SaaS Terms for AI Products in Poland: Four Types of Users, One Product
A subscription app’s terms are copied from the internet, with a paragraph about AI added later. They exclude consumer statutory rights, obtain a content license from a customer who did not submit the content, and say nothing about reporting illegal posts. They also leave a critical question unanswered: who is responsible when a model-generated error enters an official document?
These gaps matter when a SaaS product combines an AI module with a public-facing feature—a feedback form, issue map, comments section, or marketplace. The product may serve four distinct groups at once: a business or public-sector customer, its team members, consumers with free accounts, and guests who never register.
A workable set of terms must distinguish those groups. It must also match what the interface actually does. This article explains the decisions to make in the document and the features to build into the product.
Four user categories—and why one B2B template is not enough
A SaaS product with a public-facing layer is not simply “B2B” or “B2C.” Different users encounter the same application on different contractual terms, and Polish law places different limits on what those terms can say.
| User category | Example | How the standard terms apply | Main contractual limits |
|---|---|---|---|
| Professional customer (B2B or business-to-government) | Public authority, consulting firm, property developer | Subscription agreement and acceptance of the terms | Broad contractual freedom, including provisions on statutory warranty rights, liability caps, and courts at the provider’s registered office |
| Member of the customer’s team | External consultancy granted access by the customer | Terms accepted during account registration | More contractual freedom than for a consumer; a separate data processing agreement is also needed |
| End user with a free account (consumer) | Resident registering for a public consultation app | Terms accepted during registration | Consumer protections under Articles 385¹ and 385³ of the Polish Civil Code, the Consumer Rights Act, and the GDPR |
| Unregistered guest | Person opening a public link without a checkbox | Article 8(3) of Poland’s Act on the Provision of Electronic Services | The terms must be made available before the service begins, despite the absence of a checkbox |
If the terms do not distinguish these users, B2B provisions may be ineffective or unfair when applied to consumers. Examples include excluding statutory warranty rights, capping liability at the subscription fee, requiring disputes to be heard at the provider’s registered office, or imposing confidentiality obligations. A provider may think its template protects it when, for some users, it does not.
Terms used throughout this article
| Term | Meaning | Why it matters |
|---|---|---|
| Input data | Text, files, prompts, comments, and other material entered into the application | Defines the material covered by user-content licenses and model-training provisions |
| Output | Material generated automatically by the application, such as summaries, classifications, ratings, alerts, or visualizations | Helps distinguish responsibility for a model error from responsibility for using the result |
| Verification buffer | A system state in which generated content exists but is not published until a professional user approves it | Turns a request to “verify AI output” into an actual product control |
| Right of access | A non-exclusive, non-transferable right to use the interface during the subscription term, rather than a software copyright license | In the cloud model described here, the user does not reproduce the application’s code locally |
| Unfair contract term | A non-individually negotiated provision that, contrary to good practice, grossly infringes a consumer’s interests under Article 385¹ of the Civil Code | Consumer-facing exclusions, provider-controlled measurements, and jurisdiction clauses require particular scrutiny |
If you are unsure which clauses in your current terms need revision, get in touch.
How can terms apply to a guest who never clicks “accept”?
Under Article 8(3) of the Act on the Provision of Electronic Services, the terms bind a user if they are made available before the service begins in a way that allows the user to obtain, reproduce, and store them.
For an unregistered guest, design for three practical requirements:
- Show the terms before use. Make them visible and accessible on the public-link page, for example, before the guest opens a submission form.
- Make them retainable. Give the guest a version they can save, such as a downloadable PDF.
- Document the sequence. The interface could log when the terms were displayed relative to the guest’s first interaction.
A checkbox is not required, but removing it does not remove the need to design the interface around Article 8.
Recommended default: require an account for participation. Let the customer decide whether to enable anonymous access, together with its duty to provide privacy information to end users.
