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.

The post What We Learned About CX Outsourcing at Microsoft HQ appeared first on Execs In The Know.

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.

Join our mailing list to receive event invites.

The post Why Transparency is a Good AI CX Strategy appeared first on Execs In The Know.

Across industries, CX leaders are now facing a familiar tension: strong momentum in adoption, uneven results in execution. AI is embedded in more contact center workflows than ever before, yet achieving consistent, enterprise-wide impact remains difficult. The technology is advancing faster than most operating models can absorb it.

According to our 2026 CX Leaders Trends & Insights: Corporate Edition Report, two-thirds of contact centers now operate with some form of AI in their workflows, more than double the rate in 2022. But only 7% of CX leaders describe themselves as very effectively meeting their AI objectives. Nearly half say they are only somewhat effective.

That gap tells its own story. This is a question of translation, moving from isolated use cases to reliable, repeatable performance inside complex service environments.

Turning AI into Operational Impact

The reality is that AI in CX is no longer a pilot conversation. It is an operational one. And in operational terms, success depends less on what the technology can do in theory and more on how it behaves under real-world constraints: legacy systems, fragmented data, shifting customer expectations, and frontline teams who must integrate new tools without losing service quality.

The same research underscores the tension:

• 67% of contact centers now use AI (up from 31% in 2022)
• 49% cite customer frustration with AI quality as a growing concern
• AI virtual assistants still resolve only ~60% of interactions, compared with 87% for phone-based service

These are not signs that AI is failing. They are signals that scale is harder than adoption. What separates progress from stagnation is rarely the model or platform itself. It is the clarity of the use case, the discipline of implementation, and the willingness to confront what happens after deployment when customers begin to interact with the system in unpredictable ways.

In many organizations, early AI wins are real but isolated. A reduction in handle time here, a deflection improvement there, or a successful pilot that performs well under controlled conditions. The challenge emerges when leaders try to extend those results across channels, geographies, and volumes without losing performance and customer trust.

That is where the conversation is shifting now: from “what can AI do?” to “what does it take to make it reliable and scalable?”

From AI Possibility to AI Proof

This is precisely the value of examining AI through structured use cases, not as abstract innovation stories, but as operational decisions. What problem was being solved? What trade-offs were made in design? What changed in the workflow? And what happened when the system met real customer behavior?

Our upcoming event, From Investment to Impact: Rapid-Fire AI Use Cases for Customer Experience, is built around that premise. It brings together real implementations from across CX environments, each grounded in a defined business challenge, a specific execution approach, and measurable outcomes.

Facilitated by Chad McDaniel, President of Execs In The Know, the format is intentionally direct. Solution providers present concrete use cases, and CX leaders respond in real time with questions grounded in their own operational realities: what works, where it works, and why.

For leaders navigating AI strategy today, the value is not in another overview of what is possible. It is in seeing what is already working under real constraints, and understanding what it actually takes to replicate it.

Join us and learn how leading organizations are applying AI in real CX environments, the challenges they’ve encountered, and the results they’re achieving.

This session is exclusively for end-user corporate CX leaders responsible for customer experience strategy, operations, and technology decisions.

If you are a vendor interested in participating as a solution provider, please contact Scott Moberly at Scott@execsintheknow.com.

The post What AI Use Cases Are Really Delivering in CX Today appeared first on Execs In The Know.

A new research report from Execs In The Know, CX Agent Insights: Perspectives from the Front Line, changes that. Based on a 33-question survey of 107 contact center agents across internal and outsourced environments, it delivers something rare: an unfiltered, data-driven look at what agents actually experience, what motivates them, and what’s holding them back.

A Workforce That Genuinely Wants to Succeed

Here’s the good news: your agents care. A lot.

An overwhelming 88% of agents surveyed report being passionate about the brands they represent, and 82% say they’re satisfied in their roles. Nearly 9 in 10 believe their organization is committed to putting the customer first. This isn’t a disengaged workforce waiting for the clock to run out; it’s a motivated group of professionals who want to do meaningful work and do it well.

In fact, 67% of agents say they plan to stay and grow within the contact center industry in the long term. That’s a workforce with real tenure potential, and a real appetite for investment. So if agents are engaged and aligned, what’s the problem?

Tools, systems, and technology that simply aren’t keeping up with job demands.

