Assessing AI in workflows.

Adding AI to a workflow is more than choosing a model or tool. First define the step to improve, the data it may use and how its output will be checked. The right solution varies by use case; conventional automation may be a clearer fit for some needs.

Define the use case

Before choosing a solution, document the current task and the difficulty it creates. Define what you expect AI to support: classification, summarisation, information retrieval or decision support each has different requirements. Describe the expected output and who will use it.

Define data access and boundaries

Identify the data the use case requires, where it resides and who is authorised to use it. If personal, business or customer data is involved, review data minimisation, access rights, retention and third-party transfers with your security and legal teams.

Design human oversight

Decide whether AI output can trigger an action directly or needs employee review. Plan how users will be informed about incorrect, incomplete or uncertain results and how to stop the process. Show every step that requires human review in the design.

Define success measures and failure scenarios

Choose success measures before implementation. Depending on the use case, these may include time saved, completion time, user corrections or answer quality. Also plan for incorrect output, service interruption and unexpected input.

Start with a focused use case

Start with a manageable use case. Define the user group, dataset, review steps and evaluation period. Review the results and base any decision to expand on measured outcomes and a security assessment.

Conclusion

The suitability of an AI application starts with its purpose and data. Gözde IT Solutions assesses AI-assisted development and AI features for existing products according to business needs.