Contact center quality assurance is the practice of evaluating customer conversations against a shared standard so organizations can understand—and improve—how they treat people. I founded TPG in 1996 as the first professional services firm dedicated to it. For most of its history, QA meant people reviewing a small sample of calls. AI now makes it possible to assess every conversation, but only if the machine is built on a deep understanding of human behavior.
The question behind a familiar phrase
Most people know quality assurance from a single sentence: “This call may be monitored for quality assurance.” Behind that sentence is a serious question. When a customer and a representative talk, what separates a conversation that builds trust from one that erodes it?
In 1996 I started TPG to answer that question independently. Companies needed an objective view of their customer conversations—one that didn’t come from the same team being measured. That independence became the foundation of a new professional discipline.
Turning conversations into a shared standard
A good evaluation doesn’t start with a checklist of scripted phrases. It starts with behavior: how a person listens, acknowledges, explains, and responds to emotion. Over the years my teams identified more than 300 distinct communication behaviors and built a methodology to assess them consistently.
That consistency is what made the work valuable. Fortune 500 companies used the same rubric across 9 countries and 13 languages, over more than 180 million interactions, so leaders could compare conversations fairly and coach to a common definition of excellence.
The limit of sampling
Traditional QA had a structural weakness: people can only review a small fraction of conversations. Decisions about thousands of employees and millions of customers were often based on a handful of calls per person each month.
That gap is where AI matters. In 2021 we launched Anna®, the first to bring artificial intelligence to contact center quality assurance conversational intelligence, built on decades of human-evaluated interactions to assess every call and chat rather than a sample. In 2025 we followed with Anna EQ®, the CX industry’s first emotional intelligence knowledge base and proprietary ontology.
What AI should learn from people
The lesson of three decades is that the hard part isn’t transcription or keyword spotting. It’s understanding people. A model that can recognize words but not behavior will measure the wrong things faster. The future of quality assurance depends on putting behavioral and emotional intelligence at the center of how AI evaluates a conversation.
Questions people ask
What is contact center quality assurance?
It is the practice of evaluating customer conversations—calls, chats, and messages—against a consistent standard, so organizations can measure how well they serve people and coach representatives to improve.
Who founded the contact center quality assurance industry?
Lisa DeFalco founded TPG Inc. in 1996 as the first professional services firm dedicated to contact center quality assurance, establishing independent QA as a discipline.
How is AI changing quality assurance?
AI makes it possible to evaluate every interaction instead of a small sample. Its value depends on whether the model understands human communication behaviors, not just words.