Proposed measures include requiring English proficiency, limiting certain types of foreign call handling, and allowing customers to request a U.S.-based agent, all of which signal a meaningful shift in how brands conduct their customer care operations. 

For customer experience (CX) leaders, this is not simply a regulatory development — it is a strategic inflection point. For decades, contact center models have been optimized around global delivery, balancing cost efficiency with scalability and coverage.

These proposals introduce a new compliance dynamic that could reshape how brands approach CX, potentially creating operational complexities for verticals subject to heavy regulation, including finance, healthcare, travel/hospitality, and other high-touch industries. Ultimately, this could become an opportunity to differentiate. Furthermore, if customers are given more control over where their support comes from, organizations may need to rethink their delivery models, potentially creating new, flexible approaches that might accommodate both preference and practicality.

This raises fundamental questions about cost structures, staffing strategies, and how brands define and deliver consistency across channels and regions. 

What CX Leaders Should Be Evaluating Right Now

As these conversations begin to take shape, CX leaders should consider engaging with their C-suite counterparts now. Understanding current exposure to offshore support, modeling the financial implications of increased onshoring, and evaluating the role of automation and artificial intelligence (AI) in facilitating necessary changes. In many ways, these proposals could accelerate trends already underway.

As labor constraints tighten and expectations rise, AI-powered self-service and agent-assist technologies may play an even more central role in maintaining efficiency while supporting a potentially more localized workforce. At the same time, organizations will need to carefully consider how they preserve experience quality, particularly as customer expectations around clarity, communication, and trust continue to evolve. Now is the time to analyze and understand both the go-forward plan and the eventual impact on customers. 

Transparency, Tradeoffs, and the Customer Experience

Communication with customers will also become a more strategic lever. If implemented, these proposals (particularly those related to consumer control over call routing) offer brands an opportunity to reframe parts of the service experience around choice and transparency, giving customers greater control over how they receive support. But that choice must be paired with clear expectations.

If requesting a U.S.-based agent introduces longer wait times or different service pathways, those tradeoffs will need to be communicated proactively and thoughtfully. Done proactively and well, this change could strengthen trust and reinforce a brand’s commitment to both service quality and customer assurance — an increasingly important differentiator in a landscape shaped by automation, AI, and heightened scrutiny around safety and security. Most leaders tasked with making these changes might benefit from getting ahead of the curve and engaging their counterparts and various stakeholders now. 

Preparing for 2027 Starts Now

Looking ahead to 2027, the organizations best positioned will be those that begin adapting (or planning steps to do so) now. This means evolving routing logic to account for customer preferences and regulatory requirements, reassessing workforce strategies to include more flexible domestic capacity, and strengthening quality assurance frameworks to align with emerging expectations around communication and performance.

Perhaps most importantly, it means shifting the mindset from reactive compliance to proactive design. These proposals are not just about where support happens … they are about how trust is built and maintained in every interaction. And in that sense, they may ultimately define the next chapter of customer experience. 

Look for more on this topic in the months to come, and practitioners can connect with peers in the Know It All (KIA) community to compare notes on getting ready for these imminent shifts. 

The post What CX Leaders Need to Know (and Do) as FCC Call Center Rules Advance appeared first on Execs In The Know.

Those things still matter. But they are no longer enough.

Today, customers are looking for something deeper from the brands they choose to do business with. They want confidence and clarity. They want to know that when something goes wrong, they will be supported by a brand that is competent, consistent, and worthy of their trust. In other words, they want assurance.

That is why Customer Assurance is such an important idea for CX leaders right now.

What Is Customer Assurance in Customer Experience?

Customer assurance is not just about making promises. It is about creating experiences that leave customers feeling informed, protected, respected, and certain they are in good hands. It is what happens when trust, empathy, operational excellence, and intelligent innovation come together in a way the customer can actually feel.

And in this moment, that matters more than ever.

Why Customer Assurance Matters More in Today’s CX Environment

Across industries, leaders are navigating enormous change. Artificial intelligence (AI) is rapidly reshaping the contact center, automation is taking on more routine tasks, and self-service has become the norm. Customers are moving faster, expecting more, and giving brands less room for error. At the same time, organizations are operating in an environment marked by cost pressure, shifting workforce expectations, economic uncertainty, and constant pressure to modernize.

That combination has created a new kind of challenge for CX teams. It is no longer enough to ask, “How do we make service faster?” The more important question is, “How do we make customers feel confident in this new experience?”

How AI Is Raising the Stakes for Customer Trust and Confidence

Because as AI becomes more visible across customer journeys, confidence becomes the differentiator. Customers may appreciate faster answers and 24/7 support, but speed alone does not build trust. If an AI agent gives incomplete information, if a handoff to a human feels disconnected, if policies are enforced without empathy, or if customers are left wondering who or what they are actually dealing with, trust begins to erode. And once trust slips, loyalty often follows.

This is where customer assurance becomes a leadership imperative. For CX leaders, assurance is about setting a higher standard for how experiences are designed and delivered. It means building operations that work responsibly, ensuring customers have clear information and support that feels grounded in both intelligence and care, and preparing teams to lead through change, not just react to it.

Why Customer Assurance Is a Competitive Advantage

For organizations, customer assurance is becoming a business advantage. In a market where products can be copied and prices can shift overnight, trust is one of the few differentiators that grows stronger over time. Brands that create confidence through every touchpoint are better positioned to retain customers, protect reputation, and grow long-term value.

