The Complete Guide to Using AI as a Legal Professional in Switzerland in 2025

Swiss legal professionals cannot afford to treat AI as a passing trend: in 2025 the Federal Council signed the Council of Europe's AI Convention and set a sector‑specific, risk‑based path that will see a draft bill and non‑binding measures prepared by end of 2026, so lawyers must balance innovation with duties under the FADP (including Article 21 on automated decisions) and strict professional‑secrecy rules; see the Federal Council's regulatory overview Federal Council regulatory overview - AI Watch: Switzerland.

Copyright and training‑data questions remain unsettled - whether scraping training sets or claiming authorship of AI output will trigger CopA changes is under active debate (Switzerland AI copyright debate and legal developments).

Practical safeguards - inventories, human review of outputs, clear vendor contracts and staff AI literacy - are essential, and short, applied courses like Nucamp's Nucamp AI Essentials for Work bootcamp (AI at Work: Foundations, Writing AI Prompts, Job Based Practical AI Skills) teach prompt design, verification and governance skills lawyers need now to reduce the risk that a single unchecked prompt becomes a courtroom problem.

A machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations or decisions that may influence physical or virtual environments.

Switzerland's 2025 playbook for AI is intentionally pragmatic: the Federal Council opted to ratify the Council of Europe's AI Convention and to stitch AI rules into existing, sector‑specific laws rather than create a single “Swiss AI Act,” so lawyers should expect a mix of targeted legislative tweaks and non‑binding measures (self‑regulation, guidance) drafted by the FDJP, DETEC and FDFA for consultation by end‑2026; see the Federal Council regulatory overview in the White & Case tracker for Switzerland and BAKOM's official Artificial Intelligence overview for the government's three‑fold goals of boosting innovation, protecting fundamental rights and building public trust.

In practice this means continued reliance on the revised FADP for automated‑decision risks, FINMA and sectoral supervisors pressing firms on governance and inventories, and Swiss companies that sell into the EU still needing to map EU obligations (the EU AI Act) onto the Swiss patchwork - a recipe that rewards early, practical safeguards (clear vendor contracts, inventories, explainability checks) and penalises complacency: regulatory change is slow but the compliance landscape will harden as sector rules and non‑binding codes emerge.

Keep an eye on the consultation timetable and regulators' guidance: the next 18 months are the quiet window to convert AI practices into defensible firm policy.

"A machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations or decisions that may influence physical or virtual environments. Different artificial intelligence systems vary in their levels of autonomy and adaptiveness after deployment."

Swiss lawyers should watch a compact cast of authorities that will shape everyday AI choices: the Federal Data Protection and Information Commissioner (FDPIC) sits at the centre - reiterating that the revised Federal Act on Data Protection (FADP) already applies to AI, insisting on transparency - including the right to know when a user is

talking to a machine

- and triggering DPIAs for high‑risk AI - so treat the FDPIC as the privacy watchtower for client data (FDPIC guidance on AI and the FADP); OFCOM and the federal Competence Network for Artificial Intelligence (CNAI) supply technical gloss and common terminology across the administration; FINMA is the enforcer for banks and insurers (see FINMA Guidance 08/2024) and will expect inventories, explainability checks and model‑risk controls; and the FDJP together with DETEC and the FDFA are drafting the sectoral roadmap that must be followed (consultation draft due end‑2026) - in short, compliance will come from a chorus, not a single conductor, so keep inventories, DPIAs and vendor contracts up to date and remember: a single unchecked chatbot prompt can cascade into a regulatory investigation as quickly as a spilled espresso ruins a court brief (Chambers - Artificial Intelligence 2025: Switzerland).

For Swiss legal teams the takeaway is simple and practical: the revised Federal Act on Data Protection (FADP), in force since 1 September 2023, already governs AI‑supported processing and brings concrete obligations - transparency, data‑minimisation, and digital self‑determination - so firms cannot wait for new sector rules before acting (FDPIC guidance on AI and the revised FADP).

Article 21's protections are key for generative systems: individuals can object to automated processing and request human review of automated individual decisions, and operators must disclose when an “intelligent language model” is talking to a user and whether inputs are used to improve self‑learning systems (as underscored in recent summaries of FDPIC AI guidance).

