AI & automation
Integrate useful AI into a business application
AI can help summarise a case, classify a request or draft a response. A useful project begins with an identifiable task, available information and a result someone can evaluate, before choosing a model.
Choose a bounded, observable task
Ask a team to demonstrate recurring work and difficult examples. Summarising a case is easier to evaluate than a broad productivity promise. Define input, expected output and the person qualified to review it.
Keep a manual fallback so staff can finish when the suggestion is wrong or the service is unavailable. This helps the first release add assistance without making the entire process dependent on generation.
Send only relevant, permitted information
Inventory the fields and documents actually needed. Avoid sending a complete customer history for a narrow writing task. Clarify processing location, retention and supplier terms.
Apply existing access rights before retrieval. A summary must not reveal documents that the user cannot otherwise read. The application, rather than the generated response, should enforce that boundary.
Make suggestions understandable and editable
Identify AI-generated proposals and show relevant sources where useful. Offer correction, retry and a return to manual work. Do not present generated material as already approved by a manager.
Separate preparation from consequential execution. AI can draft a message while sending remains subject to business approval. This retains a clear owner for actions.
Evaluate representative cases
Include routine requests, missing information and ambiguity in a reference set. Define acceptable results with the team: fluent writing can still contain omissions or errors.
Record the tested configuration and repeat important examples when changing models or instructions. Compare against business criteria instead of judging only style.
Assign ongoing ownership
Track relevant errors, costs and corrections without unnecessarily retaining confidential material. Assign decisions, technical incident response and spending limits.
Expand only after validating the first task. Custom development lets assistance appear at the right point in an existing workflow, with a known result and recovery route.
Your checklist
- Choose frequent, verifiable work.
- Apply existing data permissions.
- Separate suggestions from approved actions.
- Build representative evaluation cases.
- Assign costs, monitoring and fallback.
Frequently asked questions
Does AI integration require a chatbot?
No. Summaries, classification and suggestions can appear directly in an existing screen. Choose the interface according to the task.
Can AI update records automatically?
Define the allowed actions explicitly. Reviewed suggestions are often a useful first release for observing quality and retaining responsibility.
A project to explore
Jibril.me
Jibril.me presents AI assistance alongside notes and progress, illustrating assistance attached to a defined use rather than a generic chat window.
Explore the project