AI in the Contact Center: Process Reinvention Is the Real Game-Changer

September 2025

Artificial intelligence (AI)-enabling a contact center is such a complex undertaking that adding a new or updated application may be the easiest part. The purpose of applying AI in these departments is using technology to execute or augment a function or task handled by a human, e.g., answering questions, conducting transactions, locating policies and procedures, automating the quality evaluations, and more. For contact centers to realize the expected benefits of introducing an AI-powered solution, any manual steps or activities that are impacted must also be reimagined and reengineered to inject intelligence into their workflow. If this is a new process, such as automated post-interaction summarization, changes to procedures and operations should be relatively simple. However, when AI is intended to alter or fully replace an existing practice, like automated quality management (AQM), all actions, work efforts, and systems tied to traditional QM will need to be modified or eliminated. Below are three examples where embedding AI-based applications into the contact center requires changes to the current operations and processes: 

1. Customer-facing conversational AI (CAI) self-service platforms – are designed to complete some tasks previously performed by live agents. However, it’s not likely to be a clean cut-over to the CAI system, because a portion of customers may still prefer to work with a human on activities that have been automated or need help finishing a self-service transaction. Because of this, current manual procedures need to remain in place; however, DMG recommends they be reviewed and updated, as executing part of the process via an agent augmentation application may be possible. Potential benefits from adding more customer intents to a generative AI (GenAI)-enabled self-service solution include a decrease in interactions requiring agent assistance, improving the customer experience (CX) and productivity, and reducing costs. As routine and less complicated conversations are handled by CAI, the employee experience (EX) is also enhanced because agents prefer addressing more complex contacts. 

2. Real-time guidance (RTG) solutions – fall into a growing category of agent augmentation or assist applications. These capabilities listen to or read both sides of a conversation to identify customer intents and deliver information and direction to the employee in near-real-time. This allows the agent to concentrate on helping the consumer instead of searching for an answer or policy to process a request. Although only a portion of the interaction is automated by the AI-driven solution, RTG users should expect to see an average handle time (AHT) reduction of anywhere from five seconds to minutes, depending on the request and their average inquiry duration. However, there are other associated benefits: they improve contact quality and the CX by giving agents the correct knowledge or procedure, as well as boosting first contact resolution (FCR) rates and the EX.

3. Automated quality management applications – leverage AI-powered conversation (speech and text) analytics technology, transcription, GenAI, and business rules to identify, classify, and evaluate customer interactions based on user-defined quality criteria. AQM solutions can score up to 100% of voice- and text-based communications to determine how well employees adhere to policies and procedures; detect agent training gaps; understand customer needs and wants; gain insights into employee engagement; and discover operational opportunities. In most implementations, AQM replaces outdated manual QM programs. Significant contributions can be gained from AQM, including objectively reviewing all interactions on a timely basis; receiving statistically valid findings regarding contact center, team, and agent performance; bettering quality and effectiveness; reducing QM process costs; freeing up supervisors to conduct coaching; and more. AQM enhances the CX, EX, and productivity, but to produce full benefits, traditional QM programs must be discontinued. 

Earlier versions of CAI, RTG, and AQM solutions have been available for years, but GenAI changed their trajectory and adoption rate by vastly increasing ease of use and the accuracy/validity of their findings and agentic AI is now taking it to the next level. 

Final Thoughts

AI’s game-changing set of technologies can greatly enhance business outcomes for a contact center and its agents. But to get the most out of these applications, managers need to be all in and invest the time to identify and make changes to underlying processes and workflows. As importantly, they must be transparent with their supervisors and agents to gain buy-in and support for these capabilities.