Remote Contact Center Engagement: Beating the Industry by 11 Points and Crawling with AI

Why the most irrational thing you can do with AI is run, and how a “crawl” approach protects your human systems from execution drift.

This Fast Leader Show episode covers remote Contact Center Engagement: Beating the Industry by 11 Points and Crawling with AI. Here is what the conversation covers, then the key insights.

Jason Mercer-Pottinger shows how home dialysis teams put empathy ahead of outdated speed metrics. His crawl-walk-run approach keeps clinicians in the loop as AI matures.

Executive Summary: Key Insights
Frontline Autonomy Prevents Execution Drift:
Stripping back traditional call center efficiency metrics like average handle time allows remote agents to support vulnerable home dialysis patients without systemic friction.
Governed AI Integration Protects Operational Integrity:
Adopting a crawl-walk-run framework keeps human clinicians in the loop and protects patient safety from uncalibrated technology.
Systemic Servant Leadership Sustains Remote Cohesion:
Granting true decision-making authority to frontline managers maintains cultural alignment and manager effectiveness scores 11 points above industry benchmarks.

When a home dialysis patient calls customer care at two in the morning because an alarm is sounding on their machine, they are at their most vulnerable. Across multi-country remote operations stretching from Canada to Brazil, Jason Mercer-Pottinger’s teams handle these critical moments every day. They do not hurry the patient off the phone to meet a traditional average handle time metric.

If that call takes an hour, it takes an hour.

Most enterprise operating models force remote contact centers into a constant battle between speed and empathy. When leaders try to solve this by layering fast digital tools on top of broken operational workflows, they inadvertently accelerate Execution Drift. The Leadership Execution Institute’s research shows that without supportive environmental scaffolding, giving people new mandates or software tools only increases cognitive load and causes performance to degrade under pressure.

I missed this structural reality myself for years.

Sit with that for a moment.

JMP’s team achieved manager effectiveness scores 11 points above the industry average because they updated the operating environment rather than blaming the workforce. By implementing a governed crawl-walk-run AI framework and pushing decision-making authority down to frontline leaders, they established an unbroken Kinetic Chain of Execution. Human beings stay in the loop to protect patient safety, while the system handles the administrative noise.

Momentum.

When we eliminate the friction of outdated administrative metrics, leaders stop managing out of self-protection and start serving their teams. Pushing authority to the front line creates an environment where people feel safe to report errors, share best practices, and deliver reliable care. The operating architecture holds the standard so human biology does not have to carry the weight alone.

Operational Performance and Remote Patient Care: Frequently Asked Questions

How do traditional contact center metrics create execution drift in remote healthcare operations?

Traditional metrics like Average Handle Time (AHT) force frontline agents to choose between administrative compliance and patient safety. When remote workers are pressured to end calls quickly, cognitive load increases and agents default to biological autopilot to protect themselves from burnout. This mismatch between human capacity and legacy administrative designs creates execution drift, resulting in repeat calls, poor care quality, and invisible financial leakage across the P&L.

Why does a crawl-walk-run approach to AI governance protect operational margins?

Deploying generative AI on top of uncalibrated or broken operational workflows accelerates chaos at machine speed, creating AI slop and customer frustration. A phased crawl-walk-run framework embeds technological scaffolding deeply into existing workflows while maintaining human-in-the-loop oversight. This deliberate approach protects enterprise margins by preventing costly compliance failures, preserving clinical decision quality, and ensuring technology reduces administrative friction rather than compounding it.

How does frontline leadership authority improve manager effectiveness in distributed teams?

Frontline authority shifts leadership from top-down enforcement to systemic guidance and reinforcement. When frontline managers are given direct decision-making authority within clear environmental guardrails, administrative drag decreases and psychological safety rises. Removing the constant threat of micromanagement allows remote managers to focus on coaching and overcommunication, which directly elevates manager effectiveness and team cohesion across distributed regions.

Predictably Irrational

Human beings are predictably irrational, especially when we are placed under immense pressure and handed shiny new tools. When senior contact center leaders are bombarded by C-suite demands and marketing hype to accelerate artificial intelligence adoption, their biological instinct is often to sprint.

This rush activates cognitive biases like overconfidence and fear of missing out, leading to scattergun technology deployments. We think the technology will magically solve our operational friction, but instead, it creates uncalibrated “AI slop” that fractures the very human culture we rely on.

