Blog This perspective is informed by recent research from Everest Group in their white paper, “AI-powered Future of CX Analytics,” supported by iQor CXBPO™, and explores what the findings mean for how brands listen, learn, and act in every signal across every customer interaction.
“CX analytics has become a strategic pillar of enterprise transformation, serving as one of the most impactful applications of AI in business today.”18
“AI-powered Future of CX Analytics,” Everest Group
Feedback isn’t something customers “give” anymore. It’s something they generate constantly, in every chat bubble, every frustrated pause, every abandoned cart, every complaint or compliment, and every moment they say, “Your competitor does this better.”
The problem? Most brands aren’t listening in the places it actually happens.
For years, brands have begged customers for feedback. Pop-up surveys. Post-call questionnaires. Hello, NPS fatigue! Yet customers have been sharing their input all along, just not always in the format brands were asking for.
CX leaders are finally waking up to a truth that feels obvious in hindsight: The most valuable customer insights aren’t in surveys. They’re hiding in plain sight inside everyday interactions.
Customers express themselves at every moment, not just when asked.
Now, AI turns those moments into insight, the kind that exposes friction before it becomes churn, reveals intent before customers voice it, and gives brands the power to act in the moment instead of apologizing after the fact.
The End of Survey-Centric CX
Surveys have their place. Overreliance on them no longer does.
Surveys suffer from low response rates, stale sentiment snapshots, and feedback cycles that move too slowly. Meanwhile, customers create massive streams of rich interaction data across all CX channels.
According to “AI-powered Future of CX Analytics,” Everest Group’s latest white paper, “Even customers perceive direct feedback mechanisms as burdensome, as reflected in low completion rates and their limited impact on actual outcomes.”4
People aren’t participating in surveys, and the brands relying on them aren’t getting the full picture. If the only people you “listen” to are the ones responding, you aren’t listening. You’re guessing.
AI changes that.
Instead of asking customers how they feel, AI learns to understand them through:
- Tone detection
- Emotion and sentiment analysis
- Intent recognition
- Friction detection
- Behavioral cues
These are insights traditional surveys can’t touch.
Unlike sampling, AI-powered analytics allows brands to achieve the view Everest Group calls essential, noting that “[s]uccess now depends on building real-time, holistic customer profiles that integrate preferences, behaviors, and contextual signals.”3
Everest Group’s white paper further emphasizes that “[the] diversity [of interaction data] underscores the urgent need for data unification to build a complete, cross-channel view of customer behavior.”4
This is listening while the moment is happening.
Brands still relying on traditional VOC tools will be outpaced by those who can understand customer emotions, needs, and risks as they unfold and not days or weeks later.
The Competitive Edge You Can’t See
Here’s where it gets interesting.
Listening is step one. Learning instantly is what separates leaders from the laggards.
Organizations are moving well beyond reactive reporting, noting that enterprises are increasingly adopting predictive modeling and prescriptive recommendations to drive proactive CX decisions and next-best actions.5
This shift is redefining what performance looks like in CX.
It’s no longer about how much data you collect or how many dashboards you maintain.
“Our survey indicates that 73% of enterprise respondents have reached predictive analytics maturity across some use cases, such as demand forecasting and churn prediction, while only 6% have advanced to prescriptive CX with embedded decision support. 21% remain with operational analytics, relying on manual, rule-based reporting.”8
“AI-powered Future of CX Analytics,” Everest Group
It’s about how quickly insights surface, how seamlessly they flow across systems, and how fast teams can act on them.
Let’s be honest:
- Traditional dashboards don’t deliver velocity.
- Manual reporting doesn’t deliver velocity.
- Static analytics don’t deliver velocity.
Brands need intelligence that updates as customer experience unfolds.
But Everest Group’s white paper highlights a major gap: “Only 4% of enterprises have fully integrated major customer systems into a single platform,”10 leaving most organizations with fractured, slow-moving insight channels.
Worse yet, Everest Group reports that many enterprises face “technical, operational, and organizational issues, ranging from infrastructure and integration complexities to gaps in data readiness and resource capabilities,”5 which stall real-time intelligence efforts.
The brands that break away first will be the ones that:
- Detect friction as it happens
- Predict churn before it hits
- Guide agents with real-time coaching
- Respond to sentiment shifts in the same interaction
- Surface insights continuously, not retroactively
This is where AI becomes an advantage. In modern CX, intelligence isn’t a static report; it’s near real-time visibility into every customer interaction, enabling teams to act before small issues turn into bigger ones.
