Ask AI a question and getting a good answer is useful. But businesses usually have another problem: somebody still has to do something with that answer.

An invoice may need to be entered into a database. A customer request may need to be classified and routed. A document may need to be renamed, filed, summarized and sent for approval.

This is where AI Workflow Automation becomes interesting. Instead of stopping at an answer, AI can become one step inside a larger process:

• A document arrives.
• Document AI reads and extracts the information.
• Generative AI interprets or summarizes it.
• Business rules validate the result.
• The workflow updates a database or application.
• A person is notified only when review is required.

This direction is already becoming important. McKinsey's 2025 survey found that 62% of respondents said their organizations were at least experimenting with AI agents, systems capable of planning or performing multiple steps rather than simply generating content.

Agentic AI can take this further by adding reasoning and decision-making where a fixed workflow is not enough.

For businesses, the important question may therefore be changing from “What can AI tell us?” to “What work can AI help us complete?”