Local AI vs. ChatGPT & Co.: A comparison of data protection, costs and performance

Local AIruns on your own servers or with a hosting provider in Germany: data does not leave your company, costs are predictable, and you decide which model is used. ChatGPT, Microsoft Copilot and other cloud services offer the strongest models without any operational overhead, but require careful data protection review. For many SMEs, a mix is the best solution: sensitive data locally, non-critical tasks in the cloud.

The two approaches at a glance

Cloud AI (ChatGPT, Copilot, Gemini & Co.)

You use a model that runs with the provider – via browser, app, or interface. Billing per user or per usage. No in-house operation, always the latest models, but your inputs are processed by the provider, often outside the EU.

Local or self-hosted AI

An open AI model runs on a server in your own premises or with a German host, accessed via an interface such as Open WebUI. You control data, model selection and access rights – and are responsible for operation and hardware.

Comparison by five criteria

1. Data protection

With local AI, inputs and documents remain within your infrastructure; a DPAis only necessary with the hosting provider. For cloud services, you need to check: Where is processing taking place? Are inputs used for training? Is there a data processing agreement? For business versions, the major providers offer appropriate contracts; consumer versions are unsuitable for company data. For health, social care, or client data, local processing is often the simpler route.

2. Costs

Cloud services cost per user per month or per amount of text processed — inexpensive to start, but more expensive with many users or high volume. Local AI incurs one-time or rental costs for hardware as well as operating effort, but no costs per request. The point at which this changes depends on the number of users and the intensity of use; calculate it using your own figures.

3. Performance

The best cloud models still lead on very complex tasks. For typical office tasks — summarizing, drafting, translating, searching in your own documents — current open models deliver results that are often barely distinguishable in everyday use.

4. Control and dependency

Cloud providers change models, prices and terms at their own discretion. Local AI remains as you set it up until you decide to switch. That is an argument for predictability – see Avoid vendor lock-in.

5. Effort

Cloud AI can be up and running in minutes. Local AI requires setup, updates and monitoring – either internally or through a service provider. If you do not have your own IT team, operation is usually handled by a partner in Germany.

The hybrid solution: the best of both worlds

Many companies divide their tasks according to protection requirements:

• Local: everything with personal, confidential, or specially protected data – customer files, personnel records, contracts, internal documents.
• Cloud: general tasks without sensitive content – collecting ideas, drafting public texts, research.
• Shared interface:Tools such as Open WebUI can provide local and cloud models in a single interface – with clear rules for which model may be used for what.

These rules belong in an AI policy – see Create an AI policy.

Decision aid in five questions

1. Do your teams regularly work with personal or confidential data?
2. Are there professional secrets or particularly sensitive data (health, social services, client data)?
3. How many people are expected to use the AI — and how intensively?
4. Who would take responsibility for operating an in-house solution?
5. How important is independence from a provider’s pricing and model changes to you?

The more often you answer yes to the first two questions and the last one, the stronger the case for local or Germany-hosted AI.

bettersorted relies on for its customers and clients open, transparent components – operated on servers in Germany and bundled in the automaisa Hub. We provide vendor-neutral advice, are a BAFA-registered consultant and an authorized INQA coach. The consulting and guided implementation can be funded through the INQA-Coaching with 80% funding; the right path is shown by the Funding Check. For a non-binding initial consultation: Contact.

Example: Tax advisory firm with client data

An illustrative scenario: A tax advisory firm wants to use AI for client correspondence and searching documents. Client data is subject to confidentiality, so it should not be processed by a US-based service. The firm chooses an open model on a rented server in Germany with a ChatGPT-like interface and access to its own documents. For general research without client reference, a cloud service remains permitted — with a clear rule in the AI policy.

Typical mistakes when making the decision

• Comparing only the license costs: Operating, training, and data protection effort must be included in every calculation.
• “Local is automatically secure”:Even your own AI needs rights, updates, and logs.
• “Cloud is always prohibited”:With business contracts and clear rules, it is permissible for many tasks.
• No rules:Without an AI policy, employees use private accounts – the biggest risk of all.
• No testing:Only with real tasks does it become clear whether an open model is sufficient.

Costs and funding

The costs of a local AI solution consist of three parts: Setup (planning, installation, integration, testing), ongoing operation (server or hosting, updates, monitoring, data backup) and support for employees (training, rules, points of contact). We do not quote fixed prices because scope and starting point vary greatly. The software itself does not incur license costs for open-source solutions.

What is funded is not the technology, but consulting and guided implementation: via the INQA Coachingthe federal government covers 80% of coaching costs nationwide (up to €11,520, vouchers until 30/06/2028). A preliminary analysis can be subsidized through BAFA consulting funding – with 80% in the new federal states, Lüneburg and Trier, otherwise 50%, for applications submitted by 31/12/2026. For investments, some federal states offer their own programs – see Funding opportunities for companies in Germany.

Frequently Asked Questions

Is ChatGPT GDPR-compliant?

The business versions of the major providers can be used in a data protection-compliant way with a data processing agreement and appropriate settings. Consumer versions are unsuitable for company data. For particularly sensitive data, local processing is often the simpler route.

Is local AI cheaper than ChatGPT?

That depends on the number of users and the intensity of use. For a few occasional users, the cloud is usually cheaper; for many users, high volume, or sensitive data, your own AI or AI hosted in Germany can be worthwhile.

Do I need my own IT department for local AI?

No. Many SMEs have such a solution operated by a service provider on servers in Germany. Internally, what is mainly needed is a responsible person and clear usage rules.

Can I use local AI and ChatGPT at the same time?

Yes. A shared interface can offer both model types, and an AI policy defines which data may be used in which model.

As of October 2026.