For years, the conversation around artificial intelligence (AI) in customer service has centered on what technology might eventually replace. But as AI becomes more capable of handling customer interactions, executing tasks, and making recommendations, a more important question is emerging for customer experience (CX) leaders:

What should people be doing when AI is doing more of the work?

It’s a question that reaches far beyond automation. It touches workforce planning, job design, employee development, compensation, organizational structure, and the future of customer service as a career.

And the urgency is growing. According to Gartner research, 85% of customer service and support leaders say they are expanding human agent responsibilities as AI reduces contact volume and shifts work toward higher-value tasks. At the same time, 80% report being under pressure to make workforce changes because of AI.

The workforce isn’t necessarily disappearing. It’s changing shape. And organizations that recognize this early have an opportunity to rethink what their people contribute and how they prepare them for what’s next.

The Shift From Handling Contacts to Solving Problems

AI is increasingly capable of managing the routine work that has traditionally occupied much of an agent’s day: authentication, information retrieval, order-status inquiries, appointment scheduling, summarization, and even more complex transactions.

As those responsibilities move to AI, human employees are likely to spend more time navigating exceptions, resolving emotionally charged situations, interpreting nuance, and making decisions that require context and judgment. That doesn’t make the human role less important. It changes where its value lies.

Ebrahim Hyder, Vice President of Customer Service at Michael Kors, sees this as an opportunity to elevate the human side of customer service. “One of the biggest misconceptions about AI is that it will replace the human element in customer service. In my view, AI actually elevates the importance of distinctly human skills,” Hyder explains.

Michael Kors has invested in AI through initiatives such as Mia, its virtual assistant, which handles routine, transactional interactions. But when a customer is dealing with a missed delivery tied to a special occasion, the interaction requires something different.

“Where humans become even more valuable is when emotion enters the conversation. Empathy, judgment, relationship-building, and the ability to interpret nuance are skills technology still struggles to replicate authentically,” Hyder added.

The distinction is important. Customers don’t necessarily want a person involved in every interaction. They want the right kind of support for the situation they’re facing. For CX leaders, that means moving beyond how many agents AI can replace and considering what employees should do once automation removes work that no longer requires a person.

The Next Generation of Agents May Look Very Different

As AI becomes more autonomous, customer service employees may increasingly find themselves managing outcomes rather than simply responding to individual inquiries. Consider an AI agent that can investigate a billing issue, retrieve information from multiple systems, recommend a resolution, and initiate a transaction. The human employee’s role may be to oversee that process, recognize when something isn’t right, and step in when the situation exceeds the system’s capabilities.

That requires a different combination of skills. AI literacy and data literacy will matter, but so will critical thinking, communication, problem-solving, and the ability to recognize when an automated recommendation shouldn’t be trusted.

Some organizations may introduce entirely new positions, including AI trainers, conversation designers, automation analysts, knowledge managers, and AI governance specialists. Others may find that existing roles evolve. Quality leaders may begin evaluating AI interactions alongside human ones. Workforce managers may oversee blended teams of people and AI agents. Training leaders may focus more on teaching employees how to collaborate with technology and exercise sound judgment.

There’s also an important consideration that can get overlooked: AI may eliminate certain tasks while creating new ones. Someone still needs to validate AI recommendations, correct mistakes, provide missing context, manage exceptions, and monitor performance. IBM’s 2026 research found that 80% of CHROs believe AI adoption creates this kind of “invisible” work.

Organizations will need to recognize these responsibilities, define them, and determine how they fit into the workforce of the future.

Are We Creating Better Career Opportunities or a Training Gap?

One of the biggest challenges in workforce reinvention may be preparing employees for jobs that don’t yet exist while preserving the opportunities they need to develop the skills those jobs will require. Traditionally, employees built expertise by handling routine interactions before progressing to more complicated situations. Repetition, exposure, mistakes, and coaching helped them develop the judgment needed to manage difficult customer scenarios.

But what happens when AI handles many of those foundational interactions? If new employees rarely encounter straightforward problems, how will they learn to recognize unusual ones? If AI diagnoses an issue, how will employees develop the ability to diagnose it themselves?

This creates a potential training paradox. Organizations want experienced employees with strong judgment, but automating the work that once helped people develop that judgment could make expertise harder to build. It also raises questions about career development and compensation.

In the CX Agent Insights: Perspectives from the Frontline report, only 47% of agents said their organizations offer clear career paths and advancement opportunities, even though 67% said they plan to stay and grow in the field.

If employees are expected to take on more complex responsibilities, manage AI-driven workflows, and protect increasingly important customer relationships, organizations will need to reconsider whether traditional job descriptions, compensation structures, and advancement opportunities still make sense. AI could make customer service careers more sophisticated and attractive. But that outcome will require intentional investment in mentoring, training, career pathways, and opportunities to practice the skills that technology cannot replace.

Workforce Reinvention Can’t Be Just an IT Initiative

Another important consideration is who owns the workforce transformation.

