Omar Puertas crosses the AI frontier
Beyond his move from Cuatrecasas to Harvey, Iberian Lawyer spoke with Omar Puertas about the impact of artificial intelligence on legal practice and the future of law firms
by gonzalo blázquez de sande
Omar Puertas’ move from Cuatrecasas to Harvey last March (here the news) is not just an unusual individual transition, but a reflection of a broader transformation beginning to take shape in the legal sector. After more than two decades in legal practice and direct involvement in the first artificial intelligence pilots at his firm, Puertas now operates from the technology side, helping law firms and in-house legal teams integrate AI into their processes.
From his current position, he works with major international firms and corporate legal departments on projects where artificial intelligence is no longer experimental, but operational. “This is no longer a pilot. There are firms where more than 90% of lawyers use these tools on a weekly basis”, he explains. The focus, he says, has shifted from exploration to measuring return. “AI has to be paid for. If you cannot measure productivity or quality, you are not doing a good job”.
His experience at Cuatrecasas was key to this transition. The firm was among the first in Europe to gain access to Harvey, and Puertas was involved in all phases, from initial testing to full-scale implementation. “I was always interested in technology, but for years it didn’t work for our language. It didn’t understand how lawyers think. That changes with models like ChatGPT”. From that point, his career progressively shifted towards the technical side, studying machine learning and statistics, and specialising in use case design and advanced prompting.
This hybrid expertise—legal and technological—is what defines his role today. “Being able to build bridges between how the machine works and how a lawyer works is where the value lies”, he notes. That bridge is precisely what organisations are now demanding: tools that not only accelerate processes but also improve outcomes. In practice, this is already translating into mature applications, particularly in large-scale data analysis, document review and the generation of complex drafts.
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