For teams, assurance creates alignment. It gives frontline leaders, agents, technologists, and executives a clearer shared purpose. Not just to reduce handle time or to deploy new tools. But to deliver experiences that customers believe in. That is a much stronger rallying point, especially in a time when many teams are being asked to adapt quickly to new technologies and new expectations.

And for the industry, customer assurance may be one of the most important ideas shaping the road ahead.

CX is entering a period where the conversation is expanding beyond efficiency and into responsibility. Beyond implementation and into impact. And beyond what technology can do and into what experiences should feel like when they are done well. The brands that lead in this next chapter will not simply be the ones adopting AI the fastest. They will be the ones using it in ways that strengthen trust, empower employees, and create more confident customer relationships.

That is the opportunity in front of us.

Attend CRS Scottsdale, Sept. 30-Oct. 2, 2026

At CRS Scottsdale, this is the conversation we are bringing to the forefront. CX leaders will come together to explore what it really takes to build trust, confidence, and clarity in a new era of care. From AI and leadership to service strategy, customer expectations, and operational transformation, the focus is not just on what is changing, but on how leading organizations are responding with intention.

Want to learn more about what Customer Assurance looks like in practice? Visit the CRS Scottsdale website to learn more. 

The post Customer Assurance: The Strategy CX Leaders Can’t Afford to Ignore appeared first on Execs In The Know.

A customer encounters an issue, reaches out, and the business reacts. For years, success has been defined by how well that recovery happens: how quickly teams respond, how efficiently they resolve, and how satisfied the customer feels afterward.

But that model is starting to show its limits.

Not because companies don’t care about experience, but because customers increasingly expect something different. They don’t want fast recovery. They want the issue handled before it ever becomes their problem.

Across industries, CX leaders are rethinking what it means to deliver great service: shifting from reacting to anticipating, from resolving to preventing, and ultimately, from servicing customers to staying ahead of them.

The gap isn’t intention — it’s execution

There’s no shortage of ambition. Most organizations already recognize that proactive, anticipatory service is the goal. The challenge is turning that ambition into something operational.

What consistently gets in the way isn’t a lack of vision, but a breakdown between insight and action.

Data lives across disconnected systems, making it difficult to see the full customer journey in real time. In regulated industries, even when the signals are clear, compliance requirements can slow or limit how teams respond. And internally, ownership isn’t always defined — who decides when a signal is strong enough to act, and what action should follow?

The result is a familiar pattern: companies are getting better at identifying potential issues, but they still struggle to do something about them before the customer feels the impact.

This isn’t a strategy problem. It’s an execution gap.

What proactive CX actually looks like

When organizations successfully make the shift, it doesn’t come from trying to predict everything. It comes from identifying the moments that matter — where timely intervention can meaningfully change the outcome.

In practice, this means recognizing friction early and stepping in before the customer has to.

• A payment likely to fail is addressed before service is interrupted
• A delayed order is communicated before the customer checks on it.
• A drop in product usage triggers outreach before a cancellation decision is made.

But what makes these moments effective isn’t just the prediction — it’s the experience that follows.

Customers aren’t simply notified; they’re given clear, immediate paths to resolution. The interaction feels helpful, not intrusive. And most importantly, it removes effort instead of adding to it.

Over time, these interventions do more than reduce contact volume. They build trust, reinforce reliability, and shift the relationship from reactive support to something that feels intuitive, seamless, and aligned with customer needs.

Rethinking how success is measured

One of the more nuanced challenges in moving to proactive CX is measurement.

Most organizations are still wired to evaluate success based on what happens after something goes wrong. Metrics like handle time, speed to answer, and post-interaction satisfaction all assume that the interaction has already occurred.

But in a preventative model, the most meaningful outcome is often the absence of that interaction.

That requires a different way of thinking about success. Instead of asking how well an issue was resolved, teams begin to look at whether it was avoided altogether. Instead of focusing solely on efficiency, they start to connect proactive interventions to outcomes like retention, reduced churn risk, and long-term value.

It’s a subtle but important shift. The goal is no longer just to fix problems faster; it’s to design experiences where those problems don’t surface in the first place.

The role of AI (and the reality behind it)

AI is often positioned as the driver of anticipatory CX, but the reality is more grounded.

AI is most valuable when it helps teams make sense of signals at scale. It can surface patterns, highlight risk, and recommend actions that would be difficult to identify manually. But it doesn’t deliver the experience on its own.

What enables proactive CX is the combination of data, AI, and human execution. Data provides the signal, AI interprets it, and people (agents, operators, and CX teams) deliver the response in a way that builds trust.

Where organizations tend to struggle is not in deploying AI, but in operationalizing it. If teams don’t trust the output, they won’t act on it. If systems aren’t connected to execution, insights stay theoretical. The value only materializes when those signals are embedded directly into workflows and decisions.

What progress actually looks like

For organizations looking to move forward, progress tends to come from focus and practicality rather than sweeping transformation.

The most effective approach isn’t to build a fully predictive model across every touchpoint. It’s to start with a small number of high-impact scenarios where the path from signal to action is clear. Addressing something like payment failures, delivery disruptions, or early churn indicators can create immediate value and, just as importantly, build internal momentum.