Structure one set of terms around the user’s status
Separate B2B and consumer documents can create gaps when four categories of user share a product. An alternative is one set of terms with different rules within each relevant clause. Liability, confidentiality, payment, and dispute provisions can each distinguish three regimes:
| Regime | Who it covers | Example treatment |
|---|---|---|
| Business users | B2B/B2G customers and team members acting in business | Exclusion of statutory warranty rights under Article 558 § 1 of the Civil Code; liability capped at 12 months’ fees; courts at the provider’s registered office |
| Consumers and sole traders with consumer rights | Consumer end users and sole traders covered by the relevant consumer protections | No exclusion of statutory warranty rights; provisions addressing nonconformity of a digital service under Articles 43m and 43n of the Consumer Rights Act; jurisdiction under general rules |
| Common rules | All users | Provisions addressing the nature of AI output and force majeure, including sudden cloud-interface outages, external model failures, or an administrative ban on the use of AI technology |
This keeps the applicable rule close to the subject it governs, rather than forcing readers to reconcile two documents.
Six decisions for the AI and public-content layers
1. Build a verification buffer, not just a warning
“The user should verify the output” is of little practical or legal value if the interface lets unreviewed output go straight into a public report. A probabilistic model can produce different answers from the same input, and an answer can be false.
For a public authority, an erroneous automated summary placed in official records can become a problem in the administrative process, not merely a software-quality complaint.
Put in the terms:
- State that AI output is probabilistic and may contain errors.
- Prohibit decisions with external effects based solely on automated output, consistently with Article 22 GDPR and Articles 14 and 50 of the EU AI Act.
- Define the verification buffer: generated content remains unpublished until the customer approves it.
Build in the product:
- An unpublished intermediate state visible to an authorized professional user.
- An approval control required before content enters the public view.
- A log recording when approval occurred and who gave it.
2. Label AI content in the interface and exported files
Article 50 of the EU AI Act addresses machine-readable marking of AI system outputs. The source identifies August 2, 2026, as the date from which this obligation applies and describes it as relevant to natural persons interacting with a system regardless of their contractual relationship with its provider.
A visible interface label can disappear when someone exports a report. Address both stages:
- In the interface: show that content was generated or assisted by AI.
- In exported files: include machine-readable metadata that survives export.
- In the terms: prohibit users from removing the markings.
3. Do not promise exclusive rights in AI output
A customer may ask whether a generated visualization belongs exclusively to them, or whether they can prevent others from using a similar result. Address that before a dispute arises.
Material produced wholly automatically may not qualify as a copyright-protected work under Article 1 of Poland’s Copyright Act. Another user may also receive a similar result from a similar prompt. The terms should therefore state that:
- AI output is not a copyright-protected work unless the user’s creative contribution is sufficient for it to meet the Article 1 criteria;
- the customer receives a non-exclusive, non-transferable right to use the output; and
- the provider does not guarantee uniqueness.
4. Obtain a content license from the person who submits the content
A provider may need permission to process a resident’s comment through an AI model. A license from the business customer alone does not resolve the position of an end user or guest who authored and submitted that comment.
Use two tracks:
- End users and guests: provide for a license upon submission, with the relevant information beside the form or on the project page before the user starts typing.
- Professional customers: obtain a representation and warranty that they have the necessary rights and consents for material they enter, together with a clause protecting the provider against claims involving copyright, personality rights, and privacy.
5. Address model training in both directions
A training clause should explain not only what the provider may do with data but also what happens with external model suppliers and what customers may do with outputs.
| Direction | Issue to regulate | Example position |
|---|---|---|
| Third-party models | Whether customer inputs train or fine-tune public commercial models | Customer input data is not used to train or fine-tune third-party providers’ public models |
| Provider’s own models | Aggregation and irreversible anonymization for development | The provider may use aggregated, irreversibly anonymized data to develop its own models |
| Competing models | Customer use of outputs for training | The customer may not use outputs to train or fine-tune models competing with the application |
Check the first promise against the contracts with your model providers. A statement in your customer terms cannot, by itself, control what a third-party supplier does.
6. Add a Digital Services Act process if the app publishes user content
An application that stores and publicly disseminates user content may qualify as a hosting service or online platform under the Digital Services Act (DSA). The source identifies the President of UKE as Poland’s Digital Services Coordinator and states that the Act of September 4, 2026 allows a periodic penalty of up to 5% of an intermediary service provider’s average daily turnover for each day of noncompliance.
The DSA layer identified in the source includes:
- Contact points under Articles 11 and 12.
- A mechanism for reporting illegal content, with formal notice requirements, under Article 16.
- Reasons for decisions restricting content, including information about automated tools, under Article 17.
