Contact centers have long sought to balance providing loyalty-and-revenue-building excellent customer experiences (CXs) with the costs of supplying them, and with this, supplying superb agent experiences (AXs) to enable CXs.
But in today’s iffy economy, amidst rising expenses, government policy changes, and with the ever-growing demand for stronger returns from shareholders and stakeholders, this has become a highwire act: with a flimsy net below.
Add to this the push by the C-suite to adopt AI to improve results, the stakes--and the risks--couldn’t be higher.
To help contact centers carefully move forward, without losing their grip and steps, we reached out to several supplier experts for their guidance.
Our panelists are:
- Raj Balasundaram, Global Vice President, AI Innovations, Verint
- Manisha Powar, Head of Product, Customer Experience Suite, Qualtrics
- Carmit DiAndrea, Director, AI Data Management, NiCE
- Eric Williamson, CMO, CallMiner
Q. What changes: developments, issues, and trends in the CX that you have heard from contact centers over the past 12 months that will likely continue into the next 12 months? What are their drivers?
Raj Balasundaram:
One of the biggest trends that will likely continue is the push for results-driven AI implementations. Deployments focused on AI experiments are falling behind those that are focused on outcomes. This is pushing organizations to reevaluate their AI strategies, with many abandoning solutions that don’t deliver scalable results.
Customer expectations are [also] rising, with 64% of young adults (18-34-year-olds) in Verint’s “The State of Customer Experience 2025” research saying their expectations for CX have increased over the past year.
“It’s clear that good CX is tied to measurable business outcomes.” —Raj Balasundaram
As a result, contact centers are prioritizing practical, measurable uses of AI that provide what customers want: faster, automated self-service, with seamless handovers to human agents when needed.
We often see that focusing on how AI can handle specific contact center tasks, or aspects of a process, can be more successful than overly broad initiatives that are difficult to scale without major disruptions.
Manisha Powar:
Over the past year, contact centers have flagged a few clear CX shifts that look set to continue and they’re all connected.
First, service still matters more than almost anything. Qualtrics’ “2026 Consumer Trends” research shows customers who pick a company for great service report the highest satisfaction and trust (about 13-plus points above average).
That makes customer service a real trust anchor, especially when the economy feels uncertain. The driver: when things go wrong, people want quick, competent, empathetic resolution, and that’s what builds loyalty.
At the same time, AI is everywhere, but it’s a mixed bag. More consumers are using AI and sentiment is improving overall yet trust in organizations to use AI responsibly remains low. And for customer support specifically, AI is underperforming; only about 20% have used AI for support and a surprising share say they got no benefit.
“...you’ll see contact centers balancing cost pressures (use AI, automate) against the greater long‑term value of service and trust.” —Manisha Powar
So, contact centers are experimenting with automation but are running into quality and trust problems. The driver here is twofold: rapid AI deployment to cut costs and scale, plus immature solutions that don’t yet replicate the empathy and judgment humans provide.
Privacy and personalization are another tension point. Customers want tailored experiences, but most still think privacy risks outweigh the benefits of personalization.
That skepticism limits how aggressively firms can use data, and it forces contact centers to be far more transparent about data handling and consent. The driver is repeated stories and headlines about data misuse; consumers are cautious.
Feedback and listening are changing fast. Direct feedback rates are at all-time lows and when customers do speak up, their feedback is fragmenting across websites, apps, email, chat, and other touchpoints instead of funneling into classic surveys [Ed. Note, also see BOX].
That means contact centers relying on traditional post-interaction surveys are missing most customer sentiment. The driver is behavioral change; consumers prefer convenient, contextual ways to share input; or they don’t share at all.
Customer satisfaction and likelihood to trust, recommend, and purchase rebounded in 2025 after a dip in 2024, especially in competitive industries where switching between brands is easy. But nearly half of consumers still choose companies mainly on value: and those relationships tend to have lower trust and are more fragile.
So, you’ll see contact centers balancing cost pressures (use AI, automate) against the greater long-term value of service and trust.
Carmit DiAndrea:
Over the past year, three themes have consistently come up in conversations with contact centers: rising customer expectations, the need to better support agents in the increasing complexity of their roles, and the growing impact of AI-driven automation.
Customers expect faster, more personalized resolutions and seamless transitions across digital and human channels. Omnichannel is no longer optional—it’s table stakes—and with generative and agentic AI raising the bar, patience for inefficient, generic interactions that fail to deliver resolution is shrinking.