From there, progress comes through iteration rather than perfection. Waiting for flawless data or fully unified systems often delays action indefinitely. Organizations that make meaningful gains are the ones willing to test, learn, and refine.

And throughout that process, the anchor remains the same: outcomes. The goal isn’t to implement new technology for its own sake, but to reduce avoidable contacts, improve retention, and create more seamless customer experiences.

From cost center to revenue driver

At VXI, this shift is central to how we think about the role of CX.

Proactive service isn’t just about efficiency or deflection. It’s about recognizing that every moment (whether it results in a customer interaction or not) has the potential to influence revenue.

When organizations combine AI-driven insight with human delivery, they move beyond support and into something more strategic. They prevent churn before it happens, identify opportunities to engage at the right time, and create experiences that feel consistent and effortless.

It’s a model built on both automation and expertise (what we often describe as “bots + brains”) where technology identifies the opportunity, and people ensure it’s delivered in a way that resonates.

Designing for what doesn’t happen

The organizations that stand out in modern CX aren’t defined by how quickly they recover. They’re defined by how often customers never need to reach out at all.

Anticipatory CX isn’t about predicting every possible outcome. It’s about consistently preventing the moments that matter most.

For organizations willing to rethink how experience is designed, measured, and delivered, that shift is already within reach.

Written by Lauren Kindzierski, Head of Strategy & Innovation, VXI

About VXI

VXI Global Solutions is a leading global BPO providing omnichannel customer service, CX, and digital solutions for top brands, with 40,000+ employees across 43 locations worldwide. For more information, visit www.vxi.com

The post Preventing Customer Recovery with Anticipatory CX appeared first on Execs In The Know.

At the Customer Response Summit in Amelia Island, I shared the stage with three other experts to understand their strategies for tying customer care excellence to revenue growth, reduced churn, and operational efficiency.

I was joined by Jen Joyce, Senior Vice President of Digital Customer Operations at Frontier Communications; Craig Barnes, Senior Vice President of Customer Care at Retail Store Operations at Williams-Sonoma; and Tanisha Parker, Associate Director at Grubhub.

The conversation centered on three pillars – each laid out here as a playbook to help you plan, measure, and communicate:

1. Reframing the contact center as a value creator
2. Securing executive and board buy-in
3. CX as a revenue system

From Cost Center to Value Creator

Execs In the Know members are in various stages of shifting the narrative around contact centers from cost center to value creator. The panel offered four recommendations:

• The first is that customer trust and growth is earned, not won. AI alone does not do that. AI + humans does. We agreed on the guiding principle: “Automate the noise, humanize the moments that matter.” AI is ideal for high volume, low emotion, and predictable interactions. Humans, however, have empathy and understanding when the stakes are higher – emotionally and financially. While automation removes noise, humans deliver the impact.
• Second, the contact center is the best source of customer insights. Because it sits at the real-time intersection of customer experience, behavior, and feedback, contact centers are uniquely able to identify what customers are thinking. By turning our rich data into actionable information, we can help organizations spot trends immediately and respond faster.
• Third, service excellence consistently correlates with higher Customer Loyalty. In practical terms, if a client reaches out for technical support, and we solve that quickly and effectively, chances increase that the customer will not churn and, instead, will become an advocate.
• This dovetails with the fourth key of modern CX: Revenue growth. We are on the front-lines of upsell, cross-sell, and repeat purchases. Our speed, efficiency, and effectiveness directly impact brand, product, and service resonance. The best growth strategies are centered on customer experience.

Securing executive and board buy-in

Securing executive buy-in for CX initiatives requires inspiring leadership to act. There are three levers to do this:

• Contact centers experience customer pains daily. Senior management will support transformation initiatives when you highlight that friction, communicate the urgency, and show them first-hand the broken workflows that the customer experience experts overcome in each interaction. This connects them emotionally to the problems we solve.
• Turning micro-pilots into macro wins. This means beginning with small experiments that reduce risk while proving ROI – important metrics for the C-suite. Having this support is required for larger-scale implementations.
• Aligning with executive priorities: This is an exercise in translation – framing CX in terms of revenue and risk. Often, it is effective to work collaboratively across functions to present a unified case to the executive team for how the recommendations will help the organization achieve its strategic goals, faster.

Driving action requires more than sharing anecdotes: Delivering quarterly evidence (grounded in data and storytelling) wins commitment and budget.

CX as a revenue system

We are confident that delivering on the points in this blog will make CX a revenue system in the next 12 months. Accomplishing this requires that CX leaders make three strategic bets:

1. Integrated intelligence and intent-led automation: The most successful contact centers design automation around customer goals rather than keywords, scripts, or rigid workflows. Applying an intent strategy combined by AI creates compounding value. This, in turn, requires data rigor: a) Unifying data from disparate data sources b) Consolidating customer data post-acquisition c) Having a unified, end-to-end view of the customer across systems and operations.

2. Structured experimentation and proof-based scaling: Begin with small pilots with clear KPIs backed with quarterly proof. Then, increase the scale. Specifically, around AI, this has been echoed at previous Execs In The Know events: Because AI aspirations are not meeting CX realities – and because most deployments still do not move beyond the pilot phase – it is important to focus on discrete use cases before expanding its scope.