Turning Interactions Into Enterprise Strategy
Imagine if every call, chat, email, or social post could shape your next product decision, pricing strategy, or retention play.
According to Everest Group’s white paper, AI-powered CX platforms now enable enterprises to “[capture] what customers say, do, feel, and expect”6 and provide a 360-degree view of the customer journey that drives unified decision-making across the organization.
This is where interaction data becomes leadership fuel:
- Customers reveal product gaps long before KPIs catch up.
- They signal policy friction before it turns into cancellations.
- Their language exposes emotional triggers and decision drivers.
- Their behavior highlights emerging use cases before research teams spot them.
Everest Group’s white paper reinforces this shift by stating that integrated AI platforms deliver measurable business outcomes by operationalizing insights and enabling faster decision-making.10
A subscription services company used iQor’s insights to retrain agents, streamline claims scripts, and anticipate pain points, resulting in:
+30x save rate
+9.5% improvement in NPS
+19% improvement in first call resolution
With AI-led analytics, organizations stop reacting and start anticipating, and customers feel it instantly. Problems get addressed before they escalate, experiences feel tailored instead of templated, and customers no longer have to repeat themselves to get things done.
The result is CX that feels intuitive, effortless, and built around the customer, not the system.
Listening Differently, Learning Faster, Acting Smarter
The familiar CX playbook of surveys, sampling, and static dashboards is fading. A new playbook is emerging, and it’s built around three capabilities:
Listen Differently
AI doesn’t wait for surveys. It learns from every call, chat, and click.
Learn Faster
AI-driven analytics “[transform] raw interactions into real-time, actionable intelligence”3 that frontline teams and leaders can apply instantly.
Act Smarter
These insights go beyond guiding service interactions. They’re increasingly shaping enterprise decisions and strategy across product, pricing, policy, and customer journey design.
91% of enterprises now operate CX analytics using a hybrid model, blending internal teams with external partnerships to balance agility, scalability, and domain expertise.8
“AI-powered Future of CX Analytics,” Everest Group
Leaders embracing this shift see the connection between insights and outcomes. “[E]nterprises are now embracing AI-based CX analytics to enable hyper-personalized engagement and optimize customer journeys,”3 elevating CX from reactive reporting to a real-time intelligence engine. It’s this evolution that allows AI-enabled analytics to drive hyper-personalization, faster decision-making, and measurable ROI for organizations that adopt it strategically.
89% of enterprises plan to maintain or increase CX analytics investment by 2026, with more than half expecting significant budget growth as real-time intelligence becomes a core capability.16
“AI-powered Future of CX Analytics,” Everest Group
The future belongs to brands that treat data as a living system, not a quarterly report.
To leaders who see every customer touchpoint as intelligence, not noise.
To companies that understand the competitive advantage of turning conversations into direction.
The Future of CX Is Already Speaking
Your customers are talking constantly and across every channel.
They’re showing you what works.
They’re revealing what breaks.
They’re signaling risk, loyalty, emotion, and opportunity, all in the flow of everyday interactions.
This is why the shift underway isn’t subtle. Everest Group calls this shift the movement toward “real-time, insight-led CX operations”3 that drives measurable outcomes and long-term loyalty.
AI-based CX analytics can “sense, analyze, and act on signals in real time,”7 enabling dynamic engagement and continuous CX improvement cycles, not static, after-the-fact reviews.
This is where platforms like iQor’s Insights iQ™ shift CX from awareness to execution. By operationalizing customer intelligence from every interaction inside day-to-day workflows, Insights iQ helps brands spot friction, prioritize action, and respond with precision. AI finally lets organizations listen at the scale, speed, and depth that modern CX demands, transforming raw interactions into insight that drives measurable outcomes and long-term loyalty.
Customers are speaking everywhere.
The real question is: Can you listen to all of it (and act fast enough)?
To understand how enterprises are scaling AI-powered analytics, transforming CX operations, and turning billions of data points into real-time intelligence, explore the full Everest Group white paper.
Joe Przybylowski is Senior Vice President, AI, Data Science, and iQor Labs at iQor CXBPO™. Click here to connect with him on LinkedIn.
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