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Contact center quality managers are responsible for ensuring service excellence throughout the customer service organization. That includes optimizing interactions to meet rising customer expectations, fostering agent engagement, satisfaction and development, and meeting key performance metrics. That’s a lot to juggle, even for veteran QA managers.
What’s more, the vast majority of these responsibilities are manual tasks, requiring a considerable amount of time and effort. That’s time and effort taken from analyzing calls for quality, compliance and agent performance. As a result, insights go unseen and challenges—from performance gaps policy adherence—emerge.
Until now, tackling these challenges was a matter of prioritization. If a contact center wanted to shorten call times, for instance, it often did so at the expense of call quality. However, that changed with artificial intelligence. Today, AI-enabled contact centers are delivering on all their service promises—and they’re doing it without compromising elsewhere.
Let’s explore how AI, and generative AI in particular, is reshaping contact centers and solving their biggest challenges using the power of data.
Top 5 contact center QA challenges AI is solving today
While each contact center has its own, unique set of challenges, there are several common issues that impact every organization. Here are five of the biggest challenges quality managers face in their day-to-day roles (and how AI is helping to overcome them):
Lack of call visibility
While contact center calls are typically recorded for quality assurance and compliance purposes, that doesn’t mean that all calls are reviewed. In fact, according to CX Today, managers only review around one to five percent of all calls. The reason is simple: it isn’t humanly possible to manually review every call that comes in (and QA managers are only human after all). That means that most interactions—and the insights they contain—are simply lost.
That was before AI. Now, thanks to natural language processing (NLP) and sentiment analysis, AI-enabled contact centers can analyze 100% of calls for both verbally and nonverbally (i.e. tonal, sentiment-based) communicated insights. They can then use those insights to improve core functions, discover emerging topics and trends, and identify new revenue-generating opportunities.
Missed automation opportunities
Contact centers have long relied on “grunt work” to perform even the most basic QA, compliance monitoring and performance evaluation tasks. It’s not only time-consuming and inefficient; it’s inconsistent and even harmful to agent morale (and, consequently, retention).
Many of these manual processes, however, are ripe for automation. With generative AI, it’s easier to delegate tasks to AI than ever before. Now, quality managers can create scorecards and establish evaluation criteria in hours—rather than the days it used to take. That’s a gamechanger in an organization where speed and efficiency directly impact the bottom line
Inconsistent evaluation criteria
Quality managers often struggle with maintaining uniform standards across evaluators and teams. Without standardized quality monitoring frameworks, different agents may be assessed with varying levels of strictness, leading to biased or unfair evaluations and employee dissatisfaction. That’s a serious problem for an industry plagued by high attrition levels. In fact, research by SQM Group puts yearly agent turnover at 38%.
Fortunately, advances in AI are helping contact center leaders reverse this trend. One particularly effective application is the use of generative AI to personalize agent coaching and development. By analyzing conversations, contact center AI can identify agent performance gaps and turnover risks and generate actionable insights for improving critical skills, job satisfaction and engagement.
Difficulty linking QA to business outcomes
Quality managers also struggle to prove the impact of quality programs on broader metrics like average handle time (AHT), agent score and others. Without integration between QA tools and business intelligence platforms for dashboards, the value of quality initiatives remains unclear to leadership.
AI enables managers to link QA initiatives to their real-world outcomes. Using GenAI-powered conversational intelligence, they can trace the effectiveness of programs and generate actionable insights for further improvement. What’s more, QA data can be leveraged across business platforms to uncover deeper insights and additional opportunities. Managers can then share these findings with business leaders to validate QA methodologies, demonstrate program success and justify further investment.
Outdated systems and processes
Despite the technological leaps customer service has taken over the past several years, many contact centers continue to rely on outdated systems and processes. Take knowledge bases, for example. For years, contact centers codified their policies, best practices, FAQs and more in static knowledge bases. Without the addition of new information from conversational analysis, the resources in these repositories would quickly become outdated, limiting their usefulness in decision making.
That changed with the advent of generative AI. With GenAI-powered conversational intelligence, agents and decision-makers can now ask simple, plain language questions and get relevant answers pulled from the call transcript. No more deep searching of rigid keywords to memorize. No more unnecessarily long wait times.
Answering the call with conversational intelligence
Powered by generative AI, conversational intelligence isn’t just solving the most pressing contact center challenges; it’s empowering quality managers to identify and develop opportunities for improvement in every area. From strengthening agent performance and morale to increasing customer satisfaction and operational efficiency, GenAI-driven solutions like U-Discover by Uniphore, are turning contact center conversations into jet fuel for operational efficiency. And in today’s competitive customer service environment—where every second of every conversation counts—that’s a serious advantage.
Unlock next-level service excellence with AI
See how U-Discover can drive deeper insights, smarter actions and better outcomes for your organization.