3. Enhanced workforce and human-centered differentiation: Smarter customer experts outperform automation-only models. Leverage AI to make them more effective through real-time assistance, recommendation engines, and decision support. 

Final Thoughts

The panel concluded with a powerful reminder: “Experience isn’t a cost—it’s the multiplier that grows every part of the business.”  By reframing CX as a growth engine and aligning it with organizational priorities, leaders can secure the resources needed to elevate customer experience initiatives and drive long-term business value.

Guest post written by Mike Lytle, Chief Delivery Officer, Americas at TP

TP is a global leader in digital business services, which consistently seeks to blend the best of advanced technology with human empathy to deliver enhanced customer care that is simpler, faster, and safer. For more information, visit tp.com.

The post Proving CX’s Value in the Boardroom appeared first on Execs In The Know.

And across industries, that pressure is showing up in the same places: how to move faster without losing trust, how to create efficiency without eroding the experience, and how to separate what is genuinely transformative from what is simply new. Those were among the biggest undercurrents in this week’s Virtual Executive Roundtable, where leaders came together to talk candidly about what AI is changing within their organizations right now.

What made the conversation so valuable was not that anyone claimed to have it all figured out. It was that the discussion stayed grounded in the tension leaders are actually managing every day. What does agentic AI really mean in practice? Where is it delivering measurable value today? Where do human teams still matter most?

And perhaps most importantly, are organizations using AI to modernize the same old service model or to build something better from the ground up? The conversation made one thing clear: this moment is bigger than automation. It is a very real opportunity for CX leaders to rethink what great service looks like next.

What does “agentic” really mean?

One of the most useful parts of the conversation was the effort to separate true agentic AI from the catch-all language that’s flooding the market. Leaders repeatedly came back to one simple distinction: traditional AI reacts, while agentic AI acts. Traditional AI answers the question, and agentic AI helps complete the task. It is more conversational, more proactive, and better at taking action across systems than simply surfacing information.

That distinction matters because confusion is still slowing organizations down. Several leaders noted that many companies say they are building agentic capabilities when, in reality, they are still enhancing scripted bots. That disconnect is important. If leaders use the same word to describe radically different levels of maturity, it becomes harder to benchmark progress, align teams, and make smart investment decisions.

The industry is still early

A striking theme from the discussion was how low current adoption still is. Estimates in the room placed true agentic AI adoption somewhere below 15%, with some leaders putting it closer to 3%-5%. And yet nobody sounded relaxed about that. Quite the opposite. The tone was urgent. Leaders acknowledged that while the industry is still early, the pace of change is accelerating fast enough that waiting now could create a real competitive gap later.

That is the tension many organizations are sitting in right now. They know they do not have all the answers. They also know they do not have the luxury of standing still. If competitors have already spent the last two years learning, testing, failing, refining, and scaling, what happens to the organizations that are just beginning to ask foundational questions now?

Where leaders are seeing real value today

The conversation stayed grounded in practical use cases, and that was refreshing. Leaders discussed high-volume, repeatable work such as account updates, password resets, and status checks. They also discussed more advanced uses: proactive service interventions, automated quality auditing, and knowledge management that updates in near real time based on live interactions.

One example stood out: instead of simply telling a customer that an order is delayed, an agentic system can recognize that the customer paid for expedited shipping, predict the miss before the customer complains, and proactively issue a refund. That’s not just efficiency; that’s service with foresight.

Leaders also pushed back on a narrow definition of value. This is not only about removing cost or reducing headcount. The more mature conversation is about containment, speed, routing accuracy, reduced friction, better use of human expertise, and stronger experiences overall. In other words, if your scorecard for AI is only labor reduction, are you measuring the wrong thing?

The human-in-the-loop is a strategy

If there was one point the group returned to again and again, it was this: human oversight still matters, especially in emotionally charged moments. Leaders shared examples from industries where the issue is not a simple transaction but a life event, a safety concern, or a vulnerable moment. In those cases, the role of AI is not to replace empathy. It is to recognize when empathy is required and make the handoff smarter, faster, and more informed.

That raises an important leadership challenge. Are organizations training AI only on business rules? Or are they also teaching it context, tone, and the signals that should trigger human intervention? Because the risk is obvious: a system can be technically correct and emotionally disastrous. And in customer experience, that still counts as failure.

A few shared perspectives

• “The old AI is ‘what do you want to know?’ agentic AI is ‘what do you want to do?’”
• “Instead of AI being a helper, AI is now your accountable digital labor. It’s part of your workforce.”
• “Standard AI was reactive… agentic AI is more proactive in how we solve for the customer.”
• “Traditional AI is scripted responses. Agentic AI can go out, pull from multiple sources, and make decisions.”
• “The AI would say your order is confirmed. Agentic AI will predict it won’t arrive on time and refund the expedited shipping in real time.”
• “It’s moving from supervised learning to autonomous decision-making.”
• “Agentic AI isn’t just answering questions; it’s completing the transaction end-to-end.”

This is bigger than automation

The biggest takeaway from the discussion was not that AI is moving quickly. Leaders already know that. It is the organizations making the most meaningful progress who are asking sharper questions as they move. They are not just chasing use cases. They are thinking carefully about trust, orchestration, customer expectations, employee impact, and where human connection still matters most. That is the real work in front of CX leaders now; not simply adopting AI, but shaping how it shows up in the experience in a way that is thoughtful, responsible, and genuinely useful.

