How Large Action Models are reshaping CX

Despite years of artificial intelligence (AI) investment, most customer experiences still remain fragmented, reactive and heavily dependent on disconnected systems behind the scenes.

While 88% of businesses now use AI in at least one function, nearly two-thirds remain stuck in pilot phases, according to McKinsey, highlighting the gap between AI adoption and meaningful operational transformation.

Large Language Models (LLMs) have helped businesses create more responsive and personalized interactions, but many organizations are beginning to recognize that conversational AI alone is not enough. As organizations increasingly compete in the experience economy, the focus is shifting toward technologies capable of coordinating actions, workflows and decisions across the entire journey in real time.

That shift is helping drive a new era of agentic customer experience orchestration, where AI systems can move beyond simply responding to requests and instead help execute tasks, resolve issues and coordinate outcomes autonomously across the enterprise.

Large Action Models (LAMs) are emerging as a key part of that transition, helping organizations move beyond conversational intelligence to real-time operational execution.

Moving AI beyond conversation

That shift matters because it fundamentally changes what AI tools can deliver within customer experience.

LLMs brought conversational intelligence into the enterprise, helping AI understand intent and generate more natural interactions. LAMs build on that foundation by turning intent into action: determining the next best steps and executing multi-step workflows in real time, within enterprise-defined guardrails.

Importantly, the rise of LAMs does not signal the end of LLMs. The two technologies work side by side. LLMs remain critical for conversational understanding and contextual reasoning, while LAMs connect that intelligence to coordinated action. This moves AI beyond simply responding to requests, toward orchestrating outcomes…