AI adoption often begins within technology, operations, or digital teams. But redesigning work requires input from human resources, CX leadership, and the broader organization. IBM’s 2026 CHRO research found that 46% of organizations don’t involve the CHRO when defining AI strategy. Only 26% clearly define work across human-led, AI-assisted, and AI-executed activities.

That suggests a disconnect between technology adoption and workforce planning. HR needs to be involved before organizations start eliminating responsibilities or restructuring teams. Decisions about which tasks belong to people and which belong to AI will influence job architecture, compensation, skills development, career progression, and organizational design.

Ultimately, AI workforce strategy should be a shared responsibility across CX, HR, technology, and executive leadership. The goal isn’t simply to prepare employees to use new tools. It’s to determine how the organization itself needs to change.

The Customer Still Needs a Human When It Matters

There’s one more perspective CX leaders cannot overlook: the customer. As consumers become more comfortable interacting with AI, their expectations around human support aren’t necessarily disappearing.

Gartner’s 2026 research found that 50% of customers say interactions are easier when companies use generative AI. Yet 87% say companies using generative AI for customer service must provide an option to reach a human agent. Those findings aren’t contradictory. They point to an important distinction: Customers are willing to let AI handle an interaction when it makes the experience easier. They become less willing when technology creates another obstacle between them and a resolution.

The same principle applies to employees. AI should remove unnecessary work, improve access to information, and give people more capacity to solve meaningful problems. It shouldn’t simply increase monitoring, reduce autonomy, or make employees accountable for decisions they cannot control.

As Hyder puts it: “I believe the future of customer service isn’t AI versus people. It’s AI creating space for people to do more meaningful work. The more AI removes repetitive tasks, the more our teams can focus on moments that build trust, loyalty, and emotional connection.”

The Bigger Question: What Are We Building Around AI?

AI adoption can create enormous capacity, but capacity alone doesn’t guarantee better customer experiences or stronger business results. What organizations do with that capacity will ultimately determine the value of their investment. Will they simply reduce headcount? Handle more customer volume? Give employees more time to resolve complex issues? Create new career opportunities? Or pursue some combination of all four?

The answers will differ across organizations, but one thing is becoming clear: Automating work and reinventing the workforce are two very different challenges. CX leaders need to understand which activities should be automated, which should be AI-assisted, and which should remain human-led. They also need to rethink how employees are trained, evaluated, compensated, and prepared to take on greater responsibility.

Perhaps the simplest question to ask is this: If you turned off your AI tomorrow, would you know exactly what your people are uniquely responsible for? If the answer isn’t clear, your organization may have adopted technology faster than it has redesigned the work around it.

Explore the full article in our October issue of CX Insight magazine for a deeper look at how AI is reshaping the customer service workforce, including the evolving role of human agents, emerging skills and career paths, compensation considerations, and the organizational changes CX leaders need to start planning for.

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But another question is worth asking: What is the experience like for the employees responsible for delivering it?

As customer expectations rise and artificial intelligence (AI) reshapes frontline work, CX teams face mounting pressure to improve efficiency, control costs, and maintain service quality. Employees must navigate complex systems, manage emotionally charged conversations, and adapt to constant change while continuing to deliver empathetic customer care.

For CX leaders, protecting employee well-being is becoming essential to building a sustainable customer experience.

Why Employee Well-Being Matters to CX Performance

The emotional demands of customer-facing work are easy to overlook. Employees may spend their days resolving problems they did not create, managing frustrated customers, and meeting demanding performance targets. Managers face their own pressures, balancing business expectations with employee support and organizational change.

When these demands become unsustainable, the consequences can extend beyond employee engagement and retention to the quality of the customer experience itself.

The challenge is not simply helping employees become more resilient. Leaders must also examine whether workloads, unclear priorities, disconnected systems, or constant organizational changes are creating unnecessary friction.

As Erin Flowers, Director of Customer Experience at Nama, explains in the full article, change fatigue often shows up as confusion, declining participation, and repeated questions rather than direct complaints. Recognizing these signals gives leaders an opportunity to address problems before they affect employees and customers.

Psychological Safety is a Leadership Priority

Psychological safety allows employees to raise concerns, acknowledge mistakes, ask for help, and challenge assumptions without fear of unfair repercussions.

In a CX operation, that can make a meaningful difference. Employees who feel safe speaking up can identify broken processes before they create customer problems. Managers can raise capacity concerns before burnout leads to attrition. Teams can learn from mistakes instead of hiding them.

Creating this environment does not mean lowering standards or eliminating accountability. It means pairing clear expectations with consistent support, honest communication, and opportunities to improve.

It also requires leaders to look beyond individual coping strategies. Wellness resources have value, but they cannot compensate for an operating model that routinely leaves employees overwhelmed.

Navigating AI Transformation With People in Mind

AI adds another dimension to employee well-being. While automation can eliminate repetitive tasks and create opportunities for more meaningful work, it can also introduce uncertainty about job security, changing responsibilities, and the skills employees will need.