What should AI handle? What should stay human? Where can we remove friction? Where should we add reassurance? And how do we use this moment not just to do service cheaper, but to do it better?

These are exactly the kinds of candid, leader-level conversations happening inside our Virtual Executive Roundtables. If you want to hear how your peers are thinking through the opportunities and tradeoffs ahead, and contribute your own perspective to the discussion, join us at a future Virtual Executive Roundtable. It is a chance to step into a smaller, high-value conversation with fellow CX leaders navigating many of the same questions in real time.

Join our mailing list to receive event invites.

The post The New CX Question: What Should AI Own? appeared first on Execs In The Know.

Performance metrics may look stable — service levels met, occupancy steady, costs controlled — yet something feels structurally off.

AI pilots launch but stall. Digital volumes increase, but accountability blurs. Customer expectations rise faster than internal capability.

For decades, the traditional contact center operating model delivered exactly what it was designed to deliver: efficiency, predictability, and cost control.

It worked — until it didn’t.

Customers began carrying expectations from every interaction they have — across industries, across platforms — into every new experience. The standard is no longer set by direct competitors. It is set by the most seamless interaction they had yesterday.

Today’s CX environment is structurally different. Customers move fluidly across channels. AI is embedded into workflows. Regulatory scrutiny has intensified. Data from every interaction is strategically valuable.

Yet many organizations are still operating on a structure built for queue management — not experience orchestration.

The issue isn’t effort.

It’s architecture.

Traditional contact center operating models were engineered for a different era.

And that architecture is beginning to fracture under modern CX demands.

The Model We Built — and Why It Worked

For years, the contact center was optimized around a clear set of assumptions:

• Voice was the dominant channel
• Demand patterns were forecastable
• Workforce management drove precision
• Performance was measured by speed and cost
• Technology cycles were relatively stable

It made sense for an environment defined by concentrated voice demand, slower technology cycles, and clearer functional boundaries.

It was structured. It was disciplined. It delivered measurable efficiency.

But it was built around queues, not journeys. That distinction now matters.

The Emerging CX Operating Model

The future operating model will require evolving tools. AI will advance, automation will expand, and digital ecosystems will grow more complex. But technology alone will not determine success.

The differentiator will be how organizations redesign accountability, governance, and workforce structure to integrate those capabilities. Structural alignment will determine whether those investments create lasting value.

If structural alignment is the differentiator, redesign cannot be abstract. It requires deliberate structural shifts.

Across industries, four are becoming clear:

1. Unified Experience Ownership
2. Embedded AI Governance
3. Workforce Redesign — Not Just Upskilling
4. Real-Time Data Integration

Together, these shifts represent more than incremental improvement. They signal a structural redesign of how CX organizations must operate to compete.

The Bottom Line

Traditional contact center structures are not flawed. They were optimized for a less complex era.

They worked — until they didn’t.

The question now is not whether the model was effective. It is whether it still fits.

The future of CX will not be won by those who install better tools.

It will be won by those who redesign how the organization works.

Guest blog post written by John Sorenson

The Execs In The Know Expert Network

Want to connect with Nick or learn more about his expertise? You can do that through the Execs In The Know Expert Network, a curated group of trusted CX professionals, each selected for their proven leadership and deep subject matter expertise across key areas of the customer experience discipline.

Access to the Expert Network is available exclusively to Know It All (KIA) members. Not a member yet? Join the free KIA community today and start tapping into CX expertise you can trust.

About John

The post Evolving CX Operating Model: Why Traditional Contact Center Structures Are Breaking Down appeared first on Execs In The Know.

Let me be honest with you: I’ve been to enough industry conferences to know when a room is just going through the motions. At CRS 2026 in Amelia Island, something was different.

When I stepped on stage to lead “When AI Acts: Leading Through the Shift from Copilot to Agent,” I wasn’t there to talk about tools or trends, or which model is in market right now. I was there to have the harder conversation; the one about whether our organizations are actually ready for what’s coming.

Because here’s the reality: AI isn’t waiting for us to be ready. It’s already acting.

“By 2028, agentic AI is expected to handle 68% of customer experience interactions with technology partners.” — Cisco Global Research, 2025 (7,950 decision-makers across 30 countries)

→ Source: Cisco Newsroom, May 2025

Sarah Jeanneault presenting at CRS 2026, Amelia Island

The Question That Shifted the Room

I opened with a simple question: “When AI starts acting on behalf of your team – who is accountable?”

You could feel it land. Not because it’s new, but because most of us haven’t answered it yet. And the gap between how fast AI is advancing and how prepared our operations are to support it? That’s the gap I’ve been thinking about every single day.

As long as AI is a chatbot or a copilot, humans are the final decision-makers. The moment AI becomes agentic – resolving transactions, routing cases, applying policy logic without waiting for someone to click approve, the responsibility structure changes entirely. AI becomes embedded in your operations, and your operations had better be ready to hold it.

“93% of IT leaders report intentions to deploy autonomous AI agents within two years, and nearly half have already started.” — MuleSoft 2025 Connectivity Benchmark Report (1,050 IT leaders surveyed)

→ Source: MuleSoft / Salesforce Connectivity Benchmark Report, 2025

From Suggesting to Executing

Here’s the progression I walked through, and it’s one that most organizations are living in real time right now:

Stage 1 – AI as Responder: Chatbots that react to prompts, deflect tickets, answer straightforward questions. Reactive. Limited.

