AI under control

Assessing a request, identifying missing information or improving a process: AI can help people organise information and consider possible next steps. The question is not how much AI you add, but which work becomes clearer, better or less labour-intensive.

That is why we explore bounded use cases, such as analysis support, a proposed process step or an explanation of an exception. A suggestion is not a decision. A model output does not grant permission to change data or execute an action.

For us, AI belongs within a managed process. Beforehand, it must be clear which task receives support, which sources may be used and where an automated step ends.

For consequential decisions and uncertain outcomes, an authorised person must be able to review, correct and stop the process.

The organisation retains ownership of its policies and responsibilities. We want to prevent process rules from quietly moving into a prompt, supplier or model that no one can properly explain.

Even without AI, the purpose of a process and responsibility for its result must remain clear.

Privacy and information security start with deciding which information is actually needed. Not all technically available data belongs in an AI request. Each use case requires assessment of purpose, data use, access rights, retention and the role of any service providers.

The same applies to execution. Access to a language model must never silently grant additional permissions in a source system. Advice and a system action require separate authorisation and an identifiable control point. Confidential data also requires suitable processing and infrastructure agreements.

A useful application must offer more than a convincing answer. We want to assess which information was used, what was proposed, who made a decision and which action was actually performed. Logging should support this without unnecessarily collecting sensitive content.

Tests must also cover failures and exceptions: an incorrect suggestion, missing source data, unwanted instructions in supplied information or an unresponsive provider. A human fallback and limited impact belong in the design, not only after the first incident.

Scope4mation researches and develops AI capabilities carefully. We want to learn from concrete problems, user feedback and technical evaluation. Our development practices and the use of AI within them are distinct from AI features that customers can use in Service Automation Suite.

Want to explore a use case? Start with one task, a clear owner and testable criteria. Agree beforehand which data is needed, how the result will be checked and when the trial stops. Only then decide on further development or use.