AI Workflow Automation
AI workflow automation is the use of AI models or agents to carry out or support steps in a business process, including steps that involve reading documents, interpreting requests, or making judgment calls.
Traditional automation, including robotic process automation (RPA), follows fixed rules and works best with structured data and predictable steps. AI extends automation to work that used to need a person, such as classifying requests, extracting details from documents, drafting responses, and routing exceptions. Some workflows add a single AI step to an otherwise rule-based process. Others use AI agents that decide which steps to take.
A common mistake is adding AI to an existing process without questioning the process itself. A more useful question is how the workflow would be designed if AI had been available from the start. Because AI outputs can vary, sound automation also includes human review for high-risk steps, clear escalation paths, and measures of quality, not only speed. Good first candidates tend to be high-volume, repetitive workflows where results are easy to check.
Examples
Document intake. Extracting data from invoices, contracts, or applications.
Support triage. Classifying incoming tickets and routing them to the right team.
Approval routing. Gathering the details a reviewer needs and flagging requests that break the rules.
Recurring reports. Pulling data from several systems and summarizing it.
Exception handling. Drafting a proposed fix for an unusual case so a person can approve it.
