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Global study finds AI-assisted human agents dominate enterprise CX strategies, but many organizations lack the tools needed to measure AI effectiveness
A new global study commissioned by TELUS Digital has revealed that while artificial intelligence is becoming deeply embedded in customer experience (CX) operations, many organizations still lack the infrastructure required to effectively monitor and optimize AI performance.
The research, conducted by Ryan Strategic Advisory, surveyed 815 enterprise customer experience decision-makers across 12 countries and multiple industries, including financial services, healthcare, telecommunications, retail, and technology. The findings suggest that enterprises are rapidly adopting AI-assisted customer service models, yet significant gaps remain in how AI outcomes are measured and improved.
According to the report, the most common approach across major customer-facing functions is the use of human agents supported by AI technologies. This model was identified as the leading operational strategy for activities such as technical support, customer onboarding, complaint management, customer retention, billing, and revenue generation.
However, despite widespread AI adoption, only a minority of organizations currently utilize AI-powered quality assurance and coaching solutions. These tools help evaluate interactions, measure performance, identify improvement opportunities, and provide actionable insights for both human agents and AI systems.
Industry analysts warn that without robust performance monitoring capabilities, enterprises may struggle to understand whether their AI investments are delivering meaningful business results. The absence of automated evaluation systems can make it difficult to identify performance issues early or establish clear connections between AI deployment and customer satisfaction outcomes.
The survey also found that enterprises are pursuing a broad range of AI initiatives simultaneously. Many organizations are implementing or evaluating technologies such as AI copilots, intelligent knowledge management systems, sentiment analysis tools, predictive routing solutions, chatbots, and virtual assistants.
While investment activity remains strong, the research uncovered a noticeable gap between planned AI investments and existing operational capabilities. Several of the most sought-after AI technologies—including real-time agent assistance tools, intelligent knowledge systems, and automated quality management platforms—remain underutilized despite high future investment intentions.
Researchers suggest that these operational technologies are critical because they directly influence the effectiveness of AI-assisted customer interactions. Without them, organizations may struggle to maximize the value of customer-facing AI solutions.
The study also highlights the growing financial commitment enterprises are making toward customer experience transformation. A majority of surveyed organizations reported annual CX investments exceeding $10 million, while many indicated increasing budgets compared to previous years.
Notably, the report suggests that enterprise priorities are evolving beyond traditional efficiency metrics. Rather than focusing primarily on reducing handle times, organizations are placing greater emphasis on customer satisfaction, service consistency, and overall experience quality.
Experts believe this shift reflects a broader maturity in how businesses view AI within customer experience operations. Success is increasingly measured by improved outcomes and customer relationships rather than simple cost reduction alone.
The findings indicate that organizations seeking stronger returns from AI investments may need to focus not only on deploying customer-facing technologies but also on building the operational systems that support, measure, and continuously improve those technologies.
As AI adoption accelerates across contact centers and customer service environments, the study concludes that enterprises will need more integrated strategies that connect people, processes, technology, and performance measurement into a unified customer experience framework.
The report suggests that businesses capable of creating this balance between AI innovation and operational oversight will be better positioned to deliver consistent customer experiences while maximizing the value of their AI investments.