High‑risk AI remains allowed in principle, but only with appropriate safeguards such as a DPIA; by contrast, uses that undermine informational self‑determination (comprehensive real‑time facial recognition or “social scoring”) are prohibited.

Practical steps lawyers should insist on now include vendor clauses on training‑data use, clear user notices that a chat is with a machine, and DPIAs for high‑risk deployments - small measures that prevent a single unchecked prompt from becoming a reputational or regulatory problem (detailed guidance and further context on AI under the FADP).

Liability for lawyers and firms using AI in Switzerland rests on familiar pillars rather than a new AI code: Swiss courts will apply contractual rules (Art. 97 CO) when a mandate is breached, ordinary tort law (Art.

41 CO) for non‑contractual harms, and the Federal Product Liability Act (SPLA) for defective products - so software or AI tools that cause physical injury or property damage can trigger strict product liability rather than a negligence claim; see Pestalozzi analysis of Swiss AI legislation and regulatory approach Pestalozzi analysis of Swiss AI legislation and regulatory approach and the ICLG guide to product liability laws in Switzerland ICLG guide to product liability laws in Switzerland.

Professional and employer risks are layered: agents and lawyers face strict duties of care, loyalty and confidentiality under agency law (Art. 398(2) CO) and can be contractually or disciplinarily liable for failures to supervise AI outputs, while employers must watch employment and data‑protection limits when deploying monitoring or automated decision‑making (employment and criminal sanctions may follow from sectoral statutes).

Insurance and careful allocation of contractual liability - vendor clauses, warranties and clear indemnities - will be essential risk‑management tools, because Swiss courts currently expect existing doctrines to adapt to AI rather than invent new regimes (and insurers are already designing AI coverages); treat inventories, DPIAs and human review as routine precautions so that a single unchecked chatbot prompt doesn't unravel a client file or become a courtroom spectacle like a loose thread pulling apart a tailored suit - expensive, visible and avoidable.

For profession‑specific duty rules and limitation nuances, see the professional‑liability primers collected by leading Swiss commentators Lexology overview of regulation of liability for key professions in Switzerland.

Intellectual‑property rules in Switzerland treat AI as a powerful tool, not a rights‑holder: the Federal Administrative Court's DABUS decision (B‑2532/2024, 26 June 2025) confirmed that only a natural person can be named as inventor, while also making clear that a human who trains the model, supplies data and recognises an AI output as patentable may qualify as the inventor - in short, AI can spark invention, but a person must do the legal signing.

For further reading see the Novagraaf summary of the Swiss DABUS decision Novagraaf summary of the Swiss DABUS decision and the Swiss IPI's primer on inventor rights Swiss IPI primer on inventor rights: Who has what rights to the invention.

Practically, this means two concrete imperatives for lawyers and in‑house teams in 2025: document human contribution (problem definition, data curation, prompting, selection and recognition of outputs) and ensure inventor declarations, employment‑assignment clauses and filing steps are airtight - the IPI will refuse applications that lack a proper inventor designation and courts will assess inventorship case‑by‑case.

Treat AI like a brilliant lab assistant that can't sign the deed: careful records, clear assignment language and prompt‑level provenance turn an AI‑generated insight into a defensible Swiss patent rather than a procedural dead end.

“patent applications must name a natural person as the inventor. A person who contributes substantially to the AI data treatment process, recognises its outcome as a patentable invention, and applies for patent protection also qualifies as an inventor.”

Practical safeguards for Swiss law firms using generative AI are straightforward, concrete and immediately actionable: maintain a living AI inventory and classify use‑cases by risk so you know which systems trigger DPIAs under the FADP and Article 21 (inform and offer human review for automated individual decisions); carve strict vendor contracts with express clauses on training‑data use, security, subcontractors and audit rights; forbid input of client secrets into public models unless you have clear client consent or a compliant on‑prem/cloud setup in line with the Swiss Bar Association (SBA) guidelines and cantonal fact sheets; require human‑in‑the‑loop review and source‑checking for any legal advice, plus versioned documentation (purpose, data sources, prompts, validation tests and fallback plans) to meet FINMA governance expectations for material systems; train fee‑earners in prompt hygiene and IP/data risks so staff stop using AI like an unchecked research assistant; and embed incident and breach playbooks that map reporting duties to the FDPIC guidance on artificial intelligence and, where relevant, FINMA.

