CX Today’s 2025 Trends series gathers insights from industry leaders to identify the forces that will shape customer experience in the year ahead.
In our second round of CX trend predictions, our respondents zero in on a reality that many organizations are only now confronting: AI’s transformative potential depends entirely on the data feeding it.
Without clean, connected, and governed data, even the most sophisticated AI systems will deliver underwhelming results. The predictions below suggest that 2026 will be less about chasing the next AI feature and more about fixing the infrastructure underneath.
Meet the experts:
- Derek Slager, CTO and co-founder at Amperity
- Liz Miller, VP and Principal Analyst at Constellation Research
- Prashanth Krishnaswami, Head of CX Strategy at Zoho
- Tim Banting, head of research and business intelligence at TechTelligence
- Simon Harrison, Analyst and Executive Partner for Actionary
CDPs Evolve Beyond Storage
Derek Slager, CTO and co-founder at Amperity, sees customer data platforms moving beyond their traditional role as glorified databases.
“My biggest prediction for 2026 is that CDP category is going to evolve from building systems of record to systems of intelligence,” he says.
“Gone are the days where a CV simply takes all the disconnected assets and puts them into a singular database. That’s a great starting point, but it’s not enough for where we need to go to drive optimal customer experience.”
Slager’s vision involves layering AI on top of unified data to create systems that don’t just store information but actively generate insights and drive decisions.
“Where I see things going, building on top of those data foundations, using all forms of AI, generative AI, classic ML, et cetera, in an orchestrated way to utilize that data to drive absolutely outstanding customer experience by creating experiments and understanding those, building decisioning mechanisms and having a holistic view of how those things are working, contributing back to that data foundation, and ultimately building a closed loop system that continues to drive incredible customer experience over time.”
CDPs that simply aggregate data no longer meet the bar. Organizations need platforms that can interpret, act on, and continuously refine the information they hold.
The Data Drought Nobody Saw Coming
Liz Miller, VP and Principal Analyst at Constellation Research, warns that AI’s appetite for data has exposed a problem most organizations weren’t prepared to face.
“If I look into my crystal ball for 2026, it would be hard to say that I’m not seeing those two dreaded letters pop up, you know, A and I, that we talk a lot about,” she says.
“But here’s what’s interesting. If we have just gone through 2025, which is a year of trying to figure out what it was and what we’re going to do with it, 2026 is going to be a lot about data.”
Miller explains that the optimism around AI has run headfirst into a resource constraint.
“The reality is, is all the big dreams that we had about AI and all the great things that agents could do in agentic AI and how we’re going to change our business and how work’s going to change, how customer experience is going to change, everything’s going to change because of AI. None of it changes without data. And we’re really getting to that realization that the data drought we’ve been warning everybody about has actually accelerated because AI is a voracious eater of data. It has an insatiable appetite, and it’s coming.”
The problem is that organizations didn’t prepare their data infrastructure for what AI demands.
“The reality is, we didn’t get our data in check. We didn’t get our legacy systems in check. We didn’t clear the table for what AI wants to come and dine on. So that’s what we’re going to see a lot of in 2026.”
Miller predicts new partnerships and workflows will emerge, particularly where content, data, and experience intersect. “I think we’re going to see a lot of where this intersection between content, data, and experience really starts to impact what the contact center is doing. It’s going to forge new partnerships. It’s going to force new workflow partnerships.”
Her message is blunt: stop assuming your data is ready and start treating data preparation as the primary barrier to AI success.
Data Readiness and Culture Trump Technology
Prashanth Krishnaswami, Head of CX Strategy at Zoho, argues that two factors will separate AI winners from losers: data readiness and organizational culture.
“My primary prediction for the year 2026 is that data readiness and company organizational culture will be the biggest determinants of AI success in customer experience, particularly in mid-sized and large organizations.”
The data problem stems from years of best-of-breed tool adoption creating fragmented technology stacks.
