You will often hear talk about workflows and automation in the context of AI. This article gives a simple explanation of what these terms mean and how they fit into the changing technological and business landscape.
The shortest explanation is that you use computers to set up triggers in your business process. So the computer keeps things moving without a person having to evaluate the situation or press a button, promoting efficiency and saving time and money.
Read time: 3 min.
Workflow Use Case & Description
The World Economic Forum quotes Hala Zeine, SVP and Chief Strategy Officer at ServiceNow - "At ServiceNow, we are built for exactly this moment. AI isn't bolted onto our platform – it's native to the infrastructure that already orchestrates 80 billion workflows and 6.5 trillion transactions annually for 85% of the Fortune 500."
According to ServiceNow, efficient business operations rely on a hierarchy of work: individual tasks form processes, which scale into workflows involving multiple people and systems. However, manual workflows are often slow and error-prone. To save time and reduce the likelihood of errors, organizations use automation to streamline these complex interdependencies.
Traditional vs Agentic
Traditional Automation:
According to IBM, workflow automation focuses on optimizing business and IT operations by replacing manual tasks with software driven by rule-based logic. These systems utilize user-friendly, low-code interfaces and drag-and-drop features to streamline processes without requiring complex programming. By substituting human effort with automated execution, organizations can significantly increase speed, reduce errors, and foster better communication. Ultimately, these logic-based programs are highly effective at