Automation has become a standard approach in the field of Customer Experience (CX). According to the CallMiner CX Landscape Report for 2026, 99% of organizations involved in CX use automation in some form when interacting with customers. This figure indicates that the industry has largely addressed the need to implement automation. However, current research findings point to a more complex issue: whether this automation is actually delivering results.
In less than one in four organizations (23%), customers describe their interactions as both highly automated and continuously optimized using CX data. Simply put, the pace of automation adoption has exceeded the speed of developing the intelligence required to manage it. This leads to a widening gap between companies that are implementing automation and those that are continuously refining it.
CX Automation Adoption Outpaces Optimization
Almost every surveyed organization has implemented automation at some stage of the customer journey. Nevertheless, only 24% report that their automated customer experience is 'Very Positive,' indicating that implementation alone does not guarantee improvements for customers.
Organizations do not lack data to bridge this gap. Every surveyed company reports collecting CX data, and 66% now rely on automated processes for its analysis, up from 53% last year. However, data collection and analysis are not equivalent to action based on that data. More than two-thirds (68%) state that they still do not fully utilize CX data, which is higher than the 62% reported in 2025. When CX data is used, it is more often applied to understanding customer satisfaction rather than improving the automation itself. Only 30% use the insights gained to refine the performance of automated interactions, and only 22% use them to determine what should be automated in the first place.
The problem is exacerbated by cross-departmental misalignment. Almost all organizations (94%) face difficulties aligning CX data and feedback across different teams. This results in customer information remaining locked within the department that generated it, instead of influencing automation decisions in other parts of the business.
What Distinguishes the Most Effective Automated Experience
The report draws a clear line between organizations reporting a 'Very Positive' automated experience and those reporting 'Mixed' or 'Negative.' Companies in the 'Very Positive' group much more consistently optimize automation using CX data—49% versus only 8% among companies with 'Mixed' or 'Negative' experiences. They also use richer sources of customer information during and after interactions, including automation performance data from chatbots, voice bots, and Interactive Voice Response (IVR) systems, as well as omnichannel communication transcripts.
Knowing when to involve a human is equally important. Almost all organizations (95%) agree that human agents provide more value than automation or AI in at least one type of interaction, especially when dealing with complex problem-solving, significant business implications, customer vulnerability, or empathy. Organizations demonstrating a 'Very Positive' automated experience are more likely to hand off an interaction to a human (76% versus 68% for those reporting 'Mixed' or 'Negative' experiences), suggesting that the most effective automation strategies are designed with inherent limitations in mind.
Artificial intelligence reinforces this balance, rather than replacing it: 96% of organizations are implementing AI in their CX initiatives, and 85% use it for at least one human-involved scenario—most often for real-time assistance, boosting agent productivity, and for training and coaching. Concerns have not disappeared: 43% of organizations believe customers still prefer human interaction, and 40% think AI struggles with complex, emotional, or risky interactions. These concerns decrease slightly year over year, but they remain a reminder that trust is earned gradually through automation.