Häufig gestellte Fragen
What exactly does a chatbot do in an ERP system?
A chatbot in an ERP is a dialogue-oriented interface layer through which users query data or trigger transactions in natural language instead of navigating through screens and transaction codes. An input such as "Show open purchase orders from supplier Müller" is translated into a machine-processable request and passed to the ERP's business logic via defined interfaces such as a REST API. The bot holds no business data of its own; it accesses the existing ERP data live and first checks the requesting person's authorisation. It therefore replaces neither full-fledged reporting nor actual process automation, but primarily lowers the entry barrier for occasional users.
What is the difference between rule-based and AI-powered ERP chatbots?
Rule-based chatbots work with predefined intents and entities: they recognise keywords and follow a pre-programmed conversation tree, which makes them reliable, easy to trace and comparatively inexpensive. AI-powered variants rely on language models that interpret freer phrasing, take context into account and dynamically call the appropriate function, but in return require more effort for data protection, traceability and model maintenance. In practice, many productive ERP bots are still purely rule-based or built as hybrids, because clearly defined, recurring requests can be handled robustly this way. Which variant makes sense depends on the complexity of the requests, the maintenance effort and the auditability requirements.
Which ERP vendors offer a chatbot or AI assistant?
Several large suites offer their own assistance and dialogue functions, for example SAP with its copilot Joule, Microsoft with Copilot for Dynamics 365, and Infor with its GenAI Assistant, with further vendors pursuing their own approaches. SAP Joule, for instance, can be connected bidirectionally with Microsoft 365 Copilot and Teams, allowing users to query SAP data directly from their familiar interface, and according to the vendor it supports around a dozen languages including German. However, maturity, language support and functional scope differ considerably between products and individual releases. Before making a selection, the functions should therefore be evaluated against your own processes and the specific modules required, rather than relying on marketing claims.
Are ERP chatbots compliant with data protection law, and how secure is the data?
Data protection is particularly relevant for chatbots that use external language models, since personal or confidential business data can then leave your own system. Where such models are used, the processing generally falls under the GDPR, which is why a data processing agreement with the provider — and in many constellations an enterprise or API variant with contractually assured data processing — is standard practice. What remains decisive is consistent authorisation control via the underlying role concept, so that the dialogue cannot bypass permission boundaries, along with logging of actions for traceability. In addition, the EU AI Act tightens the transparency obligations for AI outputs and for labelling chatbot interactions, which apply from 2 August 2026, so selection and operation should also be reviewed from a regulatory perspective.
Are ERP chatbots worthwhile for mid-sized companies?
Whether an ERP chatbot pays off depends heavily on the use case: for clearly defined, recurring requests with an unambiguous data basis, such as status queries, key figures or simple order triggers, tangible quick wins often materialise rapidly. Especially with cloud ERPs that offer robust APIs, a dialogue layer can be connected comparatively cleanly, whereas with complex multi-step processes the benefit quickly reaches its limits. The cost range is considerable, as rule-based solutions can start with manageable effort, while AI-powered bots can become significantly more expensive through integration, maintenance and operating costs. In practice, the exact design varies by industry, company size and the customisation depth of the specific ERP setup, which is why a tightly scoped pilot application is recommended before a broad rollout.