# AI in customer service: prepared responses > AI in customer service: sort requests, find the customer file, prepare the response the advisor approves. Method, indicators and rules to follow. URL: https://aiorigin.io/en/ressources/insights/agent-ia-service-client-pme-2026 Insights Functions # AI in customer service: responses prepared, advisors in control AI doesn’t replace your advisors: it prepares their work. It sorts requests, finds the customer’s file and drafts a response that the advisor reviews, corrects and sends. UPDATED · OCTOBER 16, 2026 READ · 5 MIN Contents - What can AI do for customer service? - What AI prepares, what the advisor keeps - Reliable responses: connecting AI to your tools and documents - How to go about it - Points to watch - Indicators to track - How AI Origin supports you IN SHORT In customer service, AI is useful for sorting and qualifying requests, summarizing the customer’s history, finding information in your tools and preparing a response. The advisor reviews and decides whether to send it. When a customer interacts directly with an assistant, they must be told. ## What can AI do for customer service? AI steps in before the advisor, to save them search and drafting time. In practice, it can: - Sort incoming requests by reason, urgency and customer, whatever the channel: email, web form, messaging. - Qualify the request: spot the order or contract number, missing documents, the tone of the message. - Find information in the ERP, the CRM or the document base: order status, contract terms, applicable procedure. - Summarize the customer’s history: previous exchanges, open complaints, commitments made. - Prepare a response in your company’s tone, citing the source used. - Suggest the next action: a credit note to issue, a service visit to schedule, a transfer to a specialist team. The advisor stays in control: they review, correct if needed, and decide whether to send. On our operations page, you will find other uses related to orders, case files and customer relations. ## What AI prepares, what the advisor keeps The division of roles is decided reason by reason. One example, to adapt to your own requests: Type of requestAI’s roleAdvisor’s role Order or delivery trackingFinds the order, prepares the responseReviews and sends Question about a contract or warrantyFinds the clause, cites the sourceChecks the interpretation Incomplete requestLists missing documents, prepares the follow-upApproves the follow-up ComplaintSummarizes the history, suggests a responseDecides on any goodwill gesture Unhappy customer or sensitive situationFlags the urgencyTakes over directly Out-of-scope requestRoutes it to the right teamChecks the routing Here is the typical path of a request. A customer writes to ask where their delivery is. AI recognizes the reason, finds the order in the ERP, sees that the carrier reports a delay, and prepares a response that gives the new date and the usual apology. The advisor sees, on the same screen, the request, the draft and the source information. They adjust a phrase, add a goodwill gesture if the commercial policy allows it, and send. The request is filed with its reason, which feeds the team’s statistics. The simpler and better documented the reason, the more reliable the preparation. Complaints and sensitive situations are handled by a person from start to finish: AI only prepares the file. ## Reliable responses: connecting AI to your tools and documents An assistant that knows neither your orders nor your terms and conditions can only produce generic, even inaccurate, responses. Quality depends on two connections. Your software. Through connectors or MCP, an open standard, AI reads an order’s status in the ERP or a customer’s history in the CRM. The IT department approves each access, and AI has only the rights granted to it, read-only in most cases. Your documents. Terms and conditions, internal procedures, product sheets, approved template responses: AI looks for the right information there before drafting, and cites its source. This is the RAG approach, on which France’s Directorate General for Enterprise (DGE) has published a guide. A shared knowledge base, such as a Company Brain, keeps each advisor from storing their own response templates in a corner. This groundwork has a useful side effect: it forces you to update template responses and procedures, which also helps new advisors. ## How to go about it - Analyze incoming requests over a representative period: reasons, volumes, channels, response times, reopened requests. - Choose the starting reasons: frequent, simple, well documented. Order tracking and document requests are often good candidates. - Write or update the reference responses and the tone guidelines: phrasing, register, mandatory notices. - Connect AI to the sources it needs, with the IT department: ERP, CRM, document base. - Test with volunteer advisors on real requests. Every draft is reviewed; corrections are noted to adjust the instructions. - Extend to other reasons, then other channels, once the team judges the quality