Companies use AI customer service in different ways: answering routine questions, collecting enquiry details, routing requests and supporting staff with approved information. The best starting point depends on the channel customers already use and what the business can safely automate. The examples below separate ADSM’s own experience from possible workflows; they are not claims that every industry has achieved the same result.
A real ADSM example: WhatsApp enquiries for professional services
ADSM has built an AI WhatsApp workflow for a professional-services company. The relevant pattern is to respond to common incoming questions, collect useful context and pass enquiries that need judgement or a commercial response to a person. The business’s approved information and handover rules matter as much as the assistant itself.
We are not publishing customer-identifying details or performance figures for this project here. If WhatsApp is your main enquiry channel, see ADSM’s website and WhatsApp chatbot service for the types of workflows we can scope.
Appointment-led services: an inbound-call pilot
An incoming call may ask about availability, location, pricing or an appointment. A voice assistant can be tested for collecting caller details and a booking request, with a clear transfer or follow-up path when the question is unusual. ADSM is developing an inbound appointment-booking workflow; each deployment is assessed as a pilot or custom project rather than a ready-made promise.
See the inbound AI receptionist page for suitable call types and handover considerations.
Other workflows a business could assess
Retail and distribution
A chatbot could help customers find product information, ask for a quotation or check an order status. Live stock, prices and order details require reliable integration and access permissions; a bot should not invent them. ADSM has built non-AI systems for distribution businesses, which helps us understand the underlying workflow before proposing AI assistance.
Engineering and equipment services
An assistant could capture an equipment issue, identify the machine and location, and create a service request for a technician. Approved manuals and service records may help staff locate information, while qualified personnel remain responsible for technical decisions. ADSM’s prior engineering-system work informs how we approach these processes; it should not be read as a claim of an existing AI deployment for every use case.
Manufacturing operations
Routine internal questions about a job, document or production status might be supported by an assistant connected to the right system. This is a possible extension of a well-maintained manufacturing workflow, not a replacement for production controls or human supervision.
What to check before implementing
- Which questions recur often, and which require a person?
- Where do approved answers and current records live?
- Which channel should be tested first: website, WhatsApp or phone?
- What customer data can the assistant access or collect?
- How will a request reach the right team member?
- Which outcomes will show whether the pilot helped?
Measure useful handovers, resolved routine enquiries, missed questions and staff follow-up, not just the number of automated replies. For a broader explanation of channel choices and safeguards, read our AI customer-service guide.
Discuss your customer-service workflow
Tell ADSM where your enquiries arrive, what customers ask and which systems your team uses today. We can assess a suitable pilot or custom integration. Contact the ADSM team.