Your Agents Want Faster, More Reliable Tools

When agents were asked what area of their contact center operation most needed improvement, technology ranked first, cited by 24% of respondents. Only 40% say they’re very satisfied with the technology they use day-to-day. Just 50% report that their systems integrate well and work seamlessly together. And when asked what single technology improvement would make the biggest difference in their work, the answer wasn’t AI or fancy new features; it was faster, more reliable tools, named by 54% of respondents.

The picture that emerges is of a capable, committed workforce operating with one hand tied behind its back. Agent performance isn’t capped by motivation; it’s capped by the operational environment around them.

The Hidden Risk: Career Clarity

There’s another gap that the research surfaces that deserves attention. While 67% of agents plan to grow in the field, only 47% feel their organization provides clear career paths and advancement opportunities. For a workforce that’s experienced (45% have five or more years in the role), that disconnect is a retention risk hiding in plain sight.

Agents are willing to commit. Organizations need to show they’re willing to invest in return.

What This Means for CX Leaders

The research is clear on one thing: improving CX outcomes starts with improving the agent experience. Not through perks or culture programs alone, but through faster systems, better integration, clearer career frameworks, and feedback loops that actually lead to visible change.

Ready to see the full picture? The complete CX Agent Insights: Perspectives from the Front Line report is packed with data, analysis, and actionable insights across hiring, satisfaction, technology, and operational strategy.

Read and Download the Full Report →

The post 107 Contact Center Agents Have Spoken — Are CX Leaders Listening? appeared first on Execs In The Know.

Consumers Still Favor Live Agents, but the Gap Is Closing

When consumers were asked to compare their interactions with live agents versus AI-powered agents, the preference for humans was clear: 68% rated live agent interactions as “Better” or “Much Better.” By contrast, only 53% said the same about AI-powered agents when compared to their human counterparts.

That’s a meaningful gap. But here’s what’s equally telling: 71% of consumers said they feel neutral or better about AI as their first point of contact when seeking customer care help. Consumer openness to AI isn’t just growing; it’s accelerating.

So what’s driving that tension between preference and openness? It comes down to expectations.

Performance Over Personality

One of the most striking findings in the research is what consumers actually want from AI. While live agents are expected to bring warmth, empathy, and a human touch, AI is held to a different standard entirely.

Consumers ranked “Being Highly Knowledgeable and Accurate” (14%) and “Being Efficient/Quick” (13%) as the top areas where AI-powered agents perform best. Empathy and fairness? Those lagged significantly behind.

The message is clear: consumers aren’t asking AI to act human. They’re asking it to work.

Complexity Changes Everything

Where consumers draw the line most sharply is around issue complexity. For simple tasks (paying a bill, updating account information), the preference split between live and AI agents is nearly even (52% vs. 48%). But when the issue gets complicated?

58% of consumers prefer a live agent for complex issues, and a striking 81% say access to a live agent is “Extremely Important” or “Somewhat Important” in those moments.

This isn’t just a preference; it’s a signal. When the stakes are higher, consumers want a human who can exercise judgment, show empathy, and navigate nuance. AI’s current capabilities in problem-solving simply haven’t earned that level of trust yet.

What Live Agents Need to Get Better At

The research doesn’t let live agents off the hook either. When consumers were asked which soft skills are most critical for human agents to provide excellent care, “Effective Problem-Solving” (16%) and “Being Highly Knowledgeable” (15%) topped the list.

Here’s the catch: those same skills ranked near the bottom when consumers were asked where live agents are currently performing best. That gap between expectation and reality is an opportunity, and a warning, for any brand investing in contact center training.

The Bigger Picture for CX Leaders

The research makes one thing unmistakably clear: the future of customer experience isn’t human or AI. It’s human and AI working together in ways deliberately designed around what consumers actually need at each stage of their journey.

AI excels at speed, availability, and accuracy. Live agents excel at judgment, empathy, and complex resolution. The organizations that figure out how to orchestrate these strengths (matching the right interaction type to the right resource at the right moment) will be the ones that win on customer experience.

The full report goes deep on soft skill differentials, consumer comfort with AI mimicking human qualities, the impact of language and accent barriers, and specific action items for CX leaders.

Download the Full Report →

The post What Consumers Really Think About Live vs. AI-Powered Agents appeared first on Execs In The Know.