Stage 2 – AI as Assistant: Copilots that sit alongside your agents, surfacing information and suggesting next steps. Humans still make the call.

Stage 3 – AI as Actor: Agentic systems that execute. They process requests, make decisions within defined parameters, and move work across systems — independently.

Most organizations I talk to are managing all three simultaneously. And that third stage? That’s not just a technical upgrade. It’s a change in risk, accountability, and operational design.

“23% of organizations are already scaling AI agents — yet operational governance remains the primary barrier to broader deployment.” — McKinsey State of AI, 2025 (1,993 respondents across 105 countries)

→ Source: McKinsey State of AI Report, November 2025

The Foundation Beneath the Intelligence

This is where the conversation really shifted. Because we quickly moved past “is your AI smart enough?” to ask a much harder question: is the foundation beneath your AI structured enough?

Most organizations still rely on document-based knowledge: policies written in long-form PDFs, procedures scattered across shared drives, tribal knowledge living in the heads of your most experienced team members. For years, that’s been fine because humans compensate for ambiguity. We fill in the gaps, ask clarifying questions, escalate when we’re not sure.

AI doesn’t do that. AI executes based on the structure it’s given. If your knowledge is fragmented, outdated, or unclear, those weaknesses don’t disappear when AI touches them. They get amplified.

Attendees engage in the Care Gap exercise

Naming the Care Gap

Midway through the session, we stopped theorizing and got practical. I put people into small groups and gave them three questions:

1. Where does customer care break in your organization?
2. What is the measurable business impact?
3. Why does that gap exist structurally?

Each group had to distill their answers into a single Care Gap Statement: the symptom, the impact, and the root cause.

What struck me was how fast people could do it. They didn’t have to think hard about where things break. Inconsistent responses driving repeat contacts. Escalations triggered by unclear decision thresholds. Copilot suggestions overridden because agents don’t trust the logic underneath them. Extended handle times because knowledge lives in four different places and no one can find what they need fast enough.

These aren’t new problems. What changed was the framing. We stopped calling them performance issues and started calling them what they actually are: structural gaps.

“Service reps spend 66% of their time on non-customer-facing tasks. AI implementation is directly tied to reducing that friction — but only when the underlying knowledge is structured.” — Salesforce AI Agent Research, 2024

→ Source: Salesforce AI Agents Statistics, 2024

Turning Breakdowns Into Opportunities

Once you name the gap, you can reframe it. I asked every group to complete this sentence:

“If we improved ___, we could achieve ___, without compromising customer care.”

The most compelling responses weren’t about acquiring better AI. They were about designing better systems. Improving decision logic clarity to reduce override rates. Centralizing and version-controlling workflows to lower escalations. Clarifying exception paths to improve first-call resolution. The emphasis wasn’t the tool; it was the architecture underneath the tool.

A Real-World Example of Structural Change

I shared a story from a large health insurance contact center that illustrates exactly what I mean. Agents were handling complex benefit and claims inquiries, and escalation rates were high. Leadership assumed it was a training problem.

It wasn’t. The knowledge existed. It was just structured in a way that nobody could use confidently under pressure. Policies lived across documents. Decision paths weren’t mapped. So, agents defaulted to escalation not because they didn’t know the answer, but because they couldn’t find it fast enough to trust it.

The organization rebuilt its processes into clear, visual workflows with defined decision logic and governance controls. The policies didn’t change. The structure did. Escalations dropped significantly. First-call resolution improved.

The transformation wasn’t technological. It was architectural.

The Maturity Journey

Toward the end of the session, I mapped out the maturity journey that resonated most with the room:

Documented: Information exists but remains static and interpretive. You’re dependent on SMEs to fill the gaps.

Guided: Processes are structured step-by-step. People can follow them without context.

Collaborative: Governance and version control are formalized. Knowledge is owned, not assumed.

Strategic: Knowledge is connected to analytics and continuous improvement.

Innovative: AI acts autonomously within defined guardrails. This is where the magic happens but only if the earlier stages are solid.

The sequence matters. I see organizations every week trying to leap directly to “Innovative” because of competitive pressure or boardroom enthusiasm. But automating ambiguity doesn’t eliminate it, it multiplies it. Scaling inconsistency doesn’t fix it, it accelerates it. Delegating judgment to AI without defining the rules introduces risk, not efficiency.

“Gartner predicts agentic AI will autonomously resolve 80% of common customer service issues without human intervention by 2029 — a 30% reduction in operational costs.” — Gartner, March 2025

→ Source: Gartner Press Release, March 5, 2025

What the Room Carried with Them

As we wrapped, conversations kept going at the tables. Leaders were asking each other: Who currently owns knowledge updates in your organization? Is your decision logic formally documented or just assumed? If AI executed tomorrow based entirely on how your systems are structured today, would you feel confident?

That last question is the one I want to leave you with too. Not because the answer is supposed to be “yes” right now most of us aren’t there yet. But because the question itself is the leadership shift this moment demands.

The Real Takeaway

AI will keep advancing. Its role in customer experience will keep expanding. The differentiator won’t be who adopts it first.

