The best first AI project is a specific task your team can evaluate. “Add AI to the business” is too broad to estimate or test. “Draft an enquiry summary for a staff member to review” defines an input, an output and a responsible person.
Look for a repeated task with a clear handoff
List activities that consume time each week: reading incoming enquiries, finding approved answers, preparing internal summaries or categorising support requests. For each, record volume, average handling time, common exceptions and who checks the result.
Some tasks are better handled by ordinary automation. If a rule is exact—such as sending an acknowledgement when a form arrives—a deterministic workflow may be enough. AI may be useful where language or document content varies, but its output needs evaluation.
Three pilot candidates to discuss
| Workflow | Possible pilot output | Human checkpoint |
|---|---|---|
| Sales enquiries | Summary and proposed service category | Staff verify the category and reply |
| Internal knowledge search | Answer grounded in approved documents | Users can inspect the referenced material |
| Support triage | Suggested queue and draft response | Staff handle uncertain or sensitive cases |
An example: enquiry review before CRM entry
Consider a fictional business receiving enquiries through a website. A pilot could read the submitted text, extract the requested service and country, and draft a summary for an employee. The employee checks the summary before a CRM record is created or a reply is sent.
The test set should include ordinary enquiries, vague messages, missing details and requests outside the company’s services. Define what the system must do when it is uncertain: flag the message for review rather than invent an answer. This is a planning example, not a claim about a deployed FiibixTech client system.
Check data and access before choosing a model
- Source material: Which approved documents or systems may the workflow use?
- Access: Which employee roles can see each record?
- Freshness: Who updates the information when a service or policy changes?
- Handling: What information can leave the existing system, and under which provider terms?
- Exceptions: Which requests require a person immediately?
NIST’s AI Risk Management Framework provides a voluntary framework for considering trustworthiness in the design, use and evaluation of AI. For a project brief, translate those concerns into concrete ownership, evaluation and monitoring decisions.
Measure quality as well as time
Record a baseline before the pilot. Useful measures may include handling time, the proportion of drafts accepted without correction, incorrect categorisations and the amount of review required. Agree the acceptable error types and escalation rules before evaluating the results.
Do not assume that a quick demonstration proves production readiness. Test representative material with the people who perform the work. Include corrections and provider usage charges when comparing the pilot with the existing process.
Define the smallest useful release
A practical scope names one workflow, one owner, the systems involved, the review step and the acceptance criteria. Start with a restricted set of approved information and expand only when evaluation supports it. Decide who investigates failed runs, reviews changes and can pause the workflow.
Does every business need a chatbot? No. An internal task may be a more useful starting point than a customer-facing assistant.
Can a pilot promise a fixed saving? Savings need measurement against your actual process; a generic percentage would not establish your return.
Bring one workflow to the discussion
Share the task, current process and systems involved. Explore AI development and automation or ERP and CRM integration.
Discuss an AI pilot