A small team does not need to automate the whole business to find a useful role for AI. Start with a repetitive task that has a clear input, a checkable result and someone responsible for reviewing it.
For a Nepal business handling enquiries, documents and product information, these five trials can provide a practical starting point. Treat them as experiments, not promised savings.
1. Draft replies to common questions
Prepare approved answers about your services, office location and enquiry process. Use those as the basis for draft replies that a person checks before sending.
Keep prices, deadlines and commitments under human control. If the information is missing, the draft should ask for clarification rather than invent an answer.
2. Turn notes into a task list
Use non-sensitive notes to create a proposed list of actions, owners and dates. Compare the result with the original notes before sharing it.
Do not assume an AI-generated summary accurately records what someone agreed. For recordings or personal information, establish permission and an appropriate handling policy first.
3. Prepare product-description drafts
Supply verified facts such as materials, dimensions and care instructions. Ask for a clear first draft without adding features that are not in the source information.
Have a knowledgeable person check Nepali and English wording. Pay particular attention to quantities, model numbers and claims about quality or origin.
4. Sort enquiries for review
Try suggesting categories such as sales, support and general information. Begin with fictional examples, then compare suggestions against a person's decisions.
Keep uncertain messages visible. An incorrect label should not silently hide a customer's urgent request or trigger an automatic commitment.
5. Explain a prepared report
Use a checked, appropriately anonymised dataset to draft a plain-language explanation of a report. Verify every number against the original before using the summary to make a decision.
Calculations should come from a reliable data process. Fluent text is not evidence that the arithmetic is correct.
Put boundaries around the trial
Decide what data the tool may receive, review its retention and access settings, and exclude confidential material until its handling has been approved. NIST's generative AI profile discusses risks including inaccurate outputs and privacy concerns. Reference: NIST Generative AI Profile
Track review time and corrections as well as drafting time. Stop or redesign a trial that creates more checking work than it removes.
AWKASA's AI & Business Automation service can help define a limited workflow and acceptance checks. Tell us which repetitive task slows your team down to discuss a suitable pilot.