AI in customer experience has an orchestration problem, not an adoption problem
Every information technology leader I talk to has an artificial intelligence story about customer experience. Almost none has an outcome story. That gap is now measurable. Talkdesk Inc., in partnership with NewtonX, surveyed 252 director-level-and-above leaders in customer experience, IT, operations and AI strategy at midmarket and enterprise organizations across four regions. The resulting…
A recent survey of customer experience leaders reveals that while nearly every organization employs some form of artificial intelligence (AI) in customer experience, only a small fraction has successfully integrated agentic AI—systems capable of taking a goal, reasoning through it, and acting across multiple systems. This gap in implementation is being measured and analyzed, highlighting that the focus should shift from mere adoption to execution.
According to the benchmark, The State of Agentic Automation in CX, published by Talkdesk Inc. in partnership with NewtonX, 98% of organizations use AI in customer experience, with 74% utilizing generative AI and 65% employing scripted AI. However, only 24% utilize agentic AI, and just 15% pair agentic AI with the necessary orchestration to resolve customer needs end to end.
Pedro Andrade, vice president of AI at Talkdesk, emphasized that while 81% of organizations are piloting or deploying AI agents, only 19% have scaled beyond a single use case, and nearly 80% have fewer than 10 AI automations in production. The research identifies two key maturity curves: the agentic threshold, where 56% of companies fall short, and the CXA unlock, where 15% are Agentic Scalers with the ability to automate end-to-end journeys.
Leaders in this area report significantly higher customer satisfaction and Net Promoter Score (NPS) gains compared to their counterparts. The primary barriers to effectively automating customer experience are compliance, security, disconnected systems, legacy infrastructure, insufficient skills, and unclean or non-unified data. These challenges stem from IT's limitations, indicating that the solution lies in IT's capacity to connect systems, ground knowledge, and govern AI autonomy.
Without addressing these fragmentation issues, the potential for AI to automate customer issues autonomously within two years remains unrealized.
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