CX leaders can build trust by communicating honestly about what AI will change, explaining how roles may evolve, and investing in training and development.

Managers play a particularly important role. They translate organizational decisions into everyday employee experiences, determine how concerns are handled, and help teams navigate uncertainty while maintaining performance.

Senior leaders must support those managers, too. Trusted peer relationships, coaching, and opportunities for candid conversations can help CX executives manage leadership’s emotional demands.

Creating Better Experiences Starts With People

Exceptional customer experiences depend on more than technology, processes, and performance metrics. They also depend on whether employees have the clarity, tools, support, and psychological safety needed to do their jobs well.

For CX leaders, the goal is not to eliminate every challenge. The goal is to create an environment where people can meet high expectations without hiding when they need help.

Read the full article, The Human Side of CX Leadership: Taking Care of the People Behind the Experience, in our October issue of CX Insight magazine for deeper insights, research, and practical perspectives from CX leaders at Nama, Intuit, and American Airlines.

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AI is reshaping how work gets done. Customer expectations keep climbing. Teams responsible for great experiences are being asked to adapt again, often with fewer resources and little certainty about what comes next. This issue, themed The Power of Convergence, explores what happens when people, technology, and leadership come together to shape the future of CX, and what it takes to make that convergence work in practice.

Here’s what’s inside.

The Human Side of CX Leadership

Our featured story turns the lens inward: what kind of experience are we creating for the people we ask to create experiences for customers? Drawing on research from the U.S. Surgeon General, NAMI, the APA, and Google, it explores psychological safety, mental health stigma, and why a meditation app can’t fix an operating model that routinely overloads people. Leaders from Nama, Intuit, and American Airlines share how they hold high standards while still giving their teams room to be human.

Is AI Adoption Reinventing the Workforce?

The question is no longer how many agents AI can replace. It’s what people should do once AI takes on work that no longer needs a person. This feature examines the agent as orchestrator, the skills that come next, the compensation question few organizations are discussing, and the training paradox: if AI handles the easy cases, how will tomorrow’s experts build judgment?

What Does Great Leadership Look Like When Everything Keeps Changing?

With more than 73% of organizations are near, at, or beyond change saturation, this piece argues that great leadership isn’t about moving faster. It’s about deciding what is worth moving forward. Learn how leaders balance agility with stability, build decision-making their teams can use without them, and find the courage to say “not yet.”

Brand Spotlight: The Ritz-Carlton Yacht Collection

Tracy Sedlak, Vice President, Global Sales Operations & Performance, at The Ritz-Carlton Yacht Collection, shares how the brand built its Customer Intelligence Center to make advisors more perceptive, not just faster. One finding stands out: in analyzed calls where guests mentioned a special occasion, advisors missed the opportunity nearly 40% of the time. Her challenge to every CX leader is worth a read.

When Your Customer Sends an AI Agent in Their Place

Personal AI agents can now dispute charges, rebook flights, and wait on hold for 40 minutes without complaint. Cresta CEO Ping Wu outlines what that means for demand forecasting, security, and liability, and how to decide whether to block, gate, or embrace agent traffic.

KIA Spotlight: 3Rivers Federal Credit Union

Chief Member Experience Officer Peter McMahon shows how 3Rivers turns more than 100 employee ideas a year into tested improvements, pilots them in an Innovation Branch, and rolls them out across all 24 locations, keeping human connection at the center of every AI decision.

The Customer Journey Is More Than a Single Conversation

Customers rarely accomplish anything meaningful in one interaction. Sierra explores how long-horizon AI agents retain context and keep working toward outcomes over days or months, with examples from Redfin, Rocket Mortgage, CarMax, and Guild, where customers who start with Rocket Mortgage’s AI assistant close at three times the rate of those who don’t.

Read the Full Issue

The future of CX will be shaped by the technology we adopt, but also by the judgment we exercise and the people we bring along. This issue is packed with research, frameworks, and candid perspectives from CX leaders who are navigating these choices right now.

Read and download the October 2026 issue of CX Insight.

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For AMC Global Media, that experience is especially important because its audiences aren’t simply customers; they’re passionate fans with emotional connections to the stories, characters, and worlds they love.

In this Brand Spotlight, Nicholas Solomon, Vice President of Customer Service at AMC Global Media, shares how his team is combining AI, Voice of the Customer insights, and empathetic service to remove friction, strengthen loyalty, and keep customer support from getting in the way of the entertainment experience.

Removing friction at every moment that matters

In a crowded streaming market, simplicity and reliability are no longer differentiators; they’re expectations. Solomon says AMC Global Media focuses on making the experience work seamlessly across devices, platforms, and brands, without requiring customers to navigate complicated logins, entitlements, or support processes.

But seamless service isn’t just about efficiency. It’s also about empathy.

“When something goes wrong, a great customer experience is meeting customers where they are, resolving issues quickly, and making them feel heard,” Solomon explains.

