CHICAGO — The next major phase of artificial intelligence may not be about better chatbots.
It may be about AI agents capable of completing entire sequences of business tasks with limited human intervention.
American companies are increasingly testing these systems in finance, customer service, software development and operations.
From Answering Questions to Taking Action
Traditional generative AI responds to instructions.
Agentic AI is designed to do more.
An AI agent can potentially analyze information, decide what needs to happen next, use software tools and complete a multi-step task.
In financial services, that could mean automatically reviewing transactions, identifying suspicious activity and preparing documentation for human approval.
In corporate operations, an agent could monitor inventory and place orders when supplies fall below a predetermined level.
Software companies are building platforms designed to connect these agents to existing business applications.
That creates a potentially enormous market.
Businesses already spend billions of dollars on software subscriptions.
If AI agents can automate portions of that work, companies may be willing to pay for systems that deliver measurable productivity gains.
But autonomy creates new risks.
A human employee can be held responsible for a mistake.
An AI agent may make thousands of decisions before anyone notices a problem.
Companies therefore need permission systems, audit trails and human review.
Cybersecurity is another concern.
An AI agent with access to corporate systems could become a powerful target for hackers.
The technology also raises employment questions.
If agents perform administrative tasks previously handled by large teams, businesses may eventually need fewer workers in certain roles.
The transformation is unlikely to happen overnight.
Most companies will initially use AI agents for narrow, repetitive tasks.
But if reliability improves, the systems could gradually move into more important decisions.
That could make agentic AI one of the most consequential changes in enterprise software since the rise of cloud computing.
.webp)