It will be who builds the strongest operational clarity beneath it.

When AI suggests, humans can adjust. When AI acts, structure determines trust.

That’s the shift. And it extends far beyond technology.

By Sarah Jeanneault, VP of Marketing, Procedureflow

About the Author

Sarah Jeanneault is VP of Marketing at Procedureflow, where she leads growth strategy and customer-centric programs. With 20+ years of experience across startups and enterprises, she focuses on the intersection of operational clarity and AI-readiness in customer experience. She spoke at Customer Response Summit 2026 in Amelia Island.

The post When AI Starts Acting appeared first on Execs In The Know.

More specifically: Who are you when the title drops, the metrics fade, and the pressure hits? Because, as Travis reminded the room, leading people is complicated. And in a world where every conversation seems to orbit around AI, automation, and scale, the differentiator that will define the next era of customer experience isn’t just technology; it’s emotional intelligence (EQ).

And EQ, he argued, sits on a deeper foundation: identity. Who you are determines what you do. This became the heartbeat of his keynote, “The Standard Is the Strategy.”

Metrics Matter. But They Aren’t the Whole Story.

Travis began with a story from his NFL days, specifically, a moment with legendary linebacker Willie McGinest. After a tough game, Willie posed a question that stuck with him long after he left the field: “Who are you?”

Too often in CX (and in life), Travis said, we obsess about the tangible:

• NPS
• Quarterly numbers
• Service levels
• Efficiency metrics

But in leadership, you can hit the metric and miss the moment. You can meet the standard but violate the principle.

This line landed hard. Because it’s true: in the rush to deliver, leaders can unintentionally drift from the values that made them leaders in the first place.

Standards vs. Principles: The Core Distinction

Travis broke it down simply:

• Standards are what we do.
• Principles are who we are.

Standards matter. They’re measurable, operational, and necessary. But standards alone don’t create culture. Principles do. And in an industry where AI is accelerating faster than any of us expected, Travis reminded leaders of something vital: AI will scale your systems. EQ will sustain your culture. Because CX, at its core, is still about people.

EQ is the skill that helps leaders manage themselves, navigate environments, read the room, and steward their teams through uncertainty. But EQ is built on something deeper: identity. Before you can lead others, you must define who you are going to be.

The Three Principles of Principles

The centerpiece of the keynote came when Travis outlined the three rules that govern how real principles work.

External Conditions Shouldn’t Determine Your Principles

If your principles only hold when conditions are ideal, they’re not principles; they’re preferences.

Travis told stories from NFL training camp, from tough seasons, from moments when every condition felt like a good reason to justify exceptions. But that’s exactly the point: conditions expose principles; they don’t rewrite them.

He challenged leaders to examine whether pressure or convenience has ever swayed their standards, from tone to honesty to accountability.

His reminder hit home: Pressure doesn’t create character. It reveals it.

And this wasn’t just for the boardroom. He drew the line straight into the personal: marriage, parenting, and home life.

Principles Shouldn’t Be Compartmentalized

Leaders don’t get one set of principles for the office and another for home. Character doesn’t clock in and out. Travis spoke about something many leaders quietly wrestle with: the disconnect between the “stage version” of themselves and the “real version” at home. Those gaps erode trust more than any missed KPI ever could.

Authenticity, he said, isn’t about saying whatever you want. It’s about alignment. The version of you in the boardroom, at the dinner table, behind closed doors, and in moments no one sees, should be the same person. And he asked a provocative question: What if authenticity became your most important standard?

Don’t Expect from Others What You Don’t Model Yourself

This one is leadership in its purest form. You cannot expect your team to live at a level you refuse to model. From effort to attitude to integrity, Travis shared: Teams may listen to what you say, but they will replicate what you model.

He reflected on parenting, on coaching, on how often leaders get frustrated with behaviors they actively or passively teach through their example. It was a moment of self-reflection for many in the room. Before you ask, “Why won’t my team rise higher?” Ask: “Have I?”

The Danger of Success in the Wrong Direction

One of the most powerful moments came near the end: a story about scoring what he thought was a touchdown only to realize he ran toward the wrong end zone.
The metaphor was striking. Because in CX, in leadership, and in life, you can hit every target, grow revenue, improve metrics, and still be moving in the wrong direction.

The only success that matters is the kind that aligns with your principles. External success ≠ principled success.

Why This Keynote Mattered

At a conference full of strategy, innovation, AI discussions, and operational breakthroughs, Travis did something different. He grounded the week in something unmistakably human. CX leaders today sit at the intersection of exponential technology and deeply human expectations. We’re balancing automation with empathy, speed with care, efficiency with trust. AI is rewriting the rules, but it’s not rewriting our values.

Travis reminded leaders that before you can build a modern, high-performing, AI-enabled customer experience, you must anchor your identity. Because your principles, not your models, not your workflows, not your dashboards, will determine whether your culture thrives or fractures in the years ahead.

He ended where he began, returning to Willie McGinest’s question: Who are you? And is that the person you really want to be?

Because the future of CX is not just AI-powered; it is principle-powered. And as Travis said, the standard is the strategy.