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 

The post What Makes CRS Different from Other CX Conferences appeared first on Execs In The Know.

Uber decided to do something different.

The company’s Global Digital Experience team, the group sitting at the crossroads of customer support operations and engineering, started asking a harder question: what if you could infer how every single customer felt, even the ones who never filled out a form?

The answer became an artificial intelligence (AI) engine that analyzes the full universe of support interactions in real time, surfacing satisfaction signals that traditional surveys simply can’t see. No waiting for voluntary feedback, no sampling bias, and no blind spots.

The Three Measuring Levers 

The model is built around three pillars: Resolution, Effort, and Sentiment.

Resolution is the foundation. Did the customer’s problem actually get solved? Effort is the friction audit. How hard did the customer have to work to get there? And Sentiment is the hardest piece: tracking the emotional arc of an interaction from first message to final reply, measuring whether someone left feeling better or worse about the brand than when they arrived.

None of these is new in isolation. What’s new is the synthesis, such as weaving together transactional data, real-time trip telemetry, conversation logs, turn counts, and tone signals into a single, coherent picture of what a support experience actually felt like.

The Lessons Were Hard-Won

Building this wasn’t a clean sprint. Uber’s team quickly discovered that years of CSAT data had given them a false sense of understanding. Once they started peeling back layers to define more nuanced sub-metrics, they found complexity that legacy surveys had been quietly papering over all along.

Aligning stakeholders across different business lines, languages, and markets on one shared definition of “satisfaction” required iteration after iteration. Teaching an AI model not just that it failed, but why, within a specific cultural or operational context, turned out to be genuinely hard work.

It’s the kind of friction that only makes the output more valuable.

What’s Next for Digital Experience at Global Scale

The near-term unlock is significant: for the first time, Uber can compare performance across fundamentally different support technologies (legacy automation and modern conversational AI) using a normalized metric. Apples to oranges, finally made comparable.

But the longer-term vision is more ambitious. The team sees a future where AI doesn’t just measure satisfaction; it anticipates friction before customers feel it, resolves issues without a single click, and transforms every support interaction from a transaction into a trust-building moment.

That future isn’t fully here yet. But the infrastructure being built now is what makes it possible.

Want the full story?  Access the complete case study, including how Uber’s team structured the cross-functional build, what broke along the way, and how they see AI reshaping customer experience on a global scale.

The post What Happens When You Stop Waiting for Customer Feedback? appeared first on Execs In The Know.

But something else is happening at the same time, and it deserves equal attention: the interactions that reach human agents are becoming more complex, more emotionally charged, and more consequential than ever before.

That’s an opportunity. And the brands that recognize it are pulling ahead.

The Shift Nobody Is Talking About Loudly Enough

When AI handles the easy stuff, what’s left for human agents isn’t the leftovers; it’s the moments that define the brand. Service recovery. High-stakes exceptions. Customers who are frustrated, confused, or vulnerable. These are the interactions where trust is either deepened or permanently lost.

Research backs this up. According to Qualtrics, when a customer issue is resolved positively, that customer is likely to demonstrate greater loyalty over time than someone who never encountered a problem. This is the Service Recovery Paradox, and it only works when a human agent has the empathy, judgment, and autonomy to execute it.

Scripts don’t get you there. Rigid escalation paths don’t get you there. Empowered agents do.

The 18-Point Lesson from Southwest Airlines

At CRS Amelia Island, Kevin McDorman, VP of Customer Care at Southwest Airlines, made a point that reframed the entire conversation around CX transformation: the frontline isn’t where strategy gets executed; it is the strategy.

His argument wasn’t anti-technology. It was pro-human, with intention. As automation absorbs more transactional contacts, the human role must be elevated with equal deliberateness. That means moving from rigid scripts to guardrails that give agents room to exercise judgment. It means investing in soft skills (active listening, empathy, problem-solving) with the same rigor as any technology deployment.

Because customers don’t experience transformation through a roadmap. They experience it in the moment they need help.

What AI Can Genuinely Do for Your Agents

Here’s where it gets interesting: AI isn’t just replacing agent work; it’s also making agents better at their jobs. Simulation-based onboarding tools are helping new agents handle complex scenarios before they encounter them in real time. AI co-pilots are supporting agents in real time with knowledge retrieval, sentiment analysis, and next-best-action guidance. Auto-summarization is reducing after-call work so agents can focus on the customer in front of them.