At the same time, employees are facing heavier workloads, more complex cases, and fragmented systems that make their jobs harder. Burnout is a real challenge, and organizations are realizing that supporting agents is critical to delivering great customer experiences.
The good news is that the right approach can address both sides of the equation. By leveraging purpose-built AI for CX within an open cloud platform approach, enterprises can:
- Unify disconnected systems with connected intelligence across every workflow, channel, and role.
- Automate workflows that span front-, mid-, and back-office tasks.
- Provide agents with real-time guidance and workflow assistance. This empowers employees to focus on high-value, meaningful interactions while delivering faster, more consistent outcomes for customers.
The drivers are clear: economic pressures demand efficiency, AI technology has matured to operate reliably at scale and human capital remains a top priority.
Organizations that adopt a platform-first, purpose-built AI strategy meet today’s higher expectations and create compounding value at scale that elevates both customer and employee experiences: while future-proofing their operations for the year ahead.
Eric Williamson:
While contact centers are finally being seen as more than a cost center, they’re also facing the same pressures as many other departments: do more with less.
AI has only accelerated this [trend]. With the rapid rise of generative AI, more organizations and contact centers have embraced the technology as a cornerstone of CX. In fact, according to the 2025 “CallMiner CX Landscape Report”, which surveyed global CX and contact center leaders, the majority (96%) now view AI implementation, including generative and agentic AI, as a strategic priority.
Strategic AI adoption requires identifying the right automation opportunities while maintaining genuine customer relationships. Today, the most successful organizations are strategically deploying virtual agents to automatically handle routine tasks and inquiries, which frees up human agents to focus on complex, relationship-building conversations that require empathy and personal connection.
“The claim that customers leave because of poor CX is directionally valid but often oversimplified.” —Eric Williamson
Looking ahead, we expect this paradox to persist. AI will be key to scaling CX in contact centers, but it requires a measured approach.
Organizations must first demonstrate clear ROI through proven automation use cases before advancing to more complex implementations. Those that strike the right balance, maximizing innovation while minimizing operational and financial friction, will deliver meaningful, loyalty-driving CXs.
Q. Let’s drill deeper into CX and loyalty. Is that oft-made assertion customers will leave companies because of poor CXs. Isn’t that based mostly on surveys? What about actual sales/revenues/market share? Is it not true:
--Companies know/watch what their competitors are doing and react accordingly, resulting in very little differences between them/their offerings?
--Companies strive, and when feasible, make their products/services sticky?
--Customers may complain and threaten to leave but remain loyal for convenience, price, and inertia reasons?
Raj Balasundaram:
We surveyed 5,000 consumers for our State of Customer Experience research and found that 78% say they’re likely to switch to a competitor after one terrible experience, up from 67% last year. These growing numbers show that companies face risks when they fall short of meeting CX expectations.
We have seen companies that prioritize good CX drive revenue growth well beyond their peers, with customers spending more and purchasing more frequently.
In our survey, product quality is a top factor driving loyalty for 53% of consumers, but this is closely followed by “excellent customer service” (48% of respondents). If they have an amazing CX, 86% of consumers say they will likely buy again, while 81% will likely recommend the company, and 73% will likely write a positive review.
It’s clear that good CX is tied to measurable business outcomes.
Manisha Powar:
We found that when people pick a company because of great customer service, their satisfaction (92%) and trust (89%) scores are about 13 points higher than average: the biggest premium of any reason customers choose a brand.
While our 2026 Consumer Trends report found that 46% of consumers choose companies for good value for money, these economically-driven decisions shift quickly when competitors undercut prices or when financial pressures change. Financial insecurity already correlates with lower loyalty, and in today’s uncertain economy, price-based loyalty is especially vulnerable.
Service and product excellence create durable advantages. Those companies that prioritize good customer service or products achieve highest satisfaction and trust: relationships competitors can’t easily replicate when price is the only differentiator.
Companies need back-end excellence to maintain margins while meeting price expectations. Technology and operations that reduce costs (turnover, process inefficiencies) allow companies to compete on value without sacrificing quality or entering unsustainable price wars.
Carmit DiAndrea:
Traditionally, product or service quality accounted for most customer churn, but that balance is shifting. Today, I’d estimate it’s closer to a 60/40 split between product/service experiences and customer experience, trending toward parity.