sufficient. Advisors are best placed to say whether a draft is good. Involve them from the request analysis onward: they know the difficult cases that statistics don’t show. ## Points to watch Transparency. When a customer interacts directly with an assistant, without an advisor, they must know it. This is a transparency obligation under the AI Act, which has applied since August 2, 2026, with the general application of the regulation. When AI prepares a draft that an advisor reviews and sends, the response is the advisor’s. Personal data. Requests contain names, addresses, sometimes sensitive information. The GDPR applies: give AI only what is necessary, choose tools whose contract rules out training models on your data, and set the retention period. Your DPO must approve the setup. Automatic sending. We recommend that AI sorts and prepares, and that a person approves. Sending without review exposes the company to an error of fact or tone that it will have to answer for. Escalation. Set clear rules: an unhappy customer, a threat of litigation or a situation of vulnerability is passed immediately to a person. Traceability. Every prepared response keeps a record of the sources used and of the person who approved it. If it is challenged, you know where the information came from. Our guide on the AI Act in business details the obligations by type of use. ## Indicators to track Measure on indicators your team already tracks: time to first response, time to resolution, share of reopened requests, reported satisfaction if you measure it. Add an AI-specific indicator: the share of drafts sent without major changes. It shows where instructions need adjusting, reason by reason. Also track quality over time: errors found during review, complaints linked to a response, reasons where advisors rewrite almost everything. These signals indicate that a source is incomplete or an instruction poorly worded. A regular review with the team, reason by reason, lets you correct the reference responses and decide which reasons to add. ## How AI Origin supports you We analyze incoming requests with you and choose the reasons to handle first. In hands-on sessions, your advisors build with us the agents that prepare their responses, within your AI policy. The AI Factory then connects AI to your ERP, your CRM and your documents, with access approved by your IT department. Your data is not used to train models; hosting is in France or on your premises. YOUR QUESTIONS ## Frequently asked questions. Can an AI chatbot replace customer service? For simple, documented questions, an assistant can answer directly, provided the customer is informed and there is a quick handoff to an advisor. For most requests, we recommend that AI prepares and the advisor approves. Do you have to tell customers that AI is being used? Yes when the customer interacts directly with an assistant: it is a transparency obligation under the AI Act. When an advisor reviews and sends the response prepared by AI, the response remains theirs. How does AI know our products and procedures? It relies on your documents and software, linked through connectors approved by the IT department. Each response cites the source used, so the advisor can check it. Can AI handle complaints? It can summarize the history and suggest a response, but the decision, especially on a goodwill gesture, is the advisor’s. Sensitive situations must be passed directly to a person. Which indicators should you track for AI-assisted customer service? Time to first response, time to resolution, reopened requests and the share of drafts sent without major changes. That last indicator shows where to adjust instructions. SOURCES ## Texts and studies cited in this article. Every figure on this site is sourced. See all our sources. Union européenne, Règlement (UE) 2024/1689 sur l’intelligence artificielle (AI Act), June 13, 2024. eur-lex.europa.eu Union européenne, Règlement (UE) 2016/679 relatif à la protection des données (RGPD), April 27, 2016. eur-lex.europa.eu Direction générale des Entreprises, Guide de la génération augmentée par récupération (RAG), November 2024. entreprises.gouv.fr READ NEXT ## To go further. - AI for Operations · Orders, case files, quality - Company Brain: your team’s AI knowledge base - GUIDEEU AI Act: what companies using AI must do LET’S TALK ABOUT YOUR PROJECT ## Let’s talk about your operations. Thirty minutes to review current usage, and tell you where we would start. Your contact The AI Origin team that runs the projects You talk directly with the people who will run your project, from scoping to go-live. No specific project yet? Start with a hands-on session: everyone brings a real problem and leaves with the AI agent that solves it. See step 3, Bring your teams on board Thank you, we have received your request. We will get back to you to schedule a time. ### Write to us in two lines. Your company, the teams involved, what you are seeing. We will get back to you to schedule a time. Write to contact@aiorigin.io Or book a time slot Or write to us: contact@aiorigin.io