In many contact centers, persistent performance challenges are often attributed to gaps in knowledge.
Yet, a closer look at coaching conversations reveals a strikingly consistent observation: agents already know what to say. They have completed training, passed assessments, and demonstrated familiarity with the conversation skill requirements and processes.
On the surface, this suggests a well-prepared workforce. And still, performance remains inconsistent. As an industry, we continue to work to reduce escalations and repeat calls while improving our overall voice of the customer scores.
This contradiction reflects a deeper reality. The issue is not a lack of knowledge. Instead it suggests it is the inability to consistently apply that knowledge when it matters most.
Recently, a senior leader in a contact center described a situation that illustrates this challenge clearly. After investing 12 weeks in comprehensive training, their agents had successfully completed certification and demonstrated strong knowledge proficiency in controlled environments.
However, when those same agents transitioned to live customer interactions, performance broke down almost immediately. Even the most basic calls became difficult to manage. Agents hesitated, lost their flow, and frequently escalated interactions that should have been resolved independently.
The leader’s frustration stemmed from a fundamental realization that despite extensive training, agents were not prepared for the unpredictability of real-world conversations. They knew the material well enough; however, they did not yet know how to think with it.
This phenomenon aligns with what research in this article, “Training Transfer: An Integrative Literature Review” by Lisa A. Burke and Holly M. Hutchins in Human Resource Development Review, identified as the “transfer problem.” This is where training fails to translate into sustained workplace performance.
The Gap Between Knowledge and Execution
Traditional contact center training models are designed to transfer information. They ensure agents can recall procedures and follow workflows. However, real performance is defined by how effectively agents respond in dynamic, real-time interactions.
On average, I listen to 100-plus calls a month across industries, and one truth I can count on is every customer interaction introduces variability from emotion to complexity. These moments require decision-making, not memorization.
Our research on training effectiveness emphasizes that success depends on learning transfer, which is the ability to apply knowledge on the job.
Yet this remains one of the most persistent gaps in organizational performance, reports the CDC. When performance is built on memorization, it becomes fragile, thus making it reliable only under predictable conditions.
Where Performance Begins to Break Down
This reliance on scripted knowledge leads to consistent breakdown patterns. Customer experiences (CXs) vary widely.
As an industry, we have seen an increase in escalations as agents defer decisions. Agent confidence has also declined, particularly in ambiguous situations. And operational efficiency suffers as interactions take longer to resolve.
When performance is built on memorization, it becomes fragile, thus making it reliable only under predictable conditions.
These outcomes are typically not from a lack of effort or willingness to do a good job. Instead, they reflect a system that has not prepared agents to operate independently in dynamic environments.
The Emerging Role of AI: Information Without Judgment
As organizations look to address these gaps, many are turning to AI as a solution. AI-powered tools can now surface answers in real time, guide agents through workflows, and in some cases provide coaching directly to our teams.
This can be a meaningful advancement. AI can effectively eliminate the knowledge retrieval problem by putting the right information in front of agents at the right moment.
However, this is where a critical distinction emerges. AI can provide information, but it cannot replace judgment.
When agents are presented with AI-generated guidance, they must still interpret the situations, decide how to apply that information, and adapt it to the specific customer contexts. In fast-moving interactions, this requires situational awareness and critical thinking, which comes through experience.
Without these human-provided capabilities, AI risks becoming just another script to be followed rigidly in some cases, ignored in others, and inconsistently applied overall. The real opportunity, therefore, is not just to equip agents with AI tools, but to train them in how to use them effectively.
As an industry, our real focus should be on helping agents interpret AI recommendations in context and understanding when to follow the guidance and when to adapt. In this sense, AI is amplifying the need for more development for our teams.
A Leadership Lens on Performance Sustainability
From a leadership perspective, a critical question emerges: If supervisors stepped away, would performance remain consistent?
If performance depends on constant oversight, it is being sustained. However, it is not truly embedded into the performance of the contact center. Organizations that scale effectively do so by strengthening decision-making capability and avoiding increased supervision.
Sustainable performance scales through people who are equipped to think, decide, and act with confidence.
Performance happens in real time, often under pressure. Research shows that under time constraints, individuals shift to simplified decision strategies, which can impact outcomes. Also, cognitive load further affects how effectively people process and act on information in complex situations.
Without the ability to manage these dynamics, even well-trained individuals struggle to execute consistently.
The Shift to Capability-Based Development
High-performing organizations are increasingly shifting their focus from simple knowledge transfer to true capability development, emphasizing how agents think rather than just what they know.
This approach prioritizes building key competencies such as judgment, which at its core is the ability to make the right decisions within context. The top-performing agents are those who act decisively while skillfully navigating the unexpected.
I was reminded of the power of these capabilities recently while traveling. As I scanned my boarding pass at the airport, a flight attendant greeted me with, “Oh Mrs. Vance, today is your 30-year flying-with-us anniversary. Thank you for your loyalty, and I’m going to send you a gift.”
The “gift” came in the way of 2,500 flying miles added to my account. Now, anyone who flies knows this doesn’t get a person very far—maybe a free snack—but the sentiment meant more to me.
There was no script for that moment. It required judgment and the confidence to personalize the interaction in real time. It was a small gesture, but it transformed a routine transaction into a memorable experience demonstrating exactly what capability-driven performance looks like.
When these capabilities are fully developed, performance becomes more consistent and less reliant on direct supervision.
As a result, organizations that embrace this shift experience meaningful improvements: conversations become more natural and effective, escalations decrease, and coaching evolves from a corrective exercise into a developmental one.
Leaders, in turn, spend less time intervening in day-to-day issues and more time strengthening their teams’ capabilities. Ultimately, performance transitions from being situational and variable to systemic, embedded in how individuals consistently think and act across the organization.
The Evolving Role of Leadership
Leaders today are called to evolve from directive managers into developmental coaches, shifting away from simply telling toward thoughtfully guiding, from correcting mistakes to intentionally developing capability, and from managing execution to cultivating stronger, more independent thinkers.
Sustainable performance scales through people who are equipped to think, decide, and act with confidence. But too often that is not happening.
At its core, the challenge organizations face is a gap in capability. Agents have been trained to know what to do; however, they are missing being fully developed to determine how and when to do it.
Until this gap is addressed, performance will continue to fluctuate, and even the most advanced tools, including AI, will fall short of delivering their full potential.
While AI can enhance efficiency and provide insight, it cannot replace human judgment. This fundamentally human capability remains essential to delivering exceptional experiences and sustaining long-term performance.
A Final Consideration
As organizations evaluate their learning strategies, a critical question emerges:
Are we developing knowledge? Or are we developing judgment?
Knowledge builds awareness. Judgment drives performance.
Organizations that focus on developing how people think position themselves for more consistent, scalable success.