Yet, there is another way AI must “crawl.” Jason Mercer-Pottinger, a healthcare executive leading a fully remote, multi-country dialysis support operation at Vantiv, achieves manager effectiveness scores a staggering 11 points above the industry average.

How does he preserve this performance anomaly under immense technological pressure? By acting rationally in an irrational market.

He avoids the scattergun approach, protecting his high-performing human system from execution drift by intentionally slowing down.

In this episode of the Fast Leader Show, we explore the behavioral economics and operational realities of sustaining engagement by carefully governing our tools rather than letting them govern us.

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The Behavioral Trap of “AI Slop”

When leaders experience the pressure to innovate, they often layer new artificial intelligence tools directly on top of existing, broken workflows. In behavioral terms, this is execution blindness, focusing on the immediate implementation without considering the downstream human consequences.

This scattergun approach creates “AI slop,” a phenomenon where technology disrupts the customer and agent experience because it lacks alignment with the organization’s true operational reality.

The Power of Systemic Servant Leadership

Instead of traditional, ego-driven management, sustaining world-class engagement requires pushing autonomy to the front lines. Vantiv treats its frontline leaders as “mini CEOs,” empowering them to make the right decisions for patients in critical moments. This servant leadership methodology is not just a motivational poster; it is a systemic structure that flattens hierarchies and connects every remote worker directly to the overarching mission of saving lives.

The “Crawl, Walk, Run” Framework for AI Integration

To combat the irrational urge to move too fast, Mercer-Pottinger relies on a disciplined “crawl, walk, run” approach. By crawling first, organizations can test if an AI tool actually adds value to the patient journey and keeps the human in the loop. If a tool fails or hallucinations occur, a crawling pace allows leaders to pull it back without having exposed the entire organization to a catastrophic failure.

Building Psychological Safety in Remote Teams

In a fully remote environment, fear is the enemy of execution. When supervisors and agents are isolated, they must feel psychologically safe to report failures and share best practices without the threat of punishment. By stripping back traditional, rigid contact center metrics like punishing an agent for taking an hour to properly support a vulnerable patient the system reduces anxiety and allows intrinsic motivation and genuine care to thrive.

Developing AI Acumen to Navigate C-Suite Pressure

As AI forces a massive transformation across industries, leaders cannot afford to be passive observers. They must develop “AI acumen”—the technical and operational discernment required to understand what these tools can and cannot do. This acumen gives contact center leaders the evidence and confidence to push back against C-suite executives, ensuring that only ethical, value-driving technology is integrated into the workflow.

Preserving Manager Effectiveness Against Execution Drift

Our natural human tendency is to seek quick fixes for complex problems. The marketing hype surrounding AI plays directly into this cognitive vulnerability, promising instant transformation.

But as Jason Mercer-Pottinger’s 11-point engagement lead proves, sustainable excellence requires us to override our impulses. By intentionally slowing down, deploying a governed “crawl” strategy, and prioritizing psychological safety, you can protect your human systems from the entropy of AI slop.

To prevent execution drift from eroding manager effectiveness, listen to the complete operational breakdown in this episode of the Fast Leader Show.

• Connect with the Guest:Follow or Message Jason Mercer-Pottinger on LinkedIn.
• Evaluate Your Systems:Discover the science of closing the gap between technological intent and behavioral reality at the Leadership Execution Institute.
• Explore Ethical Healthcare Tech: Join JMP at the Contact Center AI Association (CCAIA) Phoenix Chapter.

Key Tips and Takeaways

• Prioritize the Human in the Loop: Never deploy AI that completely removes the human element, especially in complex or emotionally sensitive environments like healthcare.
• Embrace the “Crawl”: Implement AI in small, highly monitored workflows where you can easily roll back changes if they don’t produce a clear return on investment.
• Flatten the Hierarchy: Use servant leadership to remove ego and empower frontline leaders with the autonomy to act as mini-CEOs.
• Redefine Your Metrics: Traditional efficiency metrics (like Average Handle Time) can incentivize the wrong behaviors; strip them back if they conflict with your core mission of quality care.

Pros and Cons of AI Integration Velocities

The Scattergun Approach (Running)

• Pros: Satisfies immediate C-suite pressure; creates the appearance of rapid innovation and modernization.
• Cons: Layers technology over broken workflows; causes high rates of hallucinations and “AI slop”; risks fracturing high-performing cultures and causes unrecoverable execution drift.

