In today’s contact centers, training isn’t just about transferring knowledge – it’s about building adaptable, confident agents who can navigate real customer scenarios with empathy, accuracy, and speed.

The challenge? Most traditional training programs focus almost entirely on formal instruction: onboarding presentations, policy manuals, and classroom style learning. This approach falls short of preparing agents for the complexity and pressure of live interactions. That’s because the most effective learning doesn’t happen in a single moment, it happens over time through experience and interaction. And yet many teams overlook the biggest drivers of real performance: on-the-job learning and feedback from others.

The 70:20:10 learning model offers a more complete framework for how agents learn and grow. It shows that success is about what’s practiced, shared, and experienced.

What is the 70:20:10 Learning Model?

The 70:20:10 framework suggests that employee learning and development is most effective when it’s broken down into:

• 70% experiential learning: on the job experiences, decision-making, and problem-solving.
• 20% social learning: feedback, mentoring, and collaboration.
• 10% formal learning: structured courses, workshops, or classroom training.

Why It Works in Contact Centers

Contact centers are dynamic, high-volume environments where agents are constantly expected to:

• Handle unpredictable scenarios
• Apply complex procedures and soft skills in real time
• Continuously improve without lengthy classroom lectures

In this setting, the 70:20:10 model is especially relevant. Formal training may help an agent understand the basics, but it’s daily repetition, problem-solving, and peer support that build mastery and confidence.

Using AI-Powered Practice to Complement the 70:20:10 Model

While the model works on its own, many companies struggle with how to implement it effectively – especially at scale. That’s where AI-powered practice becomes a valuable accelerator.

• 70% Experiential Learning
  • Feature: AI powered practice tools provide realistic, simulated customer conversations that mirror the wide range of scenarios agents encounter daily – from basic account questions to high-pressure escalations.
  • Advantage: These lifelike interactions give agents hands-on experience without putting real customer relationships at risk.
  • Benefit: Agents build real-world decision-making skills in a safe environment. Agents can practice as often as needed to reinforce learning and reduce live call anxiety.
• 20% Social Learning
  • Feature: Built-in feedback tools allow managers to score, annotate, and review practice sessions with agents.
  • Advantage: Practice sessions can be scored, annotated, or discussed in coaching sessions. This creates an easy way to integrate performance discussions, coaching, and peer reviews into daily workflows.
  • Benefit: Strengthens learning through feedback and discussion, helping agents internalize what’s expected of them.
• 10% Formal Learning
  • Feature: AI-powered practice can be aligned with existing training modules, onboarding programs, and learning paths.
  • Advantage: It serves as a hands-on complement to formal instruction, allowing agents to apply theoretical knowledge in a practical setting immediately after learning it.
  • Benefit: This turns passive content consumption into active skill development, making learning more engaging, practice, and easier to retain over time.

Real Impact: From Novices to Experts Faster

AI-powered simulation tools are often described as “batting practice” for agents. Just like athletes improve by repeating game-like conditions, contact center employees improve when they can rehearse real scenarios, get feedback, and try again.

This means:

• New hires start faster with fewer mistakes and experienced agents sharpen their skills
• Managers can identify each agent’s strengths and areas for improvement, delivering personalized coaching and development plans based on performance

The 70:20:10 learning model offers a practice, proven framework for developing confident employees – especially in environments where customer interactions are complex and high stakes. But making the most of it requires more than theory.

By integrating AI-powered practice into your learning strategy, you’re not replacing any part of the model – you’re enhancing it. You’re allowing agents more chances to learn by doing, more opportunities to receive timely feedback, and more ways to bring formal training to life.

The result? A team that’s not just trained – but confidently ready.

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