The limits of general-purpose AI in legal practice
General-purpose AI systems have grown remarkably capable. They summarize, structure, draft, and respond across an enormous range of domains, including law.
General-purpose AI systems have grown remarkably capable. They summarize, structure, draft, and respond across an enormous range of domains, including law.
AI in transfer pricing: the value is in the reasoning, not the output. In the first part of this series, we looked at why transfer pricing defensibility depends less on the existence of documentation and more on whether a position can be explained, consistently and under scrutiny. That conclusion raises a natural question: where does AI actually fit into this picture?
Transfer pricing is not only a matter of compliance documentation. It is a test of whether a company's tax position reflects economic reality, internal consistency and defensible reasoning.
Legal and tax AI adoption should begin with clear decisions about scope, data, review, documentation and professional responsibility.
The launch of Benvolio marked an important step for the legal and tax technology landscape in Romania. But beyond the formal announcement of a new platform, the moment opened a broader conversation: how can artificial intelligence support legal and tax professionals without reducing complex reasoning to generic answers?
Artificial intelligence entered the legal and tax conversation quickly. Within a few years, large language models demonstrated an ability to summarize legal texts, draft documents, and answer complex questions about legislation and case law. For many observers, this appeared to mark the beginning of a fully automated legal future.
Legal practice depends on two distinct capabilities that are easy to conflate and consequential to confuse: the ability to find relevant information, and the ability to draw sound conclusions from it. These are not two stages of the same activity.
In legal practice, the quality of a decision is not measured solely by its outcome. A decision may appear correct and still fail when challenged, not because the conclusion was wrong, but because the reasoning behind it cannot be adequately explained. That gap between correctness and justifiability is what defensibility addresses.
Accuracy is the metric that AI developers lead with. It is easy to measure, easy to communicate, and easy to sell. But in legal work, accuracy alone is not a sufficient standard, and building AI systems around it as the primary objective may introduce more professional risk than it removes.
Large language models have made artificial intelligence more capable, and more convincing, than ever before. Yet even advanced systems remain prone to hallucinations: confident outputs that appear coherent but lack factual grounding.
Large language models generate outputs through statistical pattern prediction rather than structured legal reasoning grounded in doctrine, hierarchy, and jurisdiction. When they “hallucinate,” they are not intentionally fabricating. They are producing text that appears coherent but is not reliably anchored in verified sources or doctrinal structure.
For decades, lawyers have relied on endless folders, shared drives, and spreadsheets to keep track of cases, filings, and case files. While these methods have worked, they often result in duplication, version confusion, and wasted hours spent searching for the right document. In an industry where every clause and deadline matters, poor document management is not just frustrating, it’s risky.
Legal AI has evolved rapidly, moving beyond research and document review into more complex domains of legal analysis and decision-support.
Explore why local practice nuances remain a critical blind spot in legal AI adoption, the risks of ignoring jurisdiction-specific knowledge, and how firms can integrate tools like Benvolio Briefcase to support human judgment responsibly.
The rapid adoption of large language models has brought artificial intelligence directly into the daily work of lawyers. Drafting, summarization, research, and internal analysis are increasingly supported by AI tools that feel conversational, fast, and confident.
In today’s digital legal world, security is the foundation of trust.
Discover how AI legal assistants, chatbots, and legal AI tools help lawyers save time, automate repetitive tasks, and improve accuracy.
Cases are at the heart of every business relationship, yet drafting, reviewing, and managing them has always been one of the most time-consuming aspects of legal work. Repetitive clauses, boilerplate agreements, and endless client revisions consume valuable hours that lawyers could spend on strategy and negotiation.
Legal work has always been complex. From multi-step document reviews to compliance checks, from drafting cases to managing due diligence, every case involves dozens of moving parts.