The Crawl, Walk, Run Approach (Crawling)

• Pros: Protects existing culture and manager effectiveness; allows for ethical adoption and keeping the human in the loop; highly reversible if the ROI is not realized.
• Cons: Requires leaders to have difficult, evidence-based conversations to push back against executive impatience.

Top 10 Proven Steps to Preserve Performance Under Technological Pressure

1. Define the Business Problem First: Do not adopt AI for the sake of AI; clearly articulate the specific workflow or customer friction you are trying to solve.
2. Audit Your Existing Workflows: AI cannot fix a broken process. Ensure your knowledge management and operational steps are pristine before introducing automation.
3. Deploy the “Crawl” Strategy: Introduce AI into a single, tightly controlled segment of the customer journey where it adds the most value, and monitor it closely.
4. Preserve the Human in the Loop: Intentionally map out the customer journey to identify exactly where human empathy and complex problem-solving must take over from the AI.
5. Build Psychological Safety: Create a culture where remote agents feel safe reporting failures and system errors without fear of punishment.
6. Align to a Core Mission: Ensure every remote employee understands how their specific daily actions tie directly back to the overarching organizational purpose.
7. Strip Back Conflicting Metrics: Remove traditional contact center KPIs that force agents to rush interactions, allowing them the time required to resolve complex issues.
8. Develop AI Acumen in Leadership: Train your supervisors to understand AI capabilities so they can confidently evaluate tools and identify risks.
9. Practice Systemic Servant Leadership: Ensure the C-suite and middle management view their primary role as removing friction for the frontline workers.
10. Embrace the Power to Say ‘No’: Use your AI acumen and ROI requirements to push back against scattergun technology mandates from higher-ups.

Frequently Asked Questions

FAQ: What is the biggest risk of rapid AI deployment in contact centers?Answer: The primary risk is the “scattergun approach,” which leads to “AI slop.” When organizations rapidly deploy uncalibrated AI tools without understanding the value they drive, they often layer them over already broken workflows, leading to hallucinations, degraded customer experiences, and the fracturing of human culture.

FAQ: How can a fully remote contact center maintain high engagement scores?Answer: High engagement is sustained by connecting daily tasks to a vital mission, practicing servant leadership to remove egos, and establishing psychological safety so employees feel it is “OK to fail” and raise issues without fear.

SAQ: What should leaders be asking before they agree to implement a new AI tool?Answer: Leaders should ask: “Is our business currently set up in a way where this AI will actually add value, or are our workflows broken?”. They must also ask, “Where does the human need to remain in the loop within this specific customer journey?”. If you cannot clearly articulate the ROI and the human transition point, the tool should not be deployed.

SAQ: How do we prevent execution drift when integrating new technology?Answer: You prevent drift by utilizing a “crawl, walk, run” methodology. By embedding technology deeply and slowly into specific, well-managed parts of the workflow, you can monitor its impact and pull it back if it causes behavioral misalignment, rather than rushing a deployment that permanently alters your operational standards.

Citations and Research Statistics

• Q: What is the biggest risk of rapid AI deployment in contact centers?A: The primary risk is the “scattergun approach,” which leads to “AI slop” and fractures high-performing human systems. By deploying Culture-Calibrated AI through a governed “crawl, walk, run” methodology, you can rapidly eliminate unviable solutions and safely integrate technology without sacrificing your organizational culture to Execution Drift.
• Q: How can a fully remote contact center maintain high engagement scores?A: Remote operations often struggle with isolation and disjointed communication, which naturally leads to engagement decay. By shifting from traditional efficiency metrics to systemic servant leadership and embedding psychological safety into the daily workflow, leaders can prevent Supervisor Drift and push autonomy to the front lines, sustaining manager effectiveness scores well above the industry average.
• Q: How do we prevent new technology from ruining the customer experience?A: When new artificial intelligence tools are layered over broken workflows, they simply accelerate failure and frustrate both agents and customers. By establishing explicit Calibrated Human Oversight, contact centers ensure that complex, emotionally sensitive problem-solving remains with human supervisors, allowing the technology to resolve friction rather than creating it.
• Q: What should executives evaluate before approving a new AI tool?A: The common mistake is evaluating tools based solely on marketing hype and promised efficiency gains. A structural approach requires leaders to develop “AI acumen” to assess whether the technology actually solves a specific operational friction point. This systemic evaluation prevents Execution Blindness and identifies exactly where the human must remain in the loop to preserve service quality.