That philosophy is particularly important when serving passionate fandoms. A billing question or technical issue may seem routine from an operational perspective, but for a viewer deeply invested in a show, even a small disruption can feel personal.

Using AI to remove friction, not the human touch

As AI continues to reshape customer service, AMC Global Media is taking an intentional approach. The goal isn’t to replace human agents, but to use technology where it can make the experience easier.

Automation and self-service can efficiently handle routine, high-volume needs, while agents remain available for situations that require judgment, empathy, or deeper problem-solving. Agent-assist technology also gives employees greater context, allowing them to focus on the interactions where human connection matters most.

That balance is already producing results. As AMC Global Media reduced friction across high-volume customer journeys, CSAT increased from 69% to 82%, while NPS doubled.

Turning customer service into a source of insight

For Solomon, the contact center has a role that extends far beyond issue resolution. It serves as both a safety net for customers and a feedback loop for the organization.

Customer interactions reveal where customers are struggling, where expectations aren’t being met, and which problems keep coming up. AMC Global Media uses those insights across product, engineering, marketing, and other teams to inform improvements and reduce repeat pain points.

The result is a more proactive approach to CX, one where customer service doesn’t simply respond to problems but helps prevent them.

Building loyalty by making customers feel heard

Ultimately, AMC Global Media’s approach comes down to a simple idea: great CX should protect the customer’s relationship with the content and the brand.

Technology can make service faster. Data can make it smarter. But empathy is what makes the experience meaningful.

As Solomon puts it, “Solving the immediate issue is expected. Building trust is the differentiator.”

For CX leaders, that’s a powerful reminder: operational excellence and memorable experiences don’t have to compete. When organizations invest in their people, use technology thoughtfully, and genuinely listen to customers, they can create experiences that do more than resolve issues; they build trust that keeps customers coming back.

Want to hear more from Nicholas on how AMC Global Media is turning customer service into a driver of trust and loyalty? Read the full Brand Spotlight in the latest issue of CX Insight magazine. 

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But there is a particular kind of conference experience that senior CX leaders tend to describe when you ask them what they are actually looking for. It’s not about the biggest audience or the longest speaker list. It’s about something harder to engineer: a conversation that changes how you think, a CX peer who has wrestled with the exact problem sitting on your desk right now, and relationships that are still paying dividends years later.

When is the last time you left a conference having learned something that actually changed how you work? When is the last time you met someone in a session who became a genuine thought partner, not just a LinkedIn connection? When is the last time a conference sent you home thinking differently about your job function?

That is what CRS is built around.

At CRS Scottsdale (September 30–October 2, 2026), the format is intentionally intimate, designed to foster real conversations, share knowledge, and build relationships that outlast the event itself.

Here’s what sets it apart from other CX conferences.

Leaders Learning from Leaders

At most conferences, you learn from a stage. At CRS, you learn from the person sitting across from you at dinner. The insights come from the CX executive who just cracked a problem you have been wrestling with for months, or the C-suite keynote speaker who is willing to share not just what is working, but what isn’t. There is a candor in the room that is rare because it is composed of people who have actually done the work.

“This is the only event where true CX leaders can learn from other leaders.”

— Ebrahim Hyder, Vice President of Customer Service, Michael Kors

That peer-to-peer dynamic changes everything about how knowledge moves through an event. You aren’t passively absorbing presentations. You are actively exchanging hard-won experience with the people who understand your challenges most deeply.

Intimate by Design

CRS is intentionally small. And that is the whole point. You are not navigating a convention center floor hoping to catch five minutes with someone meaningful. The smaller scale is a deliberate structural choice that shapes every aspect of the event, from the session format to the way the agenda is built, with dedicated connection time woven throughout.

Collaboration at scale is a contradiction in terms. Real collaboration, the kind that surfaces new ideas and shifts your thinking, requires enough space for a genuine conversation. CRS is built around that insight.

“One of the things I really love about these conferences is how intimate it is. The smaller environment allows for a lot more collaboration.” 

— Dima Cichi, Global Customer Success & Service Transformation Leader, Microsoft 

An Openness You Won’t Find Anywhere Else

Something happens when you put the right people in a room together. The attendees who come to CRS are not there to pitch or to perform. They are there because they genuinely care about the customer experience and want to get better at it, alongside others who share this. That shared purpose creates a culture of openness that is hard to manufacture and impossible to fake.

“What keeps me coming back year after year are the friendships you make and the people you trust.” 

— Lisa Oswald, Senior Vice President and Global Head of Member Services, Travelzoo

When the people in the room trust each other, conversations go deeper. Problems get examined honestly. Advice is given and received in good faith. That is the environment CRS creates and protects.

Relationships That Last Beyond the Event

A conference that leaves you with a stack of business cards is forgettable. A conference that leaves you with a network of genuine partners is something else entirely. Attendees describe the connections they have made at CRS as those that have made them better leaders, strategists, and people. Relationships that did not end when the event did.

