Most conversations about "secure AI for business" collapse into a single question about which model is smartest. That is the wrong axis. The models most teams already use are capable enough. The risk is not that the answer is wrong. The risk is where your prompts go, who can read them, whether they become training data, and whether anyone in your company is already pasting confidential material into a personal account you cannot see.
Security here is not a feeling and not a badge on a landing page. It is a short list of properties you can put in a contract and verify before you deploy anything. This guide walks through those properties, explains why each one matters, and shows how a private, EU-hosted workspace addresses them. It is a neutral treatment of the category, so treat every product claim, including ours, as something to confirm against current documentation rather than accept on trust.
If you want the pure data-protection framing, the companion guide to GDPR-compliant AI covers the legal side in more depth, and our comparison of the best GDPR-compliant AI tools applies that framework to specific vendors. This page is the security-first version: what to check, in what order, and why.
The five security criteria that actually matter
Ignore marketing language and score any tool against these. Each one is verifiable, not a matter of trust.
1. Where the data is processed. Are requests handled on servers in the EU, or does the tool call a model API that runs elsewhere by default? US processing is not automatically unlawful, but it adds transfer obligations you have to document, and for regulated data it is often the difference between "yes" and "not without a lot of paperwork". EU hosting removes a whole class of questions before they start.
2. Whether there is a DPA that reaches the model providers. A tool is usually a wrapper around one or more third-party models. A signed data processing agreement (DPA, or AVV in Germany) with the tool vendor is necessary but not sufficient. The agreement chain has to reach the actual model providers behind it, because that is where your prompts are processed. Ask for the sub-processor list in writing.
3. Whether your data trains the model. On many consumer plans, prompts and uploads feed model improvement by default unless you opt out. For a business, that means confidential inputs can leave your control entirely. The property you want is a written commitment that customer data is excluded from training.
4. Whether inputs are retained after processing. "We do not train on it" quietly stops being reassuring if the provider keeps your inputs for a retention window. Zero data retention, where inputs are deleted after the request finishes, closes the gap between the training promise and what actually sits on disk afterwards.
5. Whether you can control who uses AI, and see what they use. This is the criterion most checklists forget, and it is where the largest real-world exposure lives. A tool can be perfectly secure and still leave you exposed if half your team is using something else. Providing a sanctioned tool is itself a security control.
Two practical properties sit alongside these: model choice, because being locked to one model forces a bad trade between capability and vendor risk, and price, because a secure tool that costs more than the work it saves does not get adopted, and un-adopted tools push people back to Shadow AI.
Shadow AI is the security problem you cannot see
The most common data-protection failure in 2026 is not a breach of a sanctioned system. It is an employee pasting a customer list, a salary spreadsheet, or a confidential contract into a personal AI account. There is no log, no DPA, and no retention control, because the company never approved the tool and does not know it is in use.
Surveys of European companies repeatedly show the same pattern: a large share of organisations either know or suspect staff are using personal AI tools at work, while a much smaller share provide an approved alternative. That gap is the leak. You cannot govern what you have not provided.
The fix is not a stricter policy memo. Bans push usage further underground, because the underlying need is real and the free tools are one tab away. The durable fix is to give people a sanctioned tool that is good enough that the personal account stops being worth the risk, then make it the obvious default. Secure AI for business is as much an adoption problem as a technical one. A workspace nobody wants to use is not secure. It just moves the risk somewhere you cannot see it.
How a private EU workspace addresses the checklist
Wysor is a private, EU-hosted AI workspace built for teams that need capable AI and a data-handling posture they can defend. It is a useful worked example of the checklist above because it was designed around those properties rather than retrofitted to them.
On processing location, requests run on EU infrastructure. On the agreement chain, there is an AVV/DPA in place with each model provider rather than a single vendor contract that stops short of the models. On training and retention, there is no training on customer data and inputs are handled under zero data retention, so the "we do not train on it" promise is backed by deleting the inputs rather than storing them. On the knowledge base, you can upload PDF, DOCX, XLSX, PPTX and more and ask questions grounded in your own documents, under the same EU-hosted, zero-retention handling.
