Legal

The Polish legal market 2026

The Polish legal services market splits into three main segments. First, advocate and legal counsel firms. Second, the legal departments of corporations (banks, telecoms, energy, FMCG). Third, independent lawyers serving business.

The LexisNexis International Legal Generative AI Report 2024-2025 consistently shows that GenAI adoption in the legal industry is growing faster globally than in most other sectors. Top Polish firms are keeping pace, but the segment of smaller firms often operates informally: lawyers use ChatGPT or Claude on their own, without a firm policy, without controls, without awareness of the risk. We describe this phenomenon as Shadow AI.

Five areas of AI implementation with documented ROI

A synthesis of the Thomson Reuters Future of Professionals Report, the American Bar Association Legal Technology Survey Report and Stanford CodeX research.

Contract review and due diligence. AI that parses contracts, detects deviations from standard clauses and generates an executive summary. Cutting the time from hours to minutes per large contract. This is the most mature use case in law globally.

Generating first drafts of court filings. An LLM that generates a draft of a filing based on the case facts and the firm's template library. The lawyer reviews and edits. A significant reduction in time.

Semantic search across the case base. RAG plus the firm's own knowledge base (precedents, opinions, internal notes). The value compounds over time, but it requires discipline in keeping the base up to date.

Correspondence classification. AI that categorizes incoming emails, documents and court filings. Automatic escalation, deadline reminders. Low ROI in hourly value, high ROI in the quality of case handling.

Case outcome prediction. Models that assess the probability of winning based on the type of case, the court, the panel and history. Mature in the US (tools like Lex Machina, Premonition). In Poland still at an early stage because of the limited availability of electronic case-law databases.

Regulatory and ethical specifics

Three areas of requirements specific to the legal profession.

Professional secrecy. Article 6(1) of the Law on the Bar, Article 3 of the Code of Ethics for Legal Counsel. Pasting the contents of a client's case into a free ChatGPT is a potential breach of professional secrecy. It requires either a local LLM (self-hosted Llama, Mistral) or an enterprise API with no-training guarantees (OpenAI Enterprise, Anthropic Enterprise).

Accountability for hallucinations. The American Bar Association Legal Technology Survey and Stanford CodeX document cases in the US where lawyers were sanctioned by courts for presenting fictitious case law generated by AI. The most prominent case is Mata v. Avianca from 2023, in which a New York firm was sanctioned for presenting six non-existent precedents generated by ChatGPT.

The AI Act and GDPR. The AI Act of February 2026 classifies systems that support judicial decisions as high-risk. Most uses of AI in a law firm (contract review, semantic search, drafting filings) fall into the lower-risk category, but they require transparency toward the client about the use of AI.

Three deployment models in a law firm

Tier 1, on-premise LLM. Top firms host local models (Llama, Mistral) on their own GPUs. A high upfront cost, but the data never leaves the firm. The standard for firms in the defense sector, large M&A and criminal law.

Tier 2, enterprise API with guarantees. Mid-sized firms use OpenAI Enterprise or Anthropic Enterprise under a no-training contract. The data passes through the US but is protected contractually under SCCs and the DPF.

Tier 3, dedicated legal platforms. Lexis+, Westlaw Edge, Wolters Kluwer LEX with built-in AI and a base of Polish case law. The standard for smaller firms without their own IT, where LLM infrastructure would be uneconomical.

What yesfor.ai brings that is specific

A yesfor.ai audit for a law firm takes three to six weeks. The standard scope: an assessment of the current state of Shadow AI in the team, the definition of an AI policy aligned with professional ethics, the choice of a deployment model (tier 1/2/3), three use cases for a pilot, and a roadmap.

The first recommendation usually is: start with a Shadow AI audit. Most firms do not know that their trainees are pasting fragments of client contracts into consumer tools. After the audit comes the policy and the choice of a tier 1 or tier 2 deployment.