Amazon’s prowess in AI, not just in contact centers but in all things data, should give it a unique opportunity to deliver more AI, faster than a pure play that typically needs to partner in this area.
This week, Amazon Web Services (AWS) launched enhanced capabilities for its artificial intelligence (AI)-powered assistant, Amazon Q in Connect, making it easier for contact centers to provide custom and personalized customer service. With the latest update, contact centers can configure the assistant’s responses to match their company’s brand and guidelines. This includes adjusting tone and language, as well as providing predefined replies.
For example, Amazon Q can be customized in a healthcare setting to include empathetic responses when dealing with a customer’s denied claim, allowing human agents to handle sensitive topics with empathy while following compliance guidelines. The assistant can also support agents with step-by-step instructions for resolving more complex inquiries.
Most industry watchers, myself included, view AI as the biggest transformative technology in contact centers. AI promises to streamline workflows, offload mundane tasks, and give humans faster, more accurate answers, leading to a vastly superior customer experience. The challenge is how to bring AI in to complement the human touch, not replace it. As Star Trek’s Spock stated about the computer M5, “Computers are more efficient than humans, not better.” These updates from AWS blends humans and machines and lets a digital response still the emotional response required in many cases.
How Agent Data Retrieval Boosts Human Performance in the Contact Center
Amazon Q in Connect integrates with Amazon Connect flows, customer profiles, and external systems like CRM systems to gather relevant information. The assistant provides agents with real-time recommendations based on the information it gathered and deemed contextually-appropriate, like customer history and customer preferences. If a financial services customer messages a contact center about their retirement plan, Amazon Q can pull up the customer’s account details, recent transactions, and risk assessments to guide the conversation.
This data-driven approach allows agents to personalize their responses to customers without searching through multiple systems, which saves time and keeps the customers happy. Without native AI support from Amazon Q, agents must flip between different systems which adds delays for the customer and the agent. People aren’t good at correlating data across various applications, but machines are, so let them do the heavy lifting. Additionally, agents can provide more consistent service by using guidance that follows their company’s rules and policies. As a result, agents can focus more on customer interactions, reduce errors, and resolve issues more quickly, leading to a better overall customer experience.
AI Prompts and AI Agents Power Customization
Amazon Q can be customized to fit different business needs through customizations implemented in Amazon Connect’s APIs. The customizations can be set up using AI Prompts and AI Agents. AI Prompts define how the assistant should act, while AI Agents package these instructions for different tasks, making the AI more flexible and suited to various business requirements.
More specifically, AI Prompts are instructions that guide how the AI responds to different situations. AI Prompts can also include customer-specific information, making interactions more personalized. AI Agents, on the other hand, are a collection of these prompts combined to create a complete set of instructions for handling specific scenarios. This makes it easy to apply the same rules across different types of interactions, whether automating responses or assisting agents in finding information.
The customizations allow companies to adjust the assistant’s behavior, tone, and language to align with their brand voice. They can also modify how the assistant communicates by changing the tone to be professional, friendly, or empathetic and by simplifying complex terms for general audiences. Lastly, Amazon Q can be personalized using company-specific language, greetings, and closings to maintain consistency.
These enhancements will help contact centers deliver faster, more tailored service using customer data and context-aware suggestions. Amazon Q in Connect can reduce the time needed to handle each call, increase the chances of resolving issues on the first attempt, and allow companies to adjust the assistant’s behavior to fit their brand. This makes it a useful tool for improving agent efficiency and customer satisfaction.
Closing Thoughts
The last major industry transition for contact centers was when it pivoted to the cloud, and that created a major shake-up in the vendor landscape, and AI will do the same.
Since the company launched Connect, I’ve described it as a “dark horse” challenger as it played catch up with features. With AI, it can now move out of the shadows and establish itself as a leader. One proof point came last year when Amazon Connect moved into the CCaaS MQ Leader Quadrant. I’m expecting a continued move up and right, assuming Gartner continues to evolve the MQ as AI becomes more relevant.
