AI is poised to evolve from simple tools into agents that can operate computers directly, enabling fully AI-enabled companies where AI systems actively participate in how work gets done.

The gap between AI capabilities and enterprise readiness is widening, driven more by governance, security, and data-access questions than by the technology itself.

Delays in organizational readiness for AI adoption could cost competitive ground, as AI-enabled co-workers become essential for maintaining parity or advantage.

AI progress is linked to broader economic and infrastructural impacts, with the potential for rapid growth if new services and scientific discoveries emerge within AI-enabled ecosystems.

The shift to agents requires new interaction paradigms where machines exchange information and coordinate tasks, reducing the need for humans to micromanage AI workflows.

Leaders stress the urgency of redesigning enterprises to absorb AI tools quickly, avoiding prolonged internal friction and access debates.

Security and data access—not technical capability—are the main constraints, with current systems ill-suited for always-on AI agents that observe and act across ecosystems.

Agents will move beyond drafting outputs to end-to-end task execution, navigating browsers, applications, and authenticated environments, enabling new interaction models where AI agents coordinate on behalf of humans.