Most autonomous agents stall in real-world settings because they’re built on generalized data. Enter Large Action Models (LAMs)—a new frontier in enterprise AI that trains agents with high-fidelity telemetry from your business processes, exceptions, detours, and compliance paths. The result? AI agents that act like trained employees on day one. In this session, learn how to use LAMs to close the “Agentic chasm,” reduce exception rates, enhance regulatory adherence, and fast-track ROI—powered by your enterprise’s 1st party data, along with a clear roadmap to cross the Agentic chasm and operationalize context-driven autonomy across your organization.
Check out the incredible speaker line-up to see who will be joining Xuan.
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