“Thanks to many years of driving best of breed tools for very specific use cases, the technology stack has become super complex and complicated in most mid-sized and large organizations. So we’re in peak SaaS complexity in that sense. And transitioning from this status quo to an AI-first, AI-native form of existence isn’t going to be straightforward.”
Krishnaswami points out that enterprise data is scattered across systems that don’t talk to each other.
“Enterprise data naturally is scattered all over the stack across various areas. And these applications don’t necessarily talk to each other well enough already, unless you’re using an integrated suite like Zoho. So AI certainly needs a very smooth layer of data, which it can rely on for various things like inference and decision-making.”
Culture presents a separate challenge.
“The second is, again, that many organizations are culturally not best suited to empower every employee in what they do. And they’re not necessarily built to fail. They’re just a little bit resistant to change, or they could be restrained by compliance. They could be impeded by scarcity for capital or margins or things like that. Or maybe they’re even just suffering from technology debt that they’ve accumulated over decades.”
The technology exists to build AI-powered execution layers across entire businesses. Whether organizations can actually deploy it depends on data readiness and cultural willingness to change.
AI Governance Becomes a Dealbreaker
Tim Banting, Head of Research and Business Intelligence at TechTelligence, predicts that AI governance will shift from a checkbox exercise to a core buying criterion.
“My predictions for customer experience in 2026 will be that AI governance will become a customer experience compliance layer,” he says.
“What we’re seeing at TechTelligence is buying intent data from Q4 2025 is showing research into AI compliance and regulation SP has risen by about 30 % compared to the previous quarter.
“This really tells us that AI governance is now a core part of the customer experience strategy, are not a side issue.”
Buyers are demanding transparency and accountability. “We think that buyers want systems that provide audit trails, explainable decisions, and full accountability for every AI driven action. So in 2026, vendors that can’t show how their AI works won’t make it past procurement.”
Governance isn’t a nice-to-have anymore. It’s table stakes.
The Master Orchestrator Problem
Simon Harrison, Analyst and Executive Partner for Actionary, warns that without a clear center of gravity for AI, organizations will end up with conflicting agents creating chaos instead of value.
“When it comes to our prediction of 2026, we feel the application of AI will normalize,” he says.
“The leaders will start pushing back on it as a mandate, which is how AI started to be suddenly become a thing. And it will stop [being] viewed as something that needs to be applied to every problem.
“AI can’t necessarily fix broken customer experiences. And in fact, it may just make bad experiences happen faster.”
Harrison identifies a looming problem: every vendor wants to be the master orchestrator for AI agents, but their priorities don’t always align.
“Added to that, there’ll be a new problem emerging based on every vendor out there in the CX space and perhaps beyond in just an AI provider in the AI provider landscape where they want to be the agent AI master orchestrator. However, for example, VOC agents, when it comes to agent AI, they’re more focused on how people feel while CRM agent AI agents are more about pushing tactical steps to fix issues issues perhaps at the lowest cost. The reality is you need both.”
Without clear orchestration, organizations end up with competing systems working at cross purposes.
“The predicton for 2026 from Actionary is that companies will finally realize they need a clear center of gravity for AI or a master orchestrator agent, let’s call it. They’ll also end up with conflicting agents, AI capabilities, and as a result, even more fragmented experiences that feel intelligent on paper but are chaotic for customers.”
The Unappealing Work That Actually Matters
The predictions in this article point to an uncomfortable truth: AI’s success depends on infrastructure work that most organizations don’t have in place. Data readiness, governance frameworks, cultural alignment, and clear orchestration strategies aren’t optional extras. They’re prerequisites.
Organizations that spend 2026 fixing these foundational issues will be positioned to extract real value from AI. Those that keep chasing the latest model or feature without addressing the underlying data problem will keep hitting the same walls.
It’s not glamorous work, but it’s the work that will separate AI winners from AI disappointments.
Check out CX Today’s CX Trends Part One for agentic AI predictions.