“I have developed relationships from coming here over many, many years that transcend work. They’re my partners. And I think that’s very unique in the conference space.There’s no other community like that in the industry.”

— Dave Pitsch, Vice President of Guest Services, Arc’teryx

That word, community, is what separates CRS from everything else. An event happens once a year. A community is always there.

Come Experience CRS for Yourself

We are at a complex moment in customer experience, trying to figure out how to harness AI while doubling down on the human connection that still defines great brands. The tension between those two imperatives is real, and the organizations navigating it best are the ones learning together in rooms like the ones CRS creates.

There is no better place to work through that challenge than alongside the leaders doing it in real time. If you have not been to CRS before, this is the year to find out what everyone keeps coming back for.

Learn More  

Register Today 

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But as artificial intelligence (AI) continues to evolve, the conversation is shifting. The question is no longer just how organizations can use data to personalize experiences; it is how they can use technology to better understand customers and support the people who deliver those experiences.

How can AI help organizations move from knowing customer preferences to understanding the motivations behind them? And how can companies use AI in a way that enhances the human connections at the center of exceptional service?

A Luxury Hospitality Perspective on AI-Powered Service

In luxury hospitality, where every detail and personal connection matters, this opportunity takes on even greater importance. The challenge is not simply applying technology to make interactions faster or more efficient. It is exploring how AI can help teams create experiences that feel thoughtful, personal, and considered.

That is the conversation Tracy Sedlak, Director, Contact Center Operations & Analytics at The Ritz-Carlton Yacht Collection, will explore during her keynote at CRS Scottsdale.

In today’s AI discussions, much of the focus centers on automation, efficiency, and cost reduction. The Ritz-Carlton Yacht Collection is approaching AI through a customer-first lens, exploring how the technology can help uncover richer insights, recognize individual preferences, and support employees in delivering more personalized experiences.

During her keynote, Tracy will share how her team is using AI to better understand guest personas, identify motivations and expectations earlier in the customer journey, and equip advisors with the intelligence needed to deliver the anticipatory service that defines The Ritz-Carlton Yacht Collection.

As organizations across industries continue evaluating how AI fits into their CX strategies, the conversation around meaningful implementation becomes increasingly important. Technology alone does not create exceptional experiences. The value comes from how organizations apply intelligence to better understand the people they serve and empower employees with the information they need.

What opportunities could emerge if organizations had a deeper understanding of customer expectations before each interaction begins? How can CX leaders balance the possibilities of AI with the importance of thoughtful, human-centered service?

If your organization is exploring what’s next for AI in CX, this keynote will offer a compelling perspective on where the conversation is headed.

Join us at CRS Scottsdale, September 30–October 2, to hear Tracy share how The Ritz-Carlton Yacht Collection is reimagining CX through anticipatory service.

Learn more, explore the full agenda, and register today.

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Jyotsna Khandekar sits at the center of that work. As a Director of Product Management, she leads the customer-facing digital platforms and AI initiatives that serve millions of users, including Cisco Community and the systems that surface the right insights to the right customers at the right time. Over 17 years in technology, spanning go-to-market, partner commerce, and now customer experience, she’s built a rare, end-to-end view of how product, revenue, and customer relationships all connect.

We sat down with Jyotsna to talk about where AI is genuinely improving customer experience, what it actually takes to build trust in AI systems, and why she believes the next real competitive edge isn’t your product or your data; it’s how fast your organization can turn customer understanding into action.

Execs In The Know (EITK): AI is transforming customer experiences across industries. What opportunities excite you most, and where do you see organizations getting it wrong?

Jyotsna: What excites me most is the shift AI makes possible in customer experience — moving from reactive to proactive, predictive, and personalized. For most of our support history, we waited for a customer to hit a wall and come to us. AI lets us flip that: anticipate what a customer needs and meet them with the right help at the right moment, sometimes before they’ve even had to ask. That’s a fundamentally better experience, and we’re only at the beginning of it.

Where organizations get it wrong is in starting with technology rather than the customer. There’s a lot of pressure right now to “have an AI story,” which pushes teams to adopt AI first and then hunt for a problem to attach it to. The ones who get it right do the reverse; they start with a real customer problem and ask whether AI is genuinely the best way to solve it. The other trap is optimizing for internal efficiency at the customer’s expense, measuring success by what the company saves rather than the value the customer actually gains.

EITK: Trust has become a critical topic in the age of AI. What does “trustworthy AI” mean to you, and how should organizations build trust with customers while adopting new technologies?

Jyotsna: To me, trustworthy AI comes down to three things: visibility, governance, and safety.

Visibility means you can observe which model handled a request and what data and actions were involved, audit the decisions afterward, and explain the output with clear reasoning and sources. If you can’t see what the system did and why, you can’t trust it.

Governance means real human oversight, with clear conditions for when a person can step in and when they should.

