Contact center AI ROI shifts toward resolution quality and governed execution

As contact center artificial intelligence evolves, performance will be judged by resolution quality rather than the number of interactions handled by machines. Bob Laliberte, principal analyst for networking and observability at theCUBE Research, and Zeus Kerravala, principal analyst and founder of ZK Research, emphasized this point during "The AI ROI in Contact Center Summit" summit.

They highlighted that organizations must adopt end-to-end resolution backed by connected data, governance, and measurable business outcomes. The focus shifted from traditional metrics such as containment and deflection to customer satisfaction, effort, employee productivity, cost, and growth. The analysts recommended starting with a well-defined, high-value problem and establishing baseline metrics before deploying AI.

Governance should be an ongoing practice rather than a one-time checkpoint, enabling faster adoption of AI initiatives. The adoption of AI in contact centers will also alter the balance between human employees and digital agents, with humans handling more complex tasks such as emotionally sensitive situations and judgment-based interactions.

Supervisors will need to manage this blended workforce more effectively. Laliberte and Kerravala advised a controlled approach, starting with one customer journey, documenting the workflow and data requirements, setting baseline metrics, and testing both routine interactions and edge cases before scaling up.