AI in the contact center isn’t new. For well over a decade now, adoption of AI in the contact center has been quietly growing and has recently become supercharged with new and exciting use cases. It will not be a surprise to many that, for most organizations, the contact center is actually the epicenter of AI, including generative AI (GenAI). This is backed by numerous pieces of recent research, including the latest GenAI research from ISG, which reveals that three of the top six GenAI use cases are directly related to customer support and five of the top six are directly related to service improvement.
The use of AI-based capabilities, such as natural language processing, machine learning, sentiment analysis, transcription and even translation, are allowing contact centers to automate new areas of their operations and replace or augment a more diverse set of job roles and tasks.
Benefits of Using AI in the Contact Center
Here are the five top benefits AI brings to the contact center.
- Enhanced customer experience: AI can enable contact centers to provide a quicker and more accurate response to initial customer inquiries, regardless of if the contact center is open or not. This can be achieved through conversational AI and other automated systems that handle common, repeatable questions, either on your website or via your IVR. By removing a portion of customers from human agent queues, we then leave human agents to answer the residual, with hopefully a shorter wait time, to further improve their customers’ experience.
- Increased agent productivity: AI tools, such as Agent Assist, empower human agents by providing them with real-time information and guidance during calls. This technology uses a number of AI components to create bespoke information, based on specific scenarios, in close to real time. AI is both listening to the conversations and providing information to the agent, which should reduce the handle time, as well as increase the agent’s ability to serve and resolve. Many of the tasks that become automated are basic and transactional in nature, adding no value to the customer, but with the agent freed up from clicking buttons, they can now concentrate more on what the customer is saying and improve resolutions futher.
- More precise intent understanding and call routing: AI’s ability to understand the specific nature of a customer’s needs isn’t new, but GenAI has boosted it. Intent recognition is used in both chatbots and interactive voice recognition (IVR), meaning any improvement in this technology has a direct impact on the front door of the contact center. AI is also being used to analyze customer data and interactions and determine the best agent for each call, improving the efficiency of call handling and ensuring that customers are connected to the right resources.
- Improved data-driven insights: Contact centers gather vast amounts of unstructured data from calls that AI is best suited to analyze – at scale much more efficiently and accurately than humans. This improved ability to understand data at scale allows contact centers to provide better insights into low level customer needs, sentiment analysis and even specific resolution dialogue. With AI adding a deepened layer of contact reason, you are now truly gaining insights from your data, not just basic data points. What has been to date very manual and difficult to collate – specific product feedback, competitor insights and new ideas for products or capabilities – is now available. This deep, far-reaching and insightful data can elevate the contact center from being seen as a cost burden to a more central part of the business.
- Better cost reduction: Using different types of automation to drive efficiency continues to be the starting point in the AI journey for many organizations. Though cost cutting has been the key driver for many organizations in deploying AI to date, it should be delivering so much more – from improved natural language IVR and automating simple conversations, to reducing AHT by surfacing real-time answers to an agent and automating after contact summaries. The continued evolution of AI has opened up a world efficiency opportunities.
Moving Forward
Adoption of AI in contact centers is showing no sign of slowing down, though the number of new and unique use cases does appear to be subsiding. Change in the contact center isn’t easy, and this slowing down of new use cases should not be seen as a bad thing. Instead, it might well allow the contact center to take stock of where it is on its AI journey and correctly plan ahead for what to do next.
Standing still is as good as going backward, but blindly moving forward on the wrong things is likely an expensive mistake to make also. Finding balance between innovation and cost reduction will be key, and understanding what is marketing hype vs a delivered reality will be as important as ever
Want to learn what others in your industry are doing, mistakes being made and where the untapped value in your contact center is right now? Contact us to start the conversation.
About the author
Wayne Butterfield
Wayne is an automation pioneer, initially starting out as an early adopter of RPA in 2010, creating one of the first Enterprise scale RPA operations. His early setbacks at Telefonica UK, led to many of the best practices now instilled across RPA centres of excellence around the globe. Customer centric at heart, Wayne also specialises in Customer Service Transformation, and has been helping brands in becoming more Digitally focused for their customers. Wayne is an expert in Online Chat, Social Media and Online Communities, meaning he is perfectly placed to help take advantage of Chat Bots & Virtual Assistants. More recently Wayne has concentrate on Cognitive & AI automation, where he leads the European AI Automation practice, helping brands take advantage of this new wave of automation capability.
