In the past, legal practice relied on manual work, including physical document exchange, face-to-face client meetings, research in physical libraries, and the preparation of paper documents. However, the Internet of Things changed how legal practitioners work – from online meetings and filing court documents electronically to reviewing legal documents online and conducting virtual court hearings. Together, these developments have significantly changed how lawyers work by making legal practice faster and more efficient, even though these changes began to emerge in the early 2000s.

Nowadays, another remarkable transformation is being driven by AI. Major Big Law firms are competing to integrate AI tools into their legal teams. Some of the most recent and well-known tools include:

  • Lawhive's Lawrence – an AI paralegal.
  • SIDSS – a Structured Information Decision Support System which compares initial client details of medical negligence claims with tens of thousands of previous cases in its database to deliver a "confidence score", expressed as a percentage, indicating whether the firm should continue to investigate the case.
  • Harvey – a system that uses natural language processing, machine learning, and data analytics to automate and enhance different aspects of legal work.
  • BCLP's FLARE – a lease reporting tool that can produce "a really good first draft" of a lease report, including links and explanations of how it reached its conclusions.

Even though we must acknowledge the significant benefits these tools bring to modern legal practice, and how they can help improve access to legal services, integrating AI into legal practice requires a careful balance between innovation and ethical responsibility.

While AI can improve efficiency, clear rules are needed to ensure accountability. For example, guidelines should be created to detect and correct bias in AI systems. If AI produces misleading or incorrect results, courts may decide not to allow that information to be used, and the lawyers using the AI may be held responsible for the outcome.

Traditionally, legal responsibility lies with human decision-makers. Lawyers are responsible for the legal opinions they provide, and judges are accountable for the decisions they make and must explain the legal reasoning behind them. However, AI systems often cannot clearly explain how they arrive at their results. This is known as the "black box" problem, where the reasoning behind an AI decision is unclear or hidden.

Another challenge relates to the data used to train AI systems. AI performs best when it is trained on high-quality and accurate data. If the training data is biased or incorrect, the AI may produce unfair or misleading outcomes. Over time, these errors can become worse through a feedback loop, where AI-generated decisions create new data that is fed back into the system. This can reinforce biases and influence legal strategies and outcomes in the future.

Of course, the legal profession should take advantage of the powerful potential of AI to improve efficiency and accountability in legal work. However, adopting AI must be done carefully and responsibly. Lawyers and law firms must remain vigilant to ensure that the ethical standards of the profession are maintained in the digital age. The use of technology in law should also be guided and controlled by strong legal rules and regulations.