{"id":115176,"date":"2026-01-23T13:06:29","date_gmt":"2026-01-23T13:06:29","guid":{"rendered":"https:\/\/www.taylorroot.com\/?p=115176"},"modified":"2026-02-25T13:37:26","modified_gmt":"2026-02-25T13:37:26","slug":"ai-adoption-in-europes-legal-function-and-the-impact-of-the-eu-ai-act","status":"publish","type":"post","link":"https:\/\/www.taylorroot.com\/nl\/market-insight\/ai-adoption-in-europes-legal-function-and-the-impact-of-the-eu-ai-act\/","title":{"rendered":"AI adoption in legal functions across Europe and the impact of the EU AI Act"},"content":{"rendered":"\n
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Across Europe, artificial intelligence is moving rapidly from a theoretical discussion to a practical reality for in-house legal teams<\/a>. From generative AI and automation to AI-powered legal tech platforms, organisations are reassessing how AI fits into the modern legal function and what this means for legal work, governance and talent. 
 
The use of AI across in-house legal teams is being shaped by regulatory change, evolving client expectations and growing pressure to streamline legal workflows. At the same time, General Counsel<\/a> must balance innovation with risk, particularly around data protection, cybersecurity and professional judgement. 
 
For many legal professionals, the question is no longer whether AI adoption is necessary, but how far it should be embedded within legal departments and which use cases are appropriate.<\/p>\n\n\n\n

Should businesses build AI tools in-house or outsource to third-party providers?<\/h2>\n\n\n\n

A central strategic question for legal teams is whether AI tools should be built internally or sourced from external providers. 
 
Building AI systems in-house can offer greater control over legal data, workflows and compliance with GDPR, particularly in regulated sectors such as financial services. However, it requires investment, specialist expertise and long-term commitment. 
 
Outsourcing to AI providers or legal tech platforms can accelerate implementation and reduce development risk, but introduces challenges around procurement, data protection and reliance on third-party AI models. Tools such as ChatGPT or established platforms like LexisNexis may support legal tasks, but they still require careful governance and oversight. 
 
As a result, many legal departments are adopting hybrid approaches, combining external AI platforms for routine tasks with internally controlled systems for sensitive legal work.<\/p>\n\n\n\n

How are General Counsel using AI today and where are the limits?<\/h2>\n\n\n\n

In practice, most General Counsel are deploying AI in targeted, pragmatic ways. Common use cases include document review, legal research, contract analysis and the automation of routine tasks. 
 
These AI-powered tools can streamline workflows and improve efficiency, but legal professionals remain cautious about extending AI into complex areas such as decision-making, intellectual property strategy or high-risk advisory work. 
 
The prevailing view across the legal sector is that AI should support, rather than replace, human judgement. AI-driven systems assist legal teams, but accountability remains firmly with the General Counsel and the wider legal function.<\/p>\n\n\n\n

How does AI adoption differ between regulated and non-regulated companies?<\/h2>\n\n\n\n

AI adoption varies significantly across the legal sector. 
 
In highly regulated organisations, AI systems are often tightly governed or limited to specific legal workflows. In less regulated environments, legal teams may experiment more freely with AI-enabled legal services. 
 
This divergence has prompted broader discussion around AI governance frameworks<\/a> and whether AI should be embedded incrementally within legal departments or deployed across enterprise-wide legal and compliance functions.<\/p>\n\n\n\n