The companies winning this transition aren’t choosing between AI and humans. They’re designing operating models where each does what it does best and where the intersection between them is intentional, not accidental.

Looking Ahead to 2030

The contact center of 2030 looks meaningfully different from today’s. Agent profiles will shift, and compensation structures will evolve. Hiring, onboarding, and career pathing will be redesigned around a new contact mix that demands higher emotional intelligence and sharper judgment.

The organizations that start building toward that now, investing in frontline empowerment as infrastructure, not afterthought, will have a structural advantage that’s hard to replicate later.

The question isn’t whether to automate. It’s whether you’re elevating your people at the same pace.

Read the full article in the April issue of CX Insight magazine →

The post Why Human Agents Are Your Most Important CX Asset appeared first on Execs In The Know.

The political headwinds around DEI have been loud, but the business signals are louder. According to our 2026 CX Leaders Trends & Insights: Corporate Edition report, 68% of consumers say it’s important for companies to take a public position on their DEI practices and allow that position to guide their operations. Yet only 36% of CX leaders say their company actually does this. That gap isn’t a branding problem. It’s a performance problem.

The Purchasing Power Behind the Principle

The consumers who care most about DEI aren’t a niche; they represent some of the fastest-growing pools of spending power in the country. Black buying power in the U.S. is projected to top $2 trillion in 2026. U.S. Latino purchasing power stands at $3.78 trillion. The LGBTQIA+ community represents an estimated $1.4 trillion domestically, and up to $4.7 trillion globally. Multicultural consumers now account for more than 65% of U.S. expenditure growth.

And they’re making purchase decisions accordingly. One-third of consumers say they’ve already cut back or stopped buying from brands that rolled back DEI commitments. Among Black and Latino consumers, that number jumps to 45%. Among LGBTQIA+ consumers, it reaches 58%.

The Contact Center

Corporate statements about inclusion don’t matter if the customer experience doesn’t reflect them. When CX leaders were asked how their company performs on accessibility and inclusion in customer support, 76% rated themselves “Very Good” or “Somewhat Good.” When consumers were asked the same question about those same brands, only 58% agreed.

That 18-point perception gap is a blind spot, and blind spots in CX show up in churn, negative reviews, and eroding loyalty over time.

The Companies Staying the Course

While some brands pulled back in 2024 and 2025, others held firm, and their results are worth noting. Costco’s board unanimously urged shareholders to reject an anti-DEI resolution in early 2025; shareholders agreed by a 98% margin. The company’s employee turnover rate is roughly 7%, well below the retail industry average of over 60%. That’s not a coincidence; it’s the return on a workforce that feels valued and a customer base that feels seen.

McKinsey research shows companies in the top quartile for leadership diversity are 39% more likely to outperform financially. Boston Consulting Group found that organizations with above-average diversity generate 19% higher innovation revenues. Harvard Business Review reports that diverse teams make better decisions 87% of the time.

The Window Is Open

This moment has created an opening. As some brands step back, others are signaling something unmistakable to the market: who they’re building for, and whether they can be trusted to hold that position when things get harder.

The brands that will emerge strongest aren’t the loudest; they’re the most consistent.

Want the full picture, including a practical roadmap for auditing your CX experience through an inclusion lens, connecting DEI to core KPIs, and building multicultural fluency into your service design?

Read the full article in the April issue of CX Insight magazine →

The post The Business Case for DEI appeared first on Execs In The Know.

Artificial intelligence (AI) is absorbing routine interactions at an unprecedented scale. Diversity, equity, and inclusion (DEI) commitments are being publicly tested. Frontline agents are navigating more complexity than ever before. And as customer expectations continue to rise, organizations are being forced to reckon with a more fundamental question, not just how to serve customers faster, but how to serve them better, more inclusively, and with the kind of human judgment and empathy that no technology can replicate at scale.

Our April issue of CX Insight magazine brings together research, practitioner perspectives, and real-world case studies to examine the forces reshaping CX leadership and how organizations can stay ahead of them.

The DEI Performance Gap Is Widening

The business case for inclusive customer experience has never been stronger, or more urgent. Yet a critical gap persists. CX leaders rate their own accessibility and inclusion efforts 18 points higher than consumers do. That disconnect does not resolve itself. It shows up in churn, in negative sentiment, and in the quiet erosion of loyalty over time. This article examines what closing that gap actually requires operationally, structurally, and strategically.

