Artificial Intelligence (AI) continues to reshape industries, and the contact center sector is at the forefront of much of the adoption as companies battle for Customer Experience (CX) supremacy. Although AI has become a driving force for those who choose to adopt it at scale, challenges remain around balancing AI-led and human experiences to optimize customer satisfaction and operational efficiency.
The Convergence of AI, CX, and EX
Avaya‘s Global Vice President and Chief Architect David Funck told CX Today how AI’s role in the contact center has evolved beyond mere self-service capabilities.
Instead of approaching AI as simply a way of deflecting customer interactions away from human agents, an enterprise that can orchestrate AI engagements across multiple touchpoints will have much better success. Getting this balance right between how, when, and where to use AI versus humans can benefit metrics like agent retention and satisfaction. Typically, call centers churn agents at about 30-45%, but according to Metrigy, integrating AI can reduce this figure to 10-15%, an average range considered ‘good’.
“We’re seeing AI not just solve customer problems but also improve the agent’s experience,” Funck explains. “If we can use AI to handle mundane tasks and leave human agents to focus on interactions that require empathy and complex problem-solving, it enhances job satisfaction, customer, and employee retention.”
Is AI Living Up to the Hype?
Despite AI’s potential, reality does not always match expectations. Funck notes that while AI-driven experiences are becoming increasingly sophisticated, they still come at a cost. Some enterprises find that AI solutions are priced similarly to human labor. This challenges the assumption that AI implementation will automatically lead to cost savings. So, contact center buyers must understand how scaling AI across their operations will ultimately lead to value generation and economies of scale-type savings.
However, customers are more demanding when they interact with brands, expecting some level of recognition or personalization from their experience. So, one key value of AI in the contact center lies in its ability to personalize experiences and improve efficiency. Funck points out that AI solutions tailored to specific verticals—such as healthcare, retail, or financial services—tend to perform better. “The more granular, and personalized, these AI solutions are, the better the outcome,” he says.
When we talk about the power of Machine Learning and Predictive Analytics, size truly does matter, especially when it comes to the data a business can generate and analyze. Larger enterprises have a distinct advantage because they can amass substantial datasets, which are crucial for these advanced technologies to operate effectively. With a rich pool of data, organizations can develop sophisticated predictive models that not only anticipate market fluctuations but also streamline operations and deliver personalized customer experiences, ultimately enhancing their competitive edge in the fast-paced business world.
Funck says, “I think it’s a medium and large enterprise endeavor. I don’t see your 200-agent contact center investing in predictive analytics; the data just isn’t meaningful enough to warrant that type of investment.”
AI-Human Coexistence
One hurdle facing enterprises is seamless handover between an AI interaction and human agents. Funck emphasizes the importance of orchestration, which allows businesses to integrate AI solutions flexibly without being locked into proprietary platforms. Weaving current investments together with new AI solutions can aid this collaboration between humans and AI.
“We’re giving enterprises the ability to modernize their AI-driven workflows while preserving existing integrations,” he explains. Avaya’s strategy focuses on ensuring backward compatibility, allowing businesses to integrate new AI capabilities without completely overhauling their infrastructure.
For a vendor with a strong foothold in some of the largest global businesses, the ability to sweat assets, upgrade functionality by adopting AI, and migrate to the cloud at a pace that suits the customer is crucial.
The Balancing Act
Have you ever wanted to speak to a human directly because your problem is unique and complex? Funck says that customers should always be able to speak to a human when necessary, rather than feeling trapped in an automated loop.
“We’ve all had experiences where we know our issue is too complex for AI, yet we struggle to reach a human,” Funck acknowledges. “At the same time, for simpler inquiries, AI should be able to resolve them quickly without unnecessary human intervention.”
This balance is crucial not only for customer satisfaction but also for maximizing AI’s return on investment. Funck advises enterprises to carefully evaluate the areas where AI can be most effective, ensuring it enhances—rather than hinders—the overall experience.
AI in Retail
We spoke to one of Avaya’s large retail customers facing rising call volumes, leading to long wait times and customer dissatisfaction. The company implemented Avaya’s contact center solution to enhance efficiency, integrating AI-driven virtual agents to manage routine customer inquiries. These virtual agents handled common questions about order status, product details, and return policies, offering quick, automated responses and reducing the burden on human agents.
The AI system seamlessly transferred interactions to live customer service representatives for more complex inquiries. This handoff included a summary of the AI interaction, ensuring that human agents had the necessary context to assist customers efficiently. By incorporating machine learning algorithms, the system continuously improved based on customer interactions and agent feedback, refining its ability to respond accurately.
The results were significant: wait times were reduced as AI handled routine queries, allowing human agents to focus on higher-value interactions. Customer satisfaction improved as they received quicker resolutions and smoother escalations when needed. Additionally, agent productivity increased as representatives could concentrate on more complex issues rather than repetitive tasks.
This AI-driven approach also led to cost efficiencies, reducing the need to pull in additional staff during peak hours and maintaining service quality.
The Future of AI in Customer Service
Looking ahead, Funck predicts a growing proliferation of AI point solutions tailored to specific industry needs. He foresees shifting from one-size-fits-all AI models to more specialized applications that enhance CX and EX.
“We don’t see a single, overarching AI solution solving all enterprise contact center challenges,” Funck says. “Instead, companies should focus on integrating multiple AI capabilities to create a seamless, intuitive experience for customers.”
Ultimately, the key to success lies in planning and the execution of your AI strategy. If your customers demand choice around how and when they interact with you then AI will deliver on part of that strategy. With the right implementation, enterprises can achieve the best of both worlds: a future where AI enhances, rather than replaces, human expertise in customer service.