Why? In a world where products and services are often similar across competitors, CX has become the true differentiator. How companies handle exceptions, resolve issues, and manage moments of truth now drives loyalty. A delayed shipment or minor issue can be forgiven if the CX is seamless and proactive: but can quickly erode trust if customers feel ignored or frustrated.
“Take an end-to-end view of customer journeys, not just individual touchpoints.” —Carmit DiAndrea
Generative and agentic AI are accelerating this shift by enabling companies to anticipate needs, flag dissatisfaction early, and empower agents to resolve issues effectively. This proactive, intelligent approach turns potential pain points into positive experiences and strengthens loyalty at scale.
In short, CX is more important than ever. NiCE’s “The State of CX” report shows brands excelling in customer sentiment outperform peers by 43 percentage points in stock returns over five years. Brands that don’t invest in CX risk losing customers, even if their products are excellent. Prioritizing CX now is not just a nice-to-have; it’s essential for retention, loyalty, and long-term growth.
Eric Williamson:
The claim that customers leave because of poor CX is directionally valid but often oversimplified. Survey-based metrics, such as Net Promoter Score (NPS) and customer satisfaction score (CSAT), capture sentiment and intent, but don’t always reflect real behavior in terms of revenue or churn.
These measures can be useful, but they often highlight only those customers who are most vocal, overlooking the broader customer base.
To get a stronger sense of loyalty, organizations need to move beyond just surveys. This means analyzing real interactions across the full customer journey: calls, chats, social media, and digital touchpoints. These conversations surface concerns, expectations, and opportunities better than survey data alone, allowing companies to act quickly and purposefully.
When businesses connect these customer insights to proactive, personalized engagement, CX leaders can transform passive loyalty into active loyalty built on trust and connection.
The result isn’t just reduced churn, it’s stronger, more resilient growth driven by customers who feel heard, valued, and supported.
Q. What are your recommendations to contact centers that seek to improve their CX and also AX, and their total results?
Raj Balasundaram:
My recommendations to contact centers is [as follows]:
- Start small with AI. Targeted, incremental AI deployments that focus on specific pain points and micro-workflows are much more effective than broad, one-size-fits-all deployments.
- Prioritize what truly matters to customers. That means fast resolution, effective self-service and seamless handoffs between intelligent virtual assistants and agents.
- Give agents the tools and knowledge they need to succeed. With 85% of customers using multiple channels and digital use rising sharply, agents need access to omnichannel customer data and instant context to provide a seamless experience.
Ultimately, the leaders in CX will be those that can strike the right balance between AI-powered CX automation that delivers speed and volume, and the human touch required to navigate complex conversations.
Manisha Powar:
Contact centers need continued investment in omnichannel listening and in hybrid models that pair AI with human agents, providing scale and cost efficiency without losing empathy and connection.
Contact center leaders must place more emphasis on transparency and data governance to close the consumer trust gap with AI, with smarter, context-specific AI deployments focused on clear user value rather than blanket automation.
In short: service quality and trust remain the differentiators. AI and data can help, but only if contact centers implement them carefully and listen across more channels.
Carmit DiAndrea:
My recommendations fall into four categories:
- Empower Employees. Invest in purpose-built AI copilots, and workflow automation that reduce friction and cognitive load. When AI is designed for CX, it enhances agent performance and satisfaction, enabling people to focus on high-value interactions that drive better outcomes.
- Redesign Journeys. Take an end-to-end view of customer journeys, not just individual touchpoints. A platform-based approach allows AI to orchestrate interactions across digital and human channels, across the front-, mid-, and back-office, proactively addressing friction and ensuring seamless handoffs, so customers experience consistent, personalized service at scale.
- Measure What Matters Now. Move beyond decades-old operational metrics. As more organizations deploy generative- and agentic AI-based solutions, it’s becoming increasingly important to understand and continuously improve how these solutions are using data, making decisions and impacting key business outcomes.
- Analyze Historical Interactions. XO (experience orchestration) turns historical customer interactions into a prioritized, governed automation backlog and deploys the highest-value, production-ready flows with built-in measurement. [This way] you ship high-performing CX automations at the speed of business.
Above all, don’t treat AI as a generic tool or replacement strategy. The winning approach is purpose-built AI working across an integrated CX platform, augmenting humans to deliver speed, scale, and intelligence while preserving personal connections and judgment. Enterprises that embrace this approach will not only improve CX and AX but they’ll future-proof their CX.
