In the contact center and customer experience domain, customer-facing AI is becoming increasingly popular. However, organizations may be looking at implementing AI from the wrong angle, or at least neglecting the most impactful one. By bringing AI to assist the agent first, rather than the customer, agents will have more successful outcomes and higher job satisfaction, and in turn deliver better experiences to customers.
When customer-facing AI, like chatbots, are implemented prematurely, agents may have to correct any miscommunications and manage frustrated customers. To improve the impact of AI, contact center leaders should instead start with agent-facing technology that supports agents in how they find, access and use knowledge to get their jobs done. Agent-facing AI solutions result in better quality, accuracy and speed of interactions.
How does agent-facing AI work?
To start, it is important to understand that agent-facing AI is not here to replace the agent. Its function is in the title, to assist the agent.
Imagine you’re a new agent, first day on the job. You’ve met your team, signed into your computer and have begun learning how to help customers. Most customer queries are basic FAQs, inquiring about balances, policies and other straightforward “yes or no” questions.
A new agent can be challenged by even these simple questions. For more complicated questions, making the correct connections only comes with time and experience. According to Statwolf, regardless of where resources are located, an employee spends an average of 12.5% of their workweek looking for information — that’s 11 days a year.
Enter AI-powered agent assistance. The goal is for this application to help the agent find and deliver accurate answers more quickly and efficiently, eliminating the need to hunt around a range of resources which can take up valuable time. This technology “listens in” on customer conversations and scans available knowledge resources for potential answers. The agent is then prompted with suggested answers and can edit them as needed before sharing with the customer.
Why agent-facing AI should be step one
Based on the “new day on the job” example above, it is obvious that agent-facing AI has great benefits. But it goes far beyond this use case. When used to its full potential, agent-facing AI benefits the entire contact center — like veteran agents learning a new product or service — making it a must-have tool.
Knowledge sources are cited by 48% of contact centers as an urgent investment priority. However, building these sources can be challenging and time-consuming. Using agent-facing AI, the agent and AI work together to build this information source thoroughly and more efficiently as a team. When faced with a question for which agent-facing AI cannot find an answer, agents can flag the topic to the internal content team to add to the knowledge base. If no such knowledge base exists, this is the most direct, least disruptive and most accurate way of developing the resource.
By prioritizing building knowledge bases, organizations will pave the way for future success of their Intelligent Assistance (IA) applications, like chatbots.
Debuting customer-facing AI before it is properly vetted — and without the proper training and resources — can be a difficult place for organizations to start. By using agent-facing AI first, organizations can achieve the same benefits as resource-heavy chatbot implementations with the confidence that IA can be built up internally before releasing it on the customer side. Once agent-facing AI has been mastered, companies can set their sights on AI-powered chatbots to interact directly with customers.
Lastly, organizations should be prioritizing agent-facing AI because it is a valuable tool in the cultural transition of using IA. Rather than trying to replace agents, agent-facing AI helps agents perform their jobs even better. This is made apparent to agents when they have first access to the technology and it is quite literally working with them, not against them.
Agent-facing AI is like a GPS, helping to navigate the unpredictable routes of each customer interaction. While navigating, it can avoid routine and repetitive inquires for the agent, improve performance and job satisfaction and encourage contact center agents to be more open to future IA applications that help them work smarter, not harder.
AI technology created to assist agents should not be the only priority to contact centers, but it should be the first form of AI organizations implement. By bringing AI to the agent, humans and technology can work together to improve customer satisfaction overall.