The Frontline is Not a Support Function

Kevin McDorman, Vice President of Customer Care at Southwest Airlines, made the case plainly at CRS Amelia Island: brands will not differentiate by how much they automate. They will differentiate by how well they equip their people for the moments automation cannot handle. The shift from rigid scripts to empowering guardrails is not a cultural preference; it is a strategic imperative. This article explores what that shift looks like in practice and why organizations that get it right will find it difficult to replicate.

Brand Spotlight: How Grubhub Maintains Service Reliability at Global Scale

Behind every seamless food delivery experience is an operational infrastructure most customers never see. In this issue’s Brand Spotlight, Tanisha Parker, Associate Director at Grubhub, pulls back the curtain on how one of the world’s most recognized food delivery platforms manages global BPO partnerships, workforce strategy, and service consistency across a vast and dynamic ecosystem of couriers, merchants, and diners. Her perspective on eliminating operational friction, without compromising customer value, is one of the most practically useful conversations on this issue.

Case Study: How Uber Is Closing the Customer Feedback Gap with AI

Traditional customer satisfaction surveys capture only a fraction of the experience. Uber decided that was not good enough. In this issue’s case study, Anindya Sundar Das, Senior Director and Head of Global Digital Experience at Uber, details how Uber’s Global Digital Experience team deployed an AI engine that infers customer satisfaction across every single support interaction. It was structured around three core metrics: Resolution, Effort, and Sentiment. The result is a real-time quality signal that enables proactive improvement at a global scale and fundamentally changes how Uber understands and responds to the experience it is delivering.

KIA Spotlight: Balancing AI and Human Connection at Carrier Enterprise

In a service environment where HVAC contractors rely on fast, accurate support to keep their businesses running, the balance between technology and human connection is not an abstract leadership question; it is an operational reality. Michael Luyster, Director of Customer Experience at Carrier Enterprise and a KIA Champion, shares how Carrier Enterprise has built a hybrid service model grounded in customer choice, operational consistency, and trust. His conviction that AI should augment human capability rather than replace it offers a model worth studying across industries.

The Growing Impact of Women in CX Leadership

CX is one of the most cross-functional, human-centered disciplines in business, and women are leading it with measurable impact. The feature on women in CX leadership examines why the pipeline still narrows too early, what structural barriers remain, and why advancing women into senior leadership roles is one of the most strategically sound decisions a CX organization can make. Contributing their perspectives to this important conversation are Lisa Oswald of Travelzoo, Maureen Barnett of Fanatics, Jessica Patel of Belk, and Dima Cichi of Microsoft: four leaders who are actively shaping what modern CX leadership looks like and what it can become.

When AI Improves Metrics but Not Outcomes

Organizations across industries are deploying AI to reduce costs and increase efficiency. By conventional measures, it appears to be working. Automation rates are rising, and handling times are falling. Containment continues to improve, yet retention remains flat. Customer experience remains inconsistent, and business outcomes remain unchanged.

Cortney Jonas Burnos, Vice President of AI & Digital at Transcom, offers a sharp diagnosis: the problem is not the technology. It is the misalignment between how customer experience is measured and where it actually creates value. As AI absorbs the most repeatable interactions, what remains for human agents is more complex, more consequential, and more emotionally demanding — and most organizations have not restructured around that reality.

The Trillion-Dollar Cost That Never Appears on the P&L

According to Qualtrics XM Institute, businesses worldwide risk losing $3.8 trillion annually due to poor customer experiences. More than half of negative interactions lead customers to reduce or stop their spending entirely. Yet this cost rarely surfaces on a standard profit and loss statement. It disappears into churn metrics, missing renewals, and referrals that were never made. This article from Procedureflow provides the framework CX leaders need to translate experience quality into financial risk and bring that conversation into the boardroom where it belongs.

The question this issue keeps returning to is this: what does it actually take to lead well in this moment?

The answer, across every article and every conversation, is the same. It begins with people. The organizations that understand this and build accordingly are the ones that will emerge from this period of disruption with something the competition will find very difficult to replicate: the trust of the people they serve.

Read and download the full April 2026 issue of CX Insight magazine.

The post Just Launched: The April Issue of CX Insight Magazine appeared first on Execs In The Know.