What it takes to move enterprise AI beyond the chatbot

By now, most enterprise executives have heard plenty of generic claims that AI will transform the way work gets done.

But in many cases, their initial AI investments haven’t delivered the level of transformation they were promised.

An LLM can summarize information, answer questions, and suggest next steps.

But on its own, it can’t take action on that information.

In fact, without connections to key business systems, an LLM is essentially a chatbot with a polished writing style.

Consider a finance team processing invoices.

An isolated LLM might accurately summarize a supplier invoice.

But it can’t match the invoice to a PO, determine whether it’s been paid, or see if it’s coded to the correct GL account.

It needs more information to make those decisions, and that information exists outside of the AI tool.

For AI to take an active role in business processes, it needs access to the systems where context lives.

The Model Context Protocol (MCP) can provide the infrastructure for secure connections.

This shift is already taking shape in accounts payable.

What MCP actually changes The impact of an LLM depends on what it has access to.

If the information it needs to make a reliable decision lives in an ERP , vendor database , or other business system, the model needs a way to access it.