Where is agentic AI heading over the next two to three...

A few directions are visible enough now to bet on, and they share a common thread rather than being unrelated trends:

• Agent-to-agent delegation — instead of one generalist trying to do everything, specialized agents hire each other for sub-tasks through a shared protocol, closer to how a freelance marketplace works than a monolithic assistant.
• Proactive rather than purely reactive operation — agents that monitor an environment and act on their own initiative rather than waiting to be asked, surfacing a problem already diagnosed and often already fixed rather than waiting for someone to notice it.
• Deeper specialization — general-purpose agents giving ground to narrow domain experts trained on far more specific data than a general model ever sees, the same way a specialist consistently outperforms a generalist on their home turf.
• Multimodal, interface-level operation — agents that interact with software the way a person does, by looking at a screen and clicking through it, rather than requiring a bespoke API for every application they need to touch.

The throughline across all of them is less human initiation required per unit of useful work — which is exactly why the earlier reliability and oversight questions don’t go away as this plays out; they get more important, since more autonomy and less human framing of each task raises the cost of the agent getting it wrong.