The starting point
The best place to start may be behind the scenes: helping your team find the right answer before automating the customer conversation.
Make good answers easier to find.
When a customer asks a familiar question, the delay is often finding the current answer. A team member may need to search a document, check an old conversation, or ask a colleague. An internal AI assistant can help locate relevant information and draft a response from approved material.
Start with a small set of current sources: service descriptions, operating hours, preparation instructions, and approved answers to common questions. Ask the system to point to the source it used. If it cannot find a supported answer, it should hand the question to a person.
This can be especially useful when newer team members are learning where information lives. The assistant gives them a starting point while an experienced person remains available for questions and review.
There is evidence of potential. Context matters.
A 2023 NBER working paper studied an AI assistant used by 5,179 customer support agents. It reported roughly 14% more issues resolved per hour on average, with larger gains among less experienced workers. That is evidence from a particular support setting, not a forecast for every business.
Your result will depend on the questions customers ask, the quality of your documentation, and how the tool fits into daily work. Run your own trial before setting expectations for time savings or staffing.
Make it easy to reach a person.
If you later offer a customer-facing assistant, make its role clear and give customers an obvious way to contact your team. Do not make people repeat the whole conversation when they are transferred. Pass along the question, the information already collected, and anything still unresolved.
Complaints, unusual requests, conflicting information, and commitments outside published policies should go to a person. A response that sounds confident can still be wrong. The workflow needs a clear path for uncertainty.
Begin with a narrow set of questions the system can answer from your approved material. Broaden that scope only after reviewing real conversations and correcting the gaps.
Keep quality beside speed.
Review a sample of conversations regularly. Look for accurate answers, appropriate handoffs, and issues that remain unresolved. Track repeat contacts as well as response time: a fast answer that creates another question may not have helped.
Give the team a quick way to flag outdated information and poor suggestions. Assign an owner to update the source material. A helpful system needs maintenance as services, policies, and customer expectations change.
The goal is a more prepared team and a smoother experience. When AI handles the search and first draft well, people can put more attention into listening, explaining, and solving the actual problem.
Common questions
How can AI improve customer service?
An internal assistant can help employees find approved information and prepare responses. This may reduce searching and repeated typing while leaving the employee responsible for the answer.
Does an AI assistant replace the support team?
It does not need to. An early implementation can work behind the scenes, supporting employees with drafts and summaries. Customer-facing automation needs a clear path to a person for uncertainty, complaints, and complex requests.
Sources & further reading
NBER: Measuring the Productivity Impact of Generative AI
Written by Zafe
We build websites, software, and connected systems for business. Here, we share practical ways to bring AI into everyday work.
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