Under what conditions will #AI have a lasting impact on the #enterprise? This is a fundamental strategic question for enterprise leaders. Approaching it as a utility would imply that the bulk of the investments will be borne by others. But this could impact how enterprises scale their AI efforts. Approaching it as infrastructure impacts what the enterprise builds.
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.
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.
The global robotaxi industry has entered a new era, one defined by the tangible formation of new value chains. The…
In the first three parts of this series, we achieved three objectives. We described the characteristics of the AI-first company.…