Eric Williamson:
To improve both the CX and agent experience contact centers should start by capturing data from all customer interactions. Doing so uncovers the root causes of dissatisfaction, as well as satisfaction, and highlights opportunities to coach and empower agents.
From there, balance automation with human engagement. AI can streamline repetitive, high-volume tasks and provide real-time guidance, while human agents focus on empathy and complex problem-solving.
In the years ahead, it won’t be the organizations that simply collect the most data or deploy the most tools that lead.
Instead, CX leaders must:
- Blend solicited and unsolicited feedback to capture a full spectrum of customer insights.
- Lean into automation and AI-driven analytics to accelerate data interpretation and close feedback loops faster.
- Establish robust governance frameworks that safeguard trust while driving growth.
This cycle of listening, learning, and acting, underpinned by responsible AI, creates better customer relationships, stronger agent performance, and better business outcomes.
Are Surveys Still Valid?
Each of us has no doubt heard and seen the requests to respond to surveys when we interact with organizations so they can find out what we think about our experiences with them. But how effective are these methods?
So, we posed this question to our panel: “Are there changes in how contact centers are – and should – listen for the voices of customers? Are customer surveys becoming more or less valid? Are customers and companies becoming tired of surveys?”
Raj Balasundaram:
Survey data remains vital for capturing broad sentiment, but there’s growing survey fatigue among consumers. Not every experience is best measured through a post-interaction questionnaire.
In the past, contact centers have added richer listening methods, such as speech analytics. With AI, we can now detect consumer sentiment in real time during calls and from agent input. These newer tools can capture a more complete picture of CX, as well as the employee experiences, providing actionable insights without overwhelming customers with surveys at every touchpoint.
Additionally, when brands bring more complex journeys online, there is a need for struggle detection. Voice of the customer solutions can identify friction points and intervene instantly to keep customers moving forward, before they result in lost revenue and changing customer loyalty.
Manisha Powar:
Recent research from Qualtrics shows direct customer feedback is at all time lows. And when consumers do respond, their feedback is fragmented across channels rather than flowing through traditional surveys.
The data shows that only 29% of customers provide direct feedback after a good or bad experience. This is a continuation of a troubling trend, as the number of consumers who said they provide direct feedback after a bad experience is down 7.7 points since 2021.
That has important implications for survey impact and for how companies should design listening strategies.
If only three in 10 customers give direct feedback and that feedback is splintering across many touchpoints, a contact center that relies solely on post interaction surveys is effectively missing a majority of customer sentiment.
Surveys themselves are not inherently invalid. But their coverage and representativeness have eroded.
Contact centers must improve the effectiveness of their survey programs and make them more adaptive. They need to evolve to omnichannel listening, looking deeply into behavioral and unstructured customer feedback to capture the 71%-plus of sentiment that conventional survey programs are likely missing.
Carmit DiAndrea:
Surveys remain an important tool in the voice of customer toolkit, providing critical direct feedback to companies.
But the future is about multi-channel, real-time listening. That includes analyzing interaction data using AI across voice, chat, social, and digital interactions, detecting customer intents and sentiment, and surfacing systemic issues without waiting for surveys.
With AI, organizations can process millions of unstructured interactions to generate a more complete and accurate view of customer voice than surveys.
Eric Williamson:
Although traditional survey metrics like NPS and CSAT have been the dominant measures for years, they have limitations. Legacy surveys tend to offer only hints about what’s happening: pointing to symptoms rather than root causes. They can be biased, limited due to survey fatigue, and are often too simplistic to capture the nuances of an individual customer journey.
However, despite these challenges, reliance on surveys has actually grown. The CallMiner report found that 72% of organizations say they collect all or a majority of solicited feedback (feedback they actively request, like surveys): a notable increase from 2024.
This underscores the persistent challenge organizations face in balancing solicited and unsolicited feedback methods (unprompted input such as reviews or conversations).
To get a complete view of CX, organizations have an opportunity to collect unsolicited feedback as well as solicited feedback from surveys.
By combining these feedback methods, organizations can not only capture a more comprehensive data set but also use unsolicited insights to make solicited efforts more targeted and relevant. This creates more personalized, contextual outreach that drives higher-quality responses and builds greater customer trust.
When more data is captured and analyzed at scale using AI and automation, organizations can strengthen customer service to improve efficiency, engagement, satisfaction, actual products and/or services, and ultimately the entire business.