Off the back of the launch of our new report, The Five Forces Shaping CX, drawing on data and insights from Aspire CCS, we spoke with the company’s Founder & CEO, Kaspar Roos, to unpack the current state of the CX industry, explore the report’s key findings on CX maturity and AI governance, and dig into what CX leaders need to prioritise in today’s fast-moving landscape.
Aspire surveyed 322 enterprise respondents across six countries for The State of Customer Communications and Experience Management 2026. What’s the one headline finding you’d want every business leader to walk away with?
CX maturity, not size, sector, or budget, is the single greatest influence on a business’ approach to customer communications. Aspire CCS’s research shows that organisations climb a three-stage ladder: CCM 1.0, where IT and Operations treat communications as a document-centric cost centre and compliance box to check; CCM 2.0, where line-of-business teams have introduced digital channels but remain fundamentally document-based and siloed; and CXM, where Marketing and CX leaders use AI and real-time data to orchestrate an ongoing dialogue built around the customer’s actual journey. CCM 1.0 and 2.0 often look broadly similar to each other, and the real transformation happens at the steep climb into CXM, where an organisation’s focus on developing personalised and seamless experiences from the customer’s point of view enables them to advance far beyond their less mature competitors by nearly every measure. At CX maturity, communications spending is expected to grow rather than decline, GenAI adoption nearly doubles, ownership shifts meaningfully toward Marketing and CX, and outcomes like accessibility compliance and CCM-CXM integration improve dramatically. CXM isn’t simply “better CCM.” It’s a different operating model, and understanding where your organisation sits on that ladder is the first step to knowing what actually needs to change.
NPS nearly doubles between the least and most CX-mature organisations. How should a marketing or CX leader be using that number to build the case for investment internally?
Nearly half of CX mature organisations have fully integrated CCM and CXM processes, compared to 10% of CCM 2.0 and less than 2% of CCM 1.0. Net Promoter Scores nearly double between CCM 1.0 and CXM. An NPS gap of that size is the clearest ROI argument a marketing or CX leader can make for pursuing convergence between CCM and CXM. Leaders should reframe integration from an IT or efficiency project into a strategic one, tying a concrete customer-outcome metric directly to a specific, achievable milestone (like CCM-CXM alignment) rather than an abstract “transformation” goal. The most effective way to build the internal case is to pair this NPS data with the progression of ownership: as organisations mature, they bring Marketing/CX and executive leadership into the communications conversation alongside Technology/IT, precisely because that’s where the ultimate accountability for broader customer interaction lies.
One in five customers globally switched providers this year over poor communications experience, rising to one in four under-45s. What does that tell a marketing leader about where their churn is actually coming from?
Five of the top six reasons customers cited for switching providers after a negative communications experience were directly tied to content: incorrect, inconsistent, or unclear information delivered in the wrong tone or context. Consumers don’t separate “communications” from “experience” the way businesses do internally. A poorly timed or irrelevant message damages trust in the same way a poor product experience would. Younger, more affluent, and tech-savvy consumers have all been conditioned by real-time, personalised experiences in their interactions online and expect their chosen brands to meet the same standard, regardless of the sector, application, or channel. For a marketing leader, the fix isn’t necessarily a better offer, it’s redesigning the interaction from the outside-in by focusing on what the customer is trying to understand, decide, or do.
Budget for customer communications still sits with Technology/IT in six out of ten organisations, even though it shifts toward Marketing/CX as businesses mature. What does a marketing or CX leader need to do to make the case for owning that budget?
A Marketing or CX leader shouldn’t make the case that customer communications “belong” in Marketing rather than IT. They need IT as a critical partner. The case is really about changing what the investment is expected to achieve and, therefore, who needs a meaningful say over how the budget is spent. Historically, IT owned CCM because it was primarily a technology and production problem: generate the document, deliver it reliably, control cost and meet compliance requirements. But as communications become more interactive, personalized and connected to customer journeys, the investment increasingly determines customer engagement, digital adoption, satisfaction and commercial outcomes. Marketing/CX therefore needs to put measurable customer outcomes around the investment: Are we reducing avoidable service calls? Increasing digital engagement? Helping customers complete journeys? Improving conversion, retention or satisfaction? That creates the business case for greater Marketing/CX budget authority.