On the Shadow-AI criterion, the design answer is capability and choice. Instead of one model, Wysor puts several leading families, Claude, GPT, Gemini and more, in one workspace, so people pick the right model for each task without reaching for an outside account. Beyond chat, two research databanks reduce the pull toward unsanctioned tools further. The legal databank searches real case law and legislation across twelve jurisdictions, more than 87 million documents and over 23.3 million court decisions, with citation and Fundstellen verification that flags overruled decisions, so answers point to a source you can check. The medical databank offers open-corpus medical-literature search and drug information, hosted on EU infrastructure, in the same category as tools like OpenEvidence; it helps find and understand information and does not diagnose or replace a physician. A Scribe feature turns speech into a structured note through an EU pipeline, and document generation drafts letters and reports from notes, which the user reviews and releases.
For professionals bound by confidentiality, Wysor is designed to help reduce the liability risk associated with professional secrecy rather than to make a compliance guarantee on your behalf. That distinction is deliberate. No tool can be "compliant" for you in the abstract, because compliance depends on how you deploy it and what obligations you carry. What a tool can do is remove the technical and contractual gaps that make the risk worse. Pricing starts with a free plan, then Plus at 19,99 EUR per month and Premium at 29,99 EUR per month, with no enterprise contract required, which matters for the adoption side of Shadow AI.
The checklist at a glance
| Security criterion | What to verify | Why it matters |
|---|---|---|
| Processing location | EU hosting, or documented transfers | Removes or adds a class of transfer obligations |
| DPA / AVV | Agreement reaches the model providers | Your prompts are processed by the models, not just the wrapper |
| No training on your data | Written exclusion from training | Confidential inputs stay out of shared model pipelines |
| Zero data retention | Inputs deleted after processing | Closes the gap the training promise leaves open |
| Shadow-AI control | A sanctioned tool people actually use | You cannot govern usage you never provided |
Whichever tool you shortlist, ask for the first four in writing and solve the fifth by adoption. A vendor that answers all five with a signed agreement is secure in the way that matters. One that only prints "secure" or "certified" on a page is not.
How to evaluate a tool in one sitting
- Ask where requests are processed, and get the answer in writing.
- Ask for the DPA and the full sub-processor list, and confirm it reaches the model providers.
- Ask whether your prompts and uploads are used for training, and on which plan.
- Ask what happens to inputs after a request finishes, and for how long anything is retained.
- Ask yourself the honest adoption question: is this good enough that the personal-account temptation goes away? If not, the security story has a hole in it regardless of the contract.
For a vendor-by-vendor view of how specific tools answer these, see our comparison of the best GDPR-compliant AI tools, and for the underlying legal framework, the GDPR-compliant AI guide.
FAQ
What makes an AI tool secure for business? Verifiable properties, not a label: EU processing or documented transfers, a signed DPA/AVV that reaches the model providers, exclusion of your data from training, a clear retention policy, and a sanctioned tool people actually use so work does not leak into personal accounts.
Is it safe to use ChatGPT or other consumer AI at work? The risk depends on the plan. According to publicly available information, some business tiers exclude your data from training, while default consumer plans and US-based processing raise transfer and retention questions you have to document. Confirm the current terms for your specific plan before using it for confidential work.
What is Shadow AI and why is it a security risk? Shadow AI is staff using personal or unapproved AI tools for work. There is no DPA, no log, and no retention control, so confidential data leaves your governance entirely. The fix is a sanctioned tool that is good enough to make the personal account not worth the risk.
Does Wysor train on my data or keep it? No. Wysor does not train on customer data, processes requests on EU infrastructure under zero data retention, and holds an AVV/DPA with each model provider.
Do I need an enterprise contract to get secure AI? Not necessarily. Some tools reserve their secure tiers for enterprise agreements. Wysor offers a free plan and paid tiers at 19,99 EUR and 29,99 EUR per month with no enterprise contract required, which also helps with adoption across a team.
Can secure AI still let people choose different models? Yes. Security and model choice are not in conflict. A workspace can run several model families under one EU-hosted, zero-retention framework, which also reduces the pull toward unsanctioned tools.