And safety means guardrails: monitoring for abnormal behavior, setting stop conditions, and hardening against attacks. When you can account for all three, and put that visibility in the customer’s hands, the AI earns trust.

Working at Cisco shapes how I see this: trust in the AI era depends on the full stack working together — the network that carries it, the security that protects it, and the observability that lets you see what’s actually happening end-to-end. That’s how you build trust with customers, too: by showing them the system is observable, governed, and safe, not just telling them.

EITK: What’s one AI myth you’d like to debunk?

Jyotsna: One myth I’d debunk is that keeping a human in the loop is a weakness, a sign your AI isn’t good enough yet. I see it the opposite way: it’s a sign of maturity, because it means you understand the stakes. Autonomy without boundaries isn’t innovation, it’s risk.

The goal isn’t to remove people as fast as possible; it’s to know exactly where human judgment matters most and design for it.

EITK: What’s one CX metric you pay closest attention to?

Jyotsna: The one I watch closest is adoption depth — how much of what a customer already owns they’re actually using. I care about it because it’s a leading indicator, not a lagging one: a renewal tells you what has already happened, while adoption depth tells you, months ahead, whether a customer is getting value and is likely to stay. It’s also what my team directly works to move — sending customers the right insights through the right channels about what they’re using and what they’re not yet using, so we’re actively closing that gap. If someone’s using only a fraction of what they’ve invested in, that’s a signal to act now. And if they’re deeply adopted, satisfaction and renewal tend to take care of themselves.

EITK: What technology trend are people underestimating right now?

Jyotsna: This one isn’t about a specific model or chip; it’s about where competitive advantage actually comes from now.

For a long time, the moat was your product or your data. But AI has changed that: product ideas can be copied and rebuilt faster than ever, and data alone is everywhere. So in my view, the real moat now is context, and what I’d call contextual velocity. Context is how deeply you understand your users; contextual velocity is how fast that understanding flows through your organization so you can act on it and turn it into relevant experiences for customers. When anyone can copy the product, what differentiates you is the context you hold and how quickly you can put it to work. People are only starting to realize this, but it’s becoming the real differentiator.

This is the first installment of 5 Questions With, a new blog series in which we sit down with CX leaders from different brands to hear how they’re thinking about customer experience today. Keep an eye out for the next conversation.

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That gap between what the data says and what customers actually feel is the defining challenge for customer experience (CX) leaders right now. And it is exactly what keynote speaker Julie Weingardt, Chief Operations Officer at Turo, is bringing to the mainstage at CRS Scottsdale.

There is a quiet crisis happening inside organizations that, by every measurable standard, appear to be doing everything right. Operational benchmarks are met, and satisfaction scores hold steady. And yet trust, the thing that actually drives repeat business and long-term loyalty, is eroding in ways the traditional dashboard was never built to detect.

Weingardt has a name for this problem: dashboard blindness. It is what happens when organizations confuse hitting their numbers with understanding their customers. When the metrics are green, but the friction is real, the disconnect does not stay invisible for long. It shows up in social feeds, in churn, and eventually, in revenue.

The Signal in the Silence

One of the most important insights Weingardt will unpack is what unrated interactions reveal. An interaction that goes unscored is not a neutral data point. It is a gap, and those gaps have consequences that quietly compound over time.

As automation becomes a larger part of the customer journey, the moments where customers disengage without providing feedback deserve far more attention than most organizations give them. The absence of a response is itself a response.

The Pressure Every CX Leader Feels Right Now

There is no avoiding the conversation about artificial intelligence (AI). The pressure to reduce costs through automation is real, it is coming from the top, and it is not going away. But Weingardt will challenge CX leaders to think carefully about what gets lost when the pendulum swings too far.

Human empathy, speed in the right context, and the ability to read nuance are not luxuries. They are operational assets with a measurable impact on customer trust. The question is not whether to adopt AI. The question is how to evaluate the trade-offs honestly, using frameworks that account for what a cost-savings analysis alone will never show you.

This is the cost-trust paradox, and navigating it well is quickly becoming one of the most important skills a CX leader can develop.

From Satisfaction to Advocacy

The session is ultimately a call to rethink the entire leadership model around customer loyalty. Satisfaction, as a goal, is reactive by nature. You wait for the interaction to happen, measure how it went, and adjust. Advocacy requires something different: a proactive, systematic approach to how organizations listen, what they measure, and how they scale the kind of experiences that build loyalty over time.

That shift is harder than it sounds, especially inside organizations that have spent years optimizing for the metrics they know how to measure. But it is the work that separates companies’ customers return to from companies customers tolerate.

Why This Conversation Matters Now

The timing could not be more relevant. As AI capabilities expand and budget pressures intensify, the temptation to optimize for efficiency at the expense of connection has never been stronger. Weingardt brings a practitioner’s perspective to a conversation the industry needs to have with honesty and urgency.

Whether you lead CX for retail, a financial institution, healthcare, or anywhere in between, the dynamics she is describing are not unique to Turo. They are the defining tensions of the moment.

