AI for CX Summit – Day 2 Session 2 Recap

How do you know if coaching is actually working? And if it’s not—how do you fix it?

That’s the question tackled in this high-impact panel discussion at the AI for CX Summit, where leaders from Intelication and AmplifAI came together to explore how AI is transforming the way contact centers manage coaching, agent development, and performance accountability.

Moderated by Scott Logan, Chief Marketing Officer at AmplifAI, the conversation featured insights from three industry experts:

• Stephanie Rubin, Managing Partner at Intelication
• Calli Wright, Managing Partner at Intelication
• Lauri Stanek, Customer Success Leader at AmplifAI

Together, they walked through real-world examples, customer case studies, and emerging best practices for aligning performance data with targeted actions—while freeing managers to focus more on people than process.

Who This Panel Is For

This session was designed for CX and contact center leaders looking to:

• Improve agent performance through better coaching—not just more of it
• Measure the impact of coaching, not just the frequency
• Replace gut feel with data when setting timelines and training plans
• Scale personalized coaching across large teams without overloading supervisors
• Use gamification to motivate long-term behavior change, not just short-term spikes

Whether you’re still using manual QA or already exploring auto QA and AI coaching, this session offered a clear path forward for developing your teams faster—with less guesswork and more impact.

5 Key Takeaways from the Intelication Panel

1. Most Teams Aren’t Measuring Coaching Effectiveness—Yet

Many contact centers track how often coaching happens, but very few track if it works. That’s a problem.

As Stephanie Rubin noted, forward-thinking teams are starting to connect coaching to real outcomes—tracking performance changes post-session using sentiment, QA scores, CSAT, and more. The most advanced are even measuring a “coaching delta”—the change in performance pre- and post-coaching—to pinpoint what’s improving and what’s not.

“If agent performance isn’t improving after consistent coaching, maybe the issue isn’t the agent.”

— Stephanie Rubin, Intelication

2. AI Can Automate Coaching Targets—and Track What Happens Next

With the rise of auto QA and AI-based scoring, leaders now have objective, real-time visibility into agent behaviors—tone, empathy, compliance, and more. That same data can be used to:

• Trigger coaching when behaviors drop below benchmark
• Recommend what to coach (not just who)
• Track whether improvement happens after intervention

Lauri Stanek shared examples of BPO and telecom clients using AmplifAI to connect frontline data to coaching tasks—resulting in measurable lifts in First Call Resolution (FCR), AHT, and overall customer experience.

“We’re moving from whack-a-mole coaching to targeted development based on actual performance data.”

— Lauri Stanek, AmplifAI

3. Personalized Timelines Drive Better—and Faster—Improvement

Traditionally, leaders gave agents 30–60 days to improve with little personalization. AI is changing that.

Calli Wright described how smart platforms can now calculate realistic timelines for improvement based on:

• The agent’s current skill gap
• Past coaching history
• Role complexity
• Performance of top peers in the same environment

This allows managers to set glidepath goals—smaller, achievable milestones toward proficiency—and course-correct mid-cycle when performance veers off track.

“It’s not just coaching better—it’s coaching smarter. AI helps us do both.”

— Calli Wright, Intelication

4. Coaching Must Be Behavior-Based—Not Just Metric-Based

“Your empathy score is low” doesn’t tell an agent what to do differently.

AI now enables leaders to pinpoint which behaviors need work—such as reflective listening or escalation handling—across 100% of interactions. This helps supervisors skip manual review and go straight to development.

Lauri also emphasized how integrating LMS content into coaching workflows creates a full-circle learning experience—tying metrics to behavior, behavior to training, and training to results.

“Let the technology do the heavy lifting so you can spend time actually developing your people.”

— Lauri Stanek, AmplifAI

5. Gamification Works—When It’s Built on Real Growth

Games are great—but only when tied to real goals.

As Stephanie explained, novelty wears off fast when agents realize they’re earning points for speed, not quality. The most effective gamification strategies:

• Reward skill development, not just call volume
• Create personalized challenges based on performance gaps
• Blend team-based competition with individual milestones
• Support agent wellness and engagement, not just metrics

AmplifAI clients have seen improvements in both agent satisfaction and performance by combining data-driven coaching with gamified progress—especially for mid- and low-performers who may be overlooked in leaderboard-only models.

“The best gamification strategies aren’t just fun—they’re functional. They build careers, not just dashboards.”

— Stephanie Rubin, Intelication

Final Thought: You Can’t Improve What You Don’t Measure

This session reinforced a clear message: data-first coaching works—if you measure the right things. AI gives leaders the tools to:

• Track coaching effectiveness
• Predict realistic improvement timelines
• Coach at the behavior level
• Scale progress across every agent—not just the top 10%

But you need the right systems and partners to make it all work.

Expert Quote to Remember

“You can’t manage performance if you’re not measuring coaching. The most impactful leaders are using AI not just to analyze agents—but to develop better coaches too.”

— Lauri Stanek, AmplifAI

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