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As consumer use of AI-powered and self-help solutions continues to expand, CX leaders are increasingly focused on resolution, abandonment, and measurable ROI rather than containment alone. Although digital and AI-powered channels continue to grow, phone-based support still dominates a massive portion of contact volume, and many brands still struggle to deliver seamless experiences across blended journeys. The research suggests that the next phase of CX leadership will be defined not by how much automation exists, but by how intelligently it is governed and how seamlessly channels work together.

“AI is no longer experimental — it’s operational,” said Susan McDaniel, Co-Founder and COO of Execs In The Know. “But what this research makes clear is that adoption alone isn’t enough. The brands that succeed will be those that simplify journeys and ensure automation complements — rather than replaces — live-assisted support.”

Some of the most notable findings from this new research include:

• AI adoption within the contact center has more than doubled since 2022, with 67% of organizations now using AI, and another 24% planning to do so soon.
• Consumers are increasingly navigating multichannel journeys, yet only 11% of CX leaders feel their organization delivers a seamless experience.
• Self-help and AI-powered resolution are scaling, with 35% of brands now resolving 20–60% of total volume through self-help, up from just 13% in 2024.

The 2026 CX Leaders Trends & Insights: Corporate Edition report, along with the entire Execs In The Know CX research library, including past Consumer and Corporate Editions, is accessible on the CX Research portion of the Execs In The Know website.

About Execs In The Know  

Execs In The Know brings together customer experience (CX) leaders from across industries in an effort to advance the conversation and set a new agenda for delivering amazing experiences for consumers. As a global community of the brightest minds in CX, Execs In The Know provides opportunities to learn, share, network, and engage to innovate. Operating under the motto, “Leaders Learning From Leaders,” Execs In The Know facilitates many opportunities for community engagement, such as its bi-annual national Customer Response Summit and private, online community, Know It All “KIA.” There are also exclusive, laser-focused engagements like industry briefings and executive roundtables. Execs In The Know also guides and informs the industry with a rich tapestry of CX-related content that includes CX Insight magazine, industry research, webinars, blogs, and much more. For more information, visit Execs In The Know’s website.

The post New CX Research from Execs In The Know Reveals Growing Need for Channel Parity as AI Adoption Accelerates Across the Contact Center appeared first on Execs In The Know.

This question was front and center in the presentation by Meghan Nicholas, Walmart’s Vice President of Customer Engagement Services, at the recent Execs In The Know CRS East Conference. You can watch a preview of her presentation here. At TP, we see this not as a challenge, but as our guiding principle.

We share Meghan’s vision —a people-led, tech-powered future for customer support. This approach recognizes that technology like AI and automation are powerful enablers. They help us operate at scale, remove friction, and deliver faster service. But technology alone is not the answer. The real difference is made by people. When we empower our experts with the right tools and insights, they can provide the empathy, care, and expertise that turn a good interaction into a great one.

In this post, inspired by the insights shared in Amelia Island, we will share the keys to delivering this balanced and resilient customer experience model at scale – shown through our work with a client that needed to transform its CX model. This example provides a model for designing modern service operations that strengthen both empathy and efficiency, use technology to enhance the moments that matter most, and build a foundation of trust that brings you closer to the people you serve.

The client faced a common but significant challenge: their existing customer service model couldn’t keep up with rising expectations. They needed to improve first-contact resolution, boost customer satisfaction, and create a more streamlined, positive experience from end to end. The goal was to not just solve issues but to build lasting trust and loyalty.

Recognizing the need for a fundamental shift, they partnered with TP to co-create a new service model. This collaboration moved beyond a traditional client-vendor relationship into a true strategic alliance focused on shared goals and continuous improvement.

The first step was building a dedicated team of TP experts. These weren’t just general customer service agents; they were specialists who received intensive training tailored to the client’s unique needs. This specialized knowledge empowered them to handle complex inquiries with confidence and accuracy, providing customers with reliable answers on the very first call.

Creating this highly skilled team significantly increased first-contact resolution. Customers no longer had to endure frustrating transfers or repeated calls. Instead, they connected with an expert who could own their issue and see it through to completion.

With a strong foundation of human expertise in place, the next phase was to integrate innovative technology to enhance, not replace, the human element. This included a suite of advanced tools designed to streamline processes and empower the customer experts.

One of the most impactful solutions was a “digital assistant” that provided real-time guidance during customer interactions. This tool offered instant access to knowledge bases, suggested next steps, and ensured compliance with all necessary procedures. By automating the search for information, it freed the experts to focus entirely on the customer—listening with empathy, understanding their emotional state, and providing personalized solutions.

This combination of specialized human talent and smart technology delivered remarkable results. The new model not only met but exceeded expectations, achieving a significant boost in customer satisfaction scores. The client saw firsthand that efficiency and empathy are not mutually exclusive; they are two sides of the same coin.

The success of this partnership demonstrates a clear path forward for any organization looking to elevate its customer experience. It starts with a commitment to understanding customer needs on a deeper level and investing in the people and technology required to meet them.

By building specialized teams, integrating smart digital tools, and fostering a culture of continuous improvement, companies can transform their customer service into a powerful engine for growth and loyalty. This approach doesn’t just solve immediate problems; it builds relationships that last, turning satisfied customers into passionate advocates for the brand.

As Meghan mentioned, the future of customer experience is one where innovation serves humanity, and every interaction is an opportunity to create a meaningful connection.

by Mike Lytle, Chief Delivery Officer, TP

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