- An internal complaint system: a free appeal within six months, considered by qualified staff, under Article 20.
- Measures against misuse of notices under Article 23.
- Separate categories for illegal content and content that breaches the terms.
Micro and small enterprises may qualify for the Article 19 exemption from Section 3 of Chapter III of the DSA, if their service is an online platform and they meet the size criteria in Recommendation 2003/361/EC. That is not an exemption from the entire DSA: hosting-service duties under Articles 16–18 remain.
Set a boundary for support staff as well. Technical support should not become advice on the substantive moderation of a customer’s end-user content.
GDPR: assign roles and plan for sensitive submissions
The terms should allocate GDPR roles and refer to a separate data processing agreement, stating that the agreement prevails if the documents conflict. Three points are easy to miss:
- External team members. Require the customer to enter into its own data processing agreement with an outside entity it gives team access to—for example, a consultancy conducting a public authority’s consultation.
- Unregistered submissions. Limit the data requested and advise users not to disclose special categories of personal data under Article 9 GDPR in free-text fields. A comment about a road project may incidentally describe someone’s health, family circumstances, and address.
- People mentioned by users. Consider Article 14 information duties when a submission contains personal data about someone who has not interacted with the app.
Processing Article 9 data requires a condition under Article 9(2); an Article 6(1) basis alone is insufficient. If submitted content is reused to train a model, specify that purpose more precisely and conduct a data protection impact assessment under Article 35 GDPR, as the source advises.
SLA, billing, and offboarding: make standard clauses fit the service
Availability and response times
If an availability guarantee excludes failures in cloud services and cloud-provider interfaces, it may cover only the narrow part of the stack the SaaS provider controls. AI operations can also run asynchronously. Excluding their processing time from an interface-responsiveness guarantee may be justified, but the customer needs to understand the distinction.
Take care with a clause making the provider’s own measurements conclusive. The source flags it as potentially unfair for consumers under Article 385³ point 19 of the Civil Code.
Billing for AI operations
If the commercial unit is a project rather than a seat, and AI operations draw from a separate allowance, address all three of these points:
- Whether unused units expire rather than roll over.
- Whether AI features stop when the allowance is exhausted—and what the interface tells the user.
- Whether a top-up is priced pro rata for the days remaining in the period.
For automatic renewal, provide a pre-renewal reminder, an easy way to cancel before charging the next fee—no later than one day before the next period begins—and a separate consumer price-change procedure requiring active consent.
Export, retention, and deletion
After termination, give the customer a defined period, such as six months, of read-only access and export in a machine-readable format. The source connects this approach with the Data Act (2023/2854) and the obligation to return content after a consumer withdraws from a contract.
At the end of that period, provide for irreversible deletion or full anonymization. Public-sector customers need an additional check: a blanket promise to delete all data when the service ends may conflict with archiving duties under the Prime Minister’s Regulation of January 18, 2011 and the Act on National Archival Resources. The terms should allow deletion to be suspended during an applicable archiving obligation and provide export in an agreed format.
Selling to a Polish public-sector customer
Public authorities must evaluate a SaaS contract against obligations that an ordinary commercial template may not address.
