ΠΕΡΙΓΡΑΦΗ

Artificial Intelligence is rapidly transforming the legal profession. Large Language Models (LLMs) such as ChatGPT can significantly enhance legal drafting, research, document review, and analysis—but only when used effectively and responsibly.

This practical course provides legal professionals with a structured framework for integrating LLMs into their daily work while maintaining accuracy, confidentiality, compliance, and professional standards. Through real-world examples and hands-on exercises, participants will learn how to create effective prompts, evaluate AI-generated outputs, manage legal and ethical risks, and develop efficient AI-assisted workflows.

Participants will gain practical skills in AI-assisted drafting, legal research, document summarisation, risk assessment, and policy development, while understanding the limitations of LLMs and the importance of professional judgment.

Ideal for lawyers, in-house counsel, compliance professionals, trainee lawyers, and paralegals, this course equips participants with the knowledge and tools needed to use AI confidently, responsibly, and effectively in modern legal practice.

ΣΕ ΠΟΙΟΥΣ ΑΠΕΥΘΥΝΕΤΑΙ

This course is suitable for:

• Practising lawyers at all levels, including junior, mid-level and senior practitioners
• In-house legal counsel involved in drafting, advisory and compliance work
• Corporate service providers and professionals involved in company administration and regulatory matters
• Compliance officers and risk professionals responsible for internal controls and regulatory compliance
• Trainee lawyers
• paralegals seeking to develop practical skills in modern legal workflows
• Legal professionals and organisations seeking to integrate AI tools into daily legal practice in a structured and compliant manner

ΠΕΡΙΣΣΟΤΕΡΕΣ ΠΛΗΡΟΦΟΡΙΕΣ

Course content

_{Module 1: UnderstandingLLMs and Their Role in Legal Practice}

• What Large Language Models (LLMs)are and how they function in a legal context
• Capabilities of LLMs in legal work:
• Drafting assistance
• Summarization of documents
• Research support
• Internal analysis
• Key limitations:
• - hallucinationsand inaccuracies
• - lack of jurisdiction-specific precision
• - absence of legal judgment
• Distinction between:
• - usingLLMs as a support tool
• - improperly relying on LLMs for legal decision-making
• - identification of appropriate and inappropriate use cases in daily legal practice
• Overview of commonly used LLM tools (high-level, non- technical)

_{Module 2: PracticalUse – Prompting, Drafting and Legal Workflows}

• Structuring effective prompts for legal tasks:
• - role-based prompting
• - constraint-based instructions
• -  iterative refinement techniques
• Use of LLMs in drafting:
• - contracts and clauses
• - legal opinions
• - internal memoranda
• Reviewing and refining AI-generated outputs
• UsingLLMs for:
• - summarising case law and legislation
• - extracting key legal issues
• - generating structured first drafts
• Building repeatable workflows:
• -prompt templates
• - internal usage frameworks within firms
• Practical exercises:
• - drafting and refining a clause
• - evaluating an AI-generated legal response
• - constructing prompts for real legal scenarios

_{Module 3: Risk,Ethics and Professional Responsibility}

• Confidentiality risks and handling of client data
• Data protection considerations under EU and Cyprus law
• Professional liability and negligence risks arising from AI use
• Duty of care and supervision when using LLMs
• Identifying unacceptable or high-risk use cases
• Development of internal firm policies on AI usage
• Client communication and disclosure considerations:
• - when disclosure may be required
• - when it may not be necessary
• Maintaining accountability for all AI- assisted work

_{Module 4: Taxation in Real Estate Transactions – Practical Impact on the Deal}

• Use of LLMs in higher- level legal work:
• - strategy development
• - negotiation preparation
• - risk identification and scenario analysis
• Integrating LLMs with:
• - internal know-how
• - precedent databases
• - firm-specific documentation
• Developing internal AI systems:
• knowledge repositories
• prompt libraries
• Evaluating efficiency:
• when LLMs reduce time
• when they increase review burden
• Identifying tasks that can be enhanced versus those that require full legal judgment
• Positioning AI as a tool for competitive advantage in legal practice

Trainer: Kriton Papastergiou