 years, the combination of the advances in AI and breakthroughs in quantum computing will start replacing entry level lawyers.

Other legal technology predictions on AI

Some experts also made some other legal technology predictions on AI. They are optimistic that Generative AI will improve access to justice, and that we will see courts who will start using Generative AI, as well to become more effective.  They also expect a consolidation movement in the market of legal technology service providers. Finally, some expect that Legal AI and Generative AI will become part of law school curriculum.

 

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