| Standard clause | Public-sector concern | Contract change |
|---|---|---|
| Non-refundable fees | Procurement rules and public-finance discipline require a rationale grounded in how the service is delivered | Describe setup and reserved-resource costs supporting non-refundability |
| Price adjustment without an amendment | Article 439(1) of the Polish Public Procurement Law requires a price-adjustment mechanism for contracts lasting more than six months; it cannot shift all risk to the contracting authority | Set an objective index, such as one published by Statistics Poland, a trigger, and a cap |
| Deletion at contract end | Consultation records may require archiving, and results may be public information under the Act on Access to Public Information | Provide export before deletion and suspend deletion during applicable archiving duties |
| Liability cap | Article 433 of the Public Procurement Law prohibits shifting the contracting authority’s sole responsibility to the contractor | A monetary cap may be used, but not to exclude liability for intentional harm, confidentiality breaches, or personal-data breaches |
| No accessibility commitment | Under Poland’s Digital Accessibility Act, the public entity must ensure accessibility in line with EN 301 549/WCAG | Commit contractually to designing and maintaining the app to WCAG requirements; the authority remains responsible to residents, while the provider answers under the contract |
Checklist for your AI SaaS terms
| Priority | Area | Review question |
|---|---|---|
| Required | User categories | Do the terms distinguish the professional customer, team members, consumers, and unregistered guests? |
| Required | Guest access | Can a guest see and save the terms before using a feature? |
| Required | Consumer terms | Do liability limits, warranty exclusions, and court clauses expressly account for consumers? |
| Required | AI definitions | Are input data and output defined separately? |
| Required | Verification | Is review of AI output enforced by a product feature rather than mentioned only in the terms? |
| Required | AI labels | Are labels visible in the interface, retained in export metadata, and protected against removal by the terms? |
| Required | Output rights | Do the terms avoid promising exclusivity and address uncertainty about copyright protection? |
| Required | User content | Is a license obtained from the submitting end user or guest, alongside the professional customer’s assurances? |
| Required | Model training | Are external models, the provider’s own models, and competing models addressed separately? |
| Required | GDPR | Are roles and data processing agreements addressed, including arrangements with external team members? |
| Required | DSA | Where user content is published, are contact, notice, decision-reason, and appeal processes in place? |
| Recommended | SLA | Does the customer understand what availability and responsiveness guarantees exclude? |
| Recommended | AI billing | Do the terms explain allowance exhaustion, non-rollover, and pro rata top-ups? |
| Recommended | Offboarding | Is read-only access and machine-readable export available after termination? |
| Recommended | Public procurement | Have archiving, public information, accessibility, and procurement requirements been addressed? |
How we can help
AI SaaS terms are not just a document to copy; they record product decisions. A verification buffer, AI labels, and an illegal-content reporting process do not work merely because a contract says they exist.
We help providers bring their terms into line with the product and its users through:
- An audit: identifying ineffective clauses, missing consumer, DSA, or AI Act provisions, and gaps between the document and interface.
- A rewrite: structuring terms around user status and addressing AI definitions, training, user-content licenses, data processing, and billing.
- A broader documentation package: terms, an AI policy, DSA procedures, a data processing agreement, and public-sector sales documentation covering accessibility, archiving, and procurement.
We work with the constraints product teams face—rapid releases, parallel projects, and limited resources—and focus on controls where the risk arises. Contact us to discuss what your product needs at its current stage.
Frequently asked questions
Can terms bind an unregistered guest who never checks a box?
Under the approach described in Article 8(3) of the Act on the Provision of Electronic Services, yes, if the terms are available before the service begins in a form the guest can obtain, reproduce, and store. Design the interface to record when they were presented.
Do business customers and end users need separate terms?
Not necessarily. One set of terms can specify distinct business, consumer/sole-trader-with-consumer-rights, and common rules within each relevant clause. That can reduce inconsistencies between documents.
Which familiar B2B clauses cause consumer problems?
The source highlights exclusions of statutory warranty rights, fee-based liability caps, courts at the provider’s registered office, confidentiality provisions, and clauses making provider measurements binding. Their effectiveness against consumers and sole traders with consumer rights must be assessed under Articles 385¹ and 385³ of the Civil Code.
Who is responsible if a false AI summary enters an official document?
The terms should allocate responsibility: the provider supplies the verification mechanism, while the customer approves content before publication or use in its process. Without a working verification buffer, that contractual allocation may be difficult to enforce.
Is an app that stores user content an online platform under the DSA?
Possibly, if it both stores and publicly disseminates information at a user’s request, as described in Article 3(i) DSA. Storage without public access is not enough. Classification depends on the product’s technical and contractual model.
Can the provider train its own models on anonymized customer data?
The terms should expressly address aggregation and irreversible anonymization for that purpose. Pseudonymization is not the same as irreversible anonymization. Where content may include Article 9 GDPR data, the source calls for a separate Article 9(2) condition and an Article 35 impact assessment. Contract wording does not replace technical verification of anonymization.
The central point
One AI SaaS product can create four different user relationships. Terms that ignore them may fail precisely where the provider relies on them. Review the contract and interface together: publication controls, export labels, content notices, and user permissions must work in the product as well as appear in writing. The EU AI Act transparency provisions identified above and relevant DSA requirements do not depend on whether the terms happen to mention them.
If you need help identifying the gaps, get in touch.
