Collaborative AI Agents (Part 8 of 10)
Victor Antonio
Keynote Speaker and Author - "Sales Ex Machina”, Relationship Selling" & "Mastering the Upsell | Hall of Fame Sales Speaker |
So far I've discussed what AI Agents are and how they will be able to assist and connect with customers.
Imagine for a moment that you are the owner of WindowsRUs, a small business that manufactures and installs Windows.
It’s a trick question because you wouldn’t be able to resolve it, today, with just one AI Agent (AIA). You would need several AIAs working in collaboration to resolve this issue.
Before sharing a collaborative scenario, it's worth taking a moment to understand how AI Agents communicate or talk to each other. Here are 3 ways:
Workflow Summary:
So, when a customer calls in, the 'conversation AI' uses NLP to understand the issue.
It then sends a request to the scheduling AI, which uses its database to find available times.
The scheduling AI sends the appointment details to the technician routing AI, which uses GPS data and traffic information to plan the best route. And so on.
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Case Study: Customer Service for WindowsRUs
Back to my opening example. A collaborative network of AI agents would be deployed to handle this customer inquiry efficiently. Here's how they might work together:
1. Customer Service AI: A chatbot designed to understand and respond to customer inquiries would handle the initial interaction. This chatbot would gather basic information, such as the customer's name, contact details, and the specific window in question. It would also verify the warranty status.
2. Scheduling AI: Once the chatbot has collected the necessary information, it will transfer the inquiry to a scheduling AI. This AI would consult the company's calendar and technician availability to find the earliest suitable appointment time. It would also factor in the customer's preferred time and location.
3. Technician Routing AI: After a suitable appointment is scheduled, a technician routing AI will be activated. This AI would determine the optimal route for the technician based on their location, the customer's address, and traffic conditions. It would also provide real-time updates to the technician's GPS device.
4. Inventory Management AI: To ensure that the necessary replacement parts are available for the technician's visit, an inventory management AI will be consulted. This AI would check the company's inventory records to determine if the specific window seal is in stock. If not, it would initiate an order to replenish the supply.
5. Customer Follow-up AI: After the technician has completed the repair or replacement, a customer follow-up AI would reach out to the customer to ensure their satisfaction. This AI would collect feedback on the technician's service, the quality of the replacement window, and the overall experience.
By working together, these AI agents can streamline the customer service process, reduce response times, and improve overall customer satisfaction.
The future of AI is collaborative whether agent-to-agent-to-agent or agent-to-agent-to-agent with a Human-In-The-Loop (HITL).
Next: (A)I Know Kung Fu (Part 9 of 10)
Victor Antonio | Author | Speaker
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