Unsupervised, high-autonomy AI use runs at roughly the same rate across every maturity level, including organisations that should know better. What does that tell you about where governance is actually failing?
Governance seems to be failing more at the point of deployment, not necessarily at the policy level. Most large organisations understand that AI needs controls, but having an AI policy is very different from ensuring those controls are embedded in every individual use case. The interesting thing in our research is that CX-mature organisations generally do behave differently. They make greater use of high-autonomy AI with human-in-the-loop oversight, which suggests they’re more comfortable deploying AI while putting controls around it. But the proportion using high-autonomy AI without that oversight is remarkably similar across all three maturity levels. That suggests there are still pockets of AI adoption running ahead of enterprise governance, even in sophisticated organisations. A business unit may deploy an AI capability, or a vendor may introduce AI into an existing workflow, without the same level of scrutiny being applied consistently. So governance needs to operate use case by use case: What data can the AI access? What decisions can it make? What gets logged? Where does a human need to intervene? And who is accountable when something goes wrong?
Two-thirds of CX-mature leaders cite data privacy as their top barrier to scaling AI further, is that healthy caution, or are the most sophisticated organisations getting stuck right when they should be moving? And for businesses tempted to skip governance and just move fast, what does your data say actually happens to them?
Two-thirds of CX-mature businesses named data privacy as their top barrier to further AI implementation. These organisations have already established the value case for artificial intelligence, but they are still grappling with how to deploy it safely at scale, which is precisely the right question to be asking at their stage. The risk isn’t that they’re moving too slowly; it’s that a meaningful share of organisations at every maturity level are running unsupervised high-autonomy AI. In other words, some of the same organisations citing privacy as a barrier to further expansion are also outrunning their own governance elsewhere. For businesses tempted to skip governance in the service of speed, the data is fairly direct. Confidence in AI agents making real decisions has actually fallen over the past year industry-wide, even as adoption has risen, because retrofitting oversight onto a live, high-autonomy system is far harder and riskier than baking it in from Day One.
Where do you see agentic AI pulling the market over the next 12 to 24 months?
Over the next 12 to 24 months, agentic AI will drive us toward an architecture where AI decides what should happen next and CCM turns that decision into an actual customer communication experience. This isn’t a vision of full autonomy: human oversight, permissions, and governance remain essential, with the level of autonomy calibrated to the risk of the interaction, but it does mean communications capabilities need to become services that agents can discover and invoke, not just applications humans operate directly, with MCP and APIs as the connective tissue between the decision and execution layers. At the same time, AI is increasingly driving a growing percentage of originating traffic, forcing enterprises to design content and communications for AI interpretation as much as human readers, so prospective customers can enter a journey at the next-best interaction rather than starting over. The net effect is that agentic AI is becoming the mechanism driving CCM-CXM convergence by providing a single intelligence and orchestration layer across marketing, sales, onboarding, billing, and service that maintains customer context across interactions without requiring the underlying systems to disappear.
For a business leader with time to read only one part of the report, where should they start, and what will it change about how they think?
I’d start with the section explaining the progression from CCM 1.0 through CCM 2.0 to CXM, because that provides the lens for understanding almost everything else in the report. The research shows that CX-mature organisations operate very differently from less mature organisations: in how they invest, how they use technology and AI, how communications are owned, and ultimately in the customer outcomes they achieve. The important point for a business leader is that the findings shouldn’t be treated as a list of independent trends. Where you are on that maturity journey changes what you should prioritize. An organisation still at CCM 1.0 may need to focus on building the business case and modernising its foundations; a more mature organisation may need to focus on orchestration, AI governance or closing the remaining gaps between communications and the wider customer experience. So hopefully it changes the question from “What should we do about AI, accessibility or communications technology?” to “Where are we today, where do we want to get to, and what is preventing us from getting there?” That turns the research from a collection of statistics into a practical set of recommendations for what to do next.