Is the future of contact centers bot or human?
Human-like responses from OpenAI’s ChatGPT and other generative AI large language models (LLMs) have employees and politicians concerned about impending waves of job losses. Meanwhile, contact centers have trouble recruiting and retaining enough agents to keep up with rising consumer demand. Is the stage set for a showdown between humankind and machines? Is a stalemate more likely? Or will we learn to work together to achieve greater outcomes?
Regulator intervention and consumers voting with their feet will radically change how companies respond to (or ignore) their customers’ inquiries. Many companies have made a cost-cutting business decision to block customers from reaching a live person for assistance, and others simply lack adequate customer services operations. Either way, customers in search of help are often frustrated by the avoidance tactics or lack of response. These unsatisfactory customer experiences come with tangible costs, such as: negative reviews, customer churn, and missed revenue opportunities. In addition, customer service agents are placed in the uncomfortable position of facing unnecessarily upset customers, while businesses face difficulties in retaining contact center employees.
Stress and unreasonable demands place many agents in an untenable situation. They’re expected to juggle several chats at once and to close calls quickly. Most customers expect agents to know who they are and be aware of any previous issues or interactions. But often, agents can’t easily access that type of information, which adds to the stress of the job. After months of training, many still aren’t equipped to handle the cases they encounter without additional help. Even with more experience, agents are often powerless to solve the business process issues they face. It is no wonder that many leave soon after starting.
Because generative AI LLMs can feel like the magic bullet, they are capturing the imagination of businesses and individuals alike. Who wouldn’t want an all-knowing entity solving problems as they arise? However, interacting at length with ChatGPT, Google’s Bard, or any of the increasing number of model options now available begins to reveal their flaws. They have a predilection for hallucinating (producing false results), lack contextual understanding, access outdated information, and raise security concerns for many businesses. Despite the risks and pitfalls of these generative AI tools, they’re revolutionizing the customer service space and can, with the correct application, support improved interactions.
Even before generative AI was unleashed on the world, integrated, outcome-based bots had evolved to effectively handle high-volume requests, but were transferred to a human for anything that fell outside their intended purpose. The newest generation of generative AI understands requests better, which can make a significant difference in accomplishing a task correctly. However, because responses can’t always be trusted, companies should avoid allowing generative models to answer customers directly. While they can take a first pass at answers, responses should be validated by humans before being sent to the customer.
Generative models make it feasible for companies to gain full insight into what customers most frequently ask for, how they ask for it, and the corresponding agent responses. Automating the bulk of categorization and labelling work, along with learning the words and phrasing customers are using, enables training of company natural language processing (NLP) for better recognition. In addition, LLMs are great at figuring out alternate phrasings to further improve recognition rates and can modify response style depending on customer sentiment.
Rather than replacing agents or adding demands that force agents to constantly juggle more work faster, generative AI platforms can help lighten their workload. Agent-assist technologies provide suggestions for how to help customers and shorten agent training and response time, which increases their confidence and performance, and improves overall job satisfaction.
Agents have the deepest insight into where business processes are weakest and, when they leave, their insight leaves with them. Enabling agents to improve their workplace can help retain them and capture the value of their experience. In fact, becoming a bot trainer can be an attractive career progression path that allows agents to shape their workplace into one where they will thrive. Empowering agents to improve bots catalyzes a virtuous circle and demonstrates that there is plenty of work for them for the foreseeable future.
Contact center interactions can uncover symptoms of underlying business issues. Paying attention to these signals can help you react strategically and take steps to create solutions. The responsible use and thoughtful implementation of new technologies to support staff and provide the analysis needed to reinvent business processes, positions your organization for success, not just survival.
Published with permission from CGI and Cheryl Allebrand.