Hear Weingardt’s full keynote at CRS Scottsdale. Learn more and register to attend.

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These shifts were at the center of our recent Outsourcing Briefing, held on May 7, 2026, at Microsoft Headquarters in Redmond. The one-day executive gathering brought together CX leaders for candid conversations about the realities of outsourcing in an AI-driven world, from workforce transformation and operational governance to trust, performance, and the evolving role of strategic partnerships.

Here are some of the biggest themes and takeaways that emerged throughout the day.

Turnover isn’t just a BPO problem; it’s a shared cost

Nearly every leader in the room is wrestling with attrition and has started building it into the contract.

One approach: instead of chasing a raw turnover number, track time to proficiency: how long it actually takes an agent to become fully productive on your specific product, and tie incentives to retaining people past that point. For complex products, that number can be well over a year. Once a partner’s team clears that threshold, they gain access to higher-volume or growth opportunities during peak season. It reframes retention as a shared investment rather than a penalty clause.

Another leader described a simpler version: rather than tracking 10 KPIs, pick 2 or 3 that actually matter, and cap how much a partner’s top-performing quartile can shrink in a given month. Fewer metrics, tighter guardrails, and less noise.

The consensus: if turnover isn’t written into your service level agreements (SLAs) yet, it probably should be because even when a partner backfills a seat for free, you’re still paying for it in longer handle times and lost institutional knowledge.

Some companies are quietly rethinking the phone call

One of the more candid moments came from a leader whose team eliminated voice support almost entirely, pushing customers to a self-service portal to reduce inefficient back-and-forth. It worked until it didn’t. For a subset of high-value customers doing complex annual transactions, the lack of a phone option became a genuine trust problem, and the team is now building a more targeted (and possibly paid) phone experience back in.

The lesson wasn’t “don’t cut voice” or “always keep voice”; it was that channel strategy needs to be segmented by customer, not applied as a blanket policy.

Onshore vs. offshore

More than one attendee pushed back hard on the old mental model of “our team” versus “the BPO.” Their approach: every location, including domestic work-from-home teams, gets a site code and is managed to the same standard. No special treatment for the U.S. team, no lower bar for an offshore site. Leaders who’ve made this shift report that it kills the “us vs. them” dynamic that quietly undermines many outsourcing relationships, and in some cases, offshore teams have gone on to outperform the domestic team once expectations are equalized.

Transparency reinforced this. Several leaders described sharing performance data openly across partners by letting one BPO see how another is performing on the same account as a surprisingly effective way to build trust and drive improvement, rather than a competitive risk.

Vetting a partner properly

This was maybe the most tactical, immediately useful advice of the day: when you visit a potential BPO site, don’t just talk to leadership. Ask to speak with frontline agents without their managers present.

The same skepticism applies to the numbers behind the business. A few leaders said they’ve started looping in finance and audit teams to vet a partner’s financial health directly, not just data security, because a BPO that looks great in a pitch deck can still be late paying its own vendors. With consolidation picking up across the outsourcing industry, that diligence is becoming more important, not less.

Regional consideration is getting more nuanced

Geography came up constantly, but not as a straightforward cost conversation, more as a question of fit. The Philippines remains a major hub and was described as a safe, proven choice for a reason, but several leaders pushed back on treating it as a default. A few flagged longer ramp times for complex, less-scripted products, and there was real debate about whether the market’s famously warm, accommodating service style is always the right match. Some customer bases respond better to a more direct, no-frills tone, and that mismatch can show up in satisfaction scores in ways that are easy to miss if you’re only looking at cost and language proficiency.

The most notable shift was geographic curiosity: multiple leaders are actively expanding into or exploring Morocco, Nigeria, Kenya, Ethiopia, and South Africa, citing strong English proficiency and labor quality alongside open questions about political stability and operational risk that the group agreed are worth investigating firsthand. Nobody in the room described these markets as fully proven yet; the tone was less “we’ve cracked it” and more “we’re piloting carefully and comparing notes with peers who are doing the same,” which is exactly the kind of ground-truth intelligence that’s hard to get anywhere except a room like this one.

Underneath both points was a broader shift in how leaders are evaluating location altogether: less “where is labor cheapest” and more “where can we find the right combination of skill, tone, stability, and scalability for this specific line of business.” A single global outsourcing strategy is giving way to a more deliberately blended footprint, matched to the complexity and sensitivity of the work being handled.

Outcome-based pricing has momentum

There’s a real appetite for moving away from pure productive-hour pricing toward outcome- or value-based models. But leaders running businesses with many product lines and transaction types described the practical challenge honestly: it’s hard to set fair, meaningful targets when your business has dozens of different call types, each with its own effort and value profile.

Nobody in the room claimed to have fully solved this, but the direction of travel was clear.

