GREECE Trends and Developments Contributed by: Ioanna Alexandropoulou, Konstantinos Plastiras, Filippos Lamnidis and Sergios Lamnidis, Lamnidis Law
When law lags behind: regulatory and doctrinal challenges Despite these innovations, the integration of AI into Greek real estate law is fraught with regula - tory and doctrinal challenges. First, there is a lack of AI-specific regulation. Greek real estate law, rooted in the Civil Code and supplemented by urban planning and cadastral legislation, does not currently account for AI-generated legal conclusions. This absence of tailored regulation creates uncertainty regard - ing the legal weight of AI-generated outputs. Moreover, a critical issue arises regarding pro - fessional liability. When AI systems misinterpret legal data – such as erroneously validating a title with hidden encumbrances – the attribution of responsibility becomes murky. is the developer, the user (lawyer/notary) or the client liable? The current legal framework does not clearly allocate responsibility. Furthermore, the recent withdrawal of the proposed AI Liability Directive at the EU level does little to clarify liability in the context of AI use in legal services, exacerbating uncertainty. In terms of data protection and GDPR compli - ance, AI tools require access to sensitive per - sonal data, especially when reviewing historical property records and family inheritance docu - ments. Greek data protection laws, in alignment with the GDPR, demand transparency and data minimisation – principles that may clash with “black box” AI systems and opaque algorithmic decision-making processes. Finally, there is a growing incompatibility with traditional notarial functions. Greek real estate transactions require the presence of a notary who authenticates documents and ensures legal compliance. The introduction of AI tools could marginalise or reconfigure this role, raising fun -
operational, it will offer a structured data environ - ment ripe for AI applications that can automate title searches, zoning compliance checks, and even simulate future property scenarios based on legal and economic variables. This infrastruc - ture is a critical prerequisite for more advanced applications of AI in the legal domain. In terms of due diligence automation, legal due diligence – traditionally conducted by law - yers and notaries – can be partially automated through Natural Language Processing and machine learning algorithms that analyse pub - lic registries, urban planning documents and cadastral data. AI can flag inconsistencies, iden - tify encumbrances and cross-reference property records with judicial databases, reducing human error and speeding up review time. However, the effectiveness of these tools is highly dependent on the completeness and accuracy of data pro - vided by the digital Cadastre. With respect to predictive valuation models, AI- driven platforms can assess property values by analysing a multitude of data points, including historical prices, location-based factors, infra - structure projects and market trends. This can significantly enhance transparency and support both buyers and regulators in identifying inflated or undervalued properties. Finally, regarding the use of smart contracts, though still nascent in Greece, these self-execut - ing agreements coded on blockchain have poten - tial in lease agreements and escrow arrange - ments. These contracts can embed Greek legal requirements, reducing administrative overheads and increasing transactional security.
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