These measures - inventory, DPIA, vetted contracts, human review, training and incident drills - turn fuzzy promise into defensible practice and prevent “a single unchecked prompt” from cascading into a reputational or regulatory crisis (or a malpractice claim).

For practical reading, see the FDPIC guidance on artificial intelligence, the Swiss Federal Act on Data Protection (FADP), the SBA AI guidelines and cantonal fact sheets, and sector summaries of supervisory expectations for Swiss firms.

"A machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations or decisions that may influence physical or virtual environments. Different artificial intelligence systems vary in their levels of autonomy and adaptiveness after deployment."

For Swiss organisations the shortest path from AI promise to regulatory pain is a clear, risk‑based governance programme: start with an up‑to‑date inventory (a ROAIA) and map each use case to risk tiers so high‑risk systems trigger DPIAs, human‑in‑the‑loop controls and stricter procurement checks; align policies with ISO/IEC 42001 and embed AI rules into existing data‑governance and security processes rather than creating siloed “AI only” rules (see practical guidance on AI governance and ISO alignment from datenrecht.ch).

Assign accountability - point to a central contact (often the DPO or a cross‑functional AI oversight team), ensure management and the board own oversight, and operational owners run day‑to‑day compliance while an ethics or oversight committee handles strategic choices (Vischer's recommended AI governance mix of a central contact point, business owners and an oversight body is a useful template).

In procurement demand express contractual terms on training‑data use, audit and subcontractor rights, model‑performance SLAs and indemnities, stress‑test D&O and cyber cover with brokers, and require supplier evidence of testing and monitoring; a weak vendor clause is the kind of small omission that can mushroom into a public, expensive headache.

Finally, operationalise governance with role‑specific training, continuous monitoring, incident playbooks and periodic independent audits so compliance stays practical, iterative and defensible in Switzerland's sector‑driven regulatory patchwork.

"We are seeing an increase in AI-related lawsuits since 2024," says Laura Parris, executive director of Management Liability, Gallagher.

Sector-by-sector, the message for Swiss legal teams is pragmatic: finance is the current focal point - FINMA's Guidance 08/2024 pushes banks and insurers to build inventories, a clear governance framework, rigorous testing and continuous monitoring of models, and to treat third‑party and data quality risks as first‑order issues (FINMA Guidance 08/2024 on AI governance and risk management); healthcare, transport and public administration should mirror that risk‑based playbook by prioritising DPIAs, provenance for training data, robust vendor clauses and human‑in‑the‑loop controls even where sectoral supervisors have not yet published bespoke rules, because Switzerland's sector‑specific approach means the practical expectations in finance will ripple into other regulated fields (Pestalozzi analysis of FINMA AI guidance and its wider implications for Swiss legal teams).

In short: treat AI like a high‑value vault - inventories, explainability checks and contractual locks keep risks visible and manageable across sectors; a single unchecked model can cascade from a quiet pilot into a public compliance headache faster than a filing error becomes a court day disaster.

“We need to maximise the stability and resilience of the Swiss financial centre in an environment with heightened risks.”

Conclusion: Swiss legal teams should treat 2025 as the moment to turn AI risk into routine controls - start with an up‑to‑date AI inventory and risk map, run DPIAs on high‑risk systems, and document purpose, data sources and prompt provenance so every model decision can be explained; ensure client notices and human‑review rights comply with Article 21 of the Swiss Federal Act on Data Protection (FADP) - duty to provide information (Article 21, Swiss FADP – duty to provide information) and the FDPIC's transparency expectations (FDPIC guidance on duty to provide information), carve vendor clauses that limit training‑data reuse and grant audit rights, require human‑in‑the‑loop checks for legal advice, embed incident playbooks and insurance procurement into matter intake, and train fee‑earners in prompt hygiene and verification so one unchecked chatbot reply doesn't unravel a client file as quickly as a spilled espresso ruins a court brief; for hands‑on upskilling, short practical courses such as Nucamp's Nucamp AI Essentials for Work bootcamp syllabus teach prompt design, validation and governance steps that translate policy into defensible practice - your immediate checklist: inventory, DPIA, clear client notices, airtight vendor contracts, human review, versioned records and role‑specific training.

Art. 21 Duty to provide information in the case of an automated individual decision. The controller shall inform the data subject about any decision that is ...