AI is the backdrop to every one of these conversations

AI didn’t dominate the discussion, but it ran underneath all of it as the thing that will keep pulling the “mundane, repetitive” work out of outsourced teams over time, and as a source of new tension (agents optimizing for first-contact resolution sometimes over-extend calls trying to preempt every possible follow-up question).

Those in attendance don’t think outsourcing is going away because of AI. If anything, the room’s read was the opposite: outsourcing is likely to grow as a strategic lever over the next few years, not shrink, with AI reshaping what gets outsourced rather than whether it does.

As customer expectations, AI capabilities, and outsourcing strategies continue to evolve, ongoing peer dialogue has never been more valuable.

Want in on the next conversation?

Keep an eye on our leadership events page and join us at an upcoming Outsourcing Briefing in Spring 2027 to connect with fellow CX leaders, exchange practical insights, and explore the strategies shaping the future of customer experience outsourcing. Whether you’re reevaluating existing partnerships or building your next-generation operating model, these discussions are designed to help you lead with greater confidence and clarity.

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Not burying the disclosure or softening it with a vague persona name and hoping no one asks. Actually telling customers upfront that they’re talking to an AI and giving them an immediate way out if they’d prefer a human.

The result, according to practitioners who attended our latest Virtual Executive Roundtable who’ve deployed this at scale? The vast majority of customers stay and engage.

In an era of debate about whether AI can match human service quality, organizations that lead with full transparency find that only a small fraction of customers opt out. And those who stay report customer satisfaction (CSAT) scores that, while not yet at parity with human agents, are closing the gap fast. Some deployments are seeing AI-handled interactions score 93% compared to 98% for humans.

What Actually Frustrates Customers

Most organizations approach AI deployment with a reasonable-sounding concern: if we tell customers they’re talking to a bot, they’ll disengage, they’ll demand a human, or they’ll leave frustrated. This instinct is understandable.

A Gartner survey found that 61% of consumers want the ability to toggle AI interactions on or off, reinforcing that customers don’t reject AI; they just want agency over it.

What actually frustrates customers isn’t AI; it’s deception. It’s filling out a form, expecting a live agent, only to discover mid-conversation that you’ve been talking to a bot the whole time. It’s being transferred without context, left waiting, or handed off to a human who has no idea what was already discussed.

Transparency short-circuits all of that. When customers know from the start what they’re dealing with, and know they can leave if they want to, they calibrate their expectations accordingly. And when the AI delivers, they’re satisfied.

What Transparency Looks Like

In practice, the organizations seeing these results aren’t just slapping a disclaimer at the bottom of a chat window.

They’re doing a few things deliberately:

• A named AI persona. Not “our virtual assistant,” an actual character with a name that sets clear expectations. This gives customers something concrete to interact with, rather than an ambiguous blob of automation.
• An immediate opt-out. From the very first message, without a maze of options or having to express frustration to trigger a transfer. Just a clear path to a human, available at any point.
• Continuity through handoff. When a customer does choose to transfer, the human agent receives the full conversation history. Nothing is repeated, nothing is lost. The handoff feels seamless rather than punitive.

Salesforce’s 7th edition State of the Connected Customer report, surveying 16,500+ individuals, found that trust in businesses to use AI ethically dropped from 58% in 2023 to just 42% in 2024, a 16-point decline in a single year.

From the same Salesforce report: 89% of customers say it’s important to know when they’re communicating with AI rather than a human, yet most brands still don’t consistently disclose it.

The low opt-out rates practitioners are seeing aren’t a sign that customers are trapped. They’re a sign that the experience is good enough that customers don’t feel the need to leave.

Some Interactions Shouldn’t Be Handled by AI

These findings challenge something deeper than an operational assumption. They challenge a C-suite narrative that has framed AI deployment as an inherently delicate act of customer management, to be introduced gradually, carefully disguised, and constantly hedged.

That framing has it backward. Customers are not fragile or universally hostile to AI. What they are is perceptive. They know when they’re being misled, feel the friction when a bot pretends to be something it isn’t, and they reward honesty with engagement.

There’s also an important exception worth noting: some interactions should never be handled by AI, full stop. Pet loss. Genuine financial hardship. Emotional escalations. These are human moments, and the organizations getting this right have been explicit about drawing that line. Transparency isn’t just about telling customers what they’re talking to; it’s about knowing, as an organization, where your AI should never go.

Are You Solving for the Wrong Problem?

If your organization is still in the pilot phase, debating how visible to make your AI deployment and nervous about customer backlash, the data suggests you may be solving the wrong problem. The question isn’t how to introduce AI without customers noticing. The question is how to build an AI experience good enough that customers don’t mind.

Transparency is the foundation of that. Not because it’s the right thing to do (though it is), but because it’s what works. It sets accurate expectations, builds trust, and creates the conditions under which customers will give your AI a fair chance — and, as practitioners are finding, most of them will decide it earns one.

The brands that will lead in AI-powered CX over the next few years won’t be the ones that hid their AI the longest. They’ll be the ones who trusted their customers enough to be honest and built something worth being honest about.

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.

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