Artificial Intelligence in Law

Why lawyers need artificial intelligence

Generative AI can already read long documents, summarise them, spot differences between versions, suggest wording and draft letters and court documents. For a lawyer, this means less routine work and more time for legal strategy, negotiations and clients. But AI makes mistakes with confidence: it may cite a non-existent case or an outdated version of a law. That is why the course does not just teach you to "ask a chatbot" — it shows how to build AI into your work so that every result can be verified and you can stand behind it.

Which services we cover

Classes use Russian services — GigaChat, YandexGPT (Alice) and other models available in Russia — as well as the AI features of legal reference systems. Foreign models (ChatGPT, Claude, Gemini and others) are discussed separately: their capabilities, access restrictions in Russia and the legal risks of transferring data abroad. Participants learn to choose a tool based on the task and confidentiality requirements, not on hype.

Prompt engineering for lawyers

The quality of the answer depends on how the task is set. We cover the structure of a prompt: role, context, source documents, task, output format and constraints. Participants build their own library of templates for typical tasks — contract review, comparing versions, drafting a claim, summarising case law — and learn to work with long documents in parts, refine and double-check answers.

Contracts, case law and documents

Most of the course is hands-on work with anonymised documents. Contract review: essential terms, risks for a party, imbalances in liability, a protocol of disagreements. Case law: using AI for initial research and structuring positions — and why every reference must be checked against the original source and a legal reference system. Drafting: claims, replies to requests, draft statements of claim and responses, business letters — AI prepares the draft, while the final text and responsibility remain with the lawyer.

Due diligence and large document sets

When reviewing a company or a transaction, a lawyer works with dozens or hundreds of documents. We show how AI can help structure a data room, extract key contract terms into a table, compile a risk register and prepare conclusions for the report — and how to organise sample checks so that no AI error makes it into the final opinion.

Security, ethics and responsibility

A separate module covers the legal framework: personal data under Federal Law 152-FZ (including cross-border transfer), trade secrets, attorney–client privilege and confidentiality agreements. We discuss who owns rights to text created with AI, how to draft an internal AI-use policy for a legal department and where professional responsibility lies.

Format, certificate and enrolment

The course is 36 academic hours: instructor-led sessions, workshops and a final project based on a task from your own practice (using anonymised data). Training is available online and in person; groups are formed according to the schedule, and corporate groups are possible for companies. After the final project, participants receive an HSE IPAA certificate. To enrol, submit a request on the website or contact us via the Contacts page.