A new global study from Five9 reveals that 92% of organizations have implemented or piloted AI use cases in customer service, yet two-thirds of consumers still prefer speaking with a human agent. The 2026 Business Leaders Customer Experience Report, based on surveys of 3,000 consumers and 600 decision-makers in the U.S., U.K., and Germany, shows that while AI adoption is delivering measurable returns, customer trust depends on transparency, choice, and smooth human handoffs.
The findings come as AI moves from experimentation to execution in contact centers. 80% of consumers are willing to use AI-powered customer service, but 71% consider it very or extremely important to know when they are interacting with an AI agent. Phone remains the most preferred channel overall, with preference rising sharply with age - from 23% of Gen Z consumers to 66% of the Silent Generation. The rapid uptake signals that AI for Customer Support is now mainstream, but organizations face a new set of challenges in making those interactions trustworthy.
The AI-to-human handoff is make-or-break
Nearly all decision-makers say their organization preserves context during AI-to-human handoffs, but 83% of consumers report having to repeat themselves at least sometimes after a transfer. This gap raises questions about whether organizations are measuring handoff success accurately.
"Winning with AI in customer experience will come down to more than automating interactions at scale," said Amit Mathradas, CEO of Five9. "It requires making every experience more relevant, more trusted and more human - giving customers choice, equipping agents for higher-value work, preserving context across every handoff and building AI strategies that can scale responsibly across the business."
Infrastructure gaps slow AI maturity
84% of organizations are still transitioning from on-premises infrastructure to cloud-based systems. AI execution depends on the underlying data, workflows, and system architecture, and many contact centers are still in the midst of that migration.
No one-size-fits-all AI playbook
Decision-makers are split between end-to-end platforms, hybrid approaches, and best-of-breed tools. The report reinforces the need for flexible AI strategies that align models, workflows, governance, and human oversight to each use case.
Why this matters for customer support professionals
For customer support professionals, the report underscores that AI success is not just about deployment. It requires building trust through transparent AI interactions, reliable handoffs, and agent empowerment. As AI handles more routine tasks, agents will need to focus on complex, high-value work. Supervisors, in turn, must develop skills in AI orchestration and handoff management. Resources like the AI Learning Path for Call Center Supervisors can help build these capabilities. With consumer preference for human agents remaining strong, the human element stays at the core of effective customer experience.
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