From Conversation-Centric to Agent-Centric AI Models

Enterprises are integrating AI into their operations and develop agent pilots. As we deploy more capable agent-based intelligent applications, including multi-agent systems, we will utilize agent-centric models for planning, reasoning, coordinating, and learning. Such agents will incorporate neurosymbolic components and agent-centric models (LRM, LAM). They will communicate using specialized languages and appropriate communication protocols.

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Preparing the AI-First Enterprise Workforce for the Age of Agents

As AI agents become more capable, how should the roles and responsibilities of the AI-first enterprise employees evolve? Which skills will matter at each level, and how will technical and business teams collaborate to effectively leverage agents and agent-based systems? As the capabilities of agents advance, employees will move from executing tasks to supervising workflows, orchestrating agent collectives, and, ultimately, setting mission-level strategy. Preparing for this transformation requires a clear view of how roles evolve across the six levels of AI agents, and how responsibilities will shift among AI specialists, application users, and supporting teams.

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