Agentic AI Is Here—Now What?

The Rise of Task-Smashing Machines

Agentic AI, a new wave of autonomous systems capable of executing complex tasks with minimal human oversight, is entering a pivotal moment. Moving beyond simple prompt-response models, agentic systems can plan, adapt, and even collaborate with one another in solving problems. Enterprises are already testing such tools to automate workflows, summarize documents at scale, and provide continuous background services. With giants like Microsoft integrating agentic behaviors into Copilot, the shift is poised to redefine digital work.

The Cost Behind the Autonomy

Despite their promise, agentic AIs come with a steep price tag—both financially and computationally. Performing multistep tasks requires chaining several large model operations, significantly increasing cloud API costs and energy consumption. Additionally, latency concerns emerge as agents take longer to process tasks compared to traditional AI queries. As organizations experiment with these systems, evaluating cost scalability and return on investment becomes mission-critical.

What’s at Stake for the Future

The proliferation of agentic AI stands to reshape entire professions, workflows, and even the internet’s structure. Yet, it also introduces serious risks: unreliable agents, unpredictable behavior, and ethical concerns around autonomy. Who’s held accountable when AI “decides” something independently? As the technology accelerates, experts call for better governance frameworks and transparency from both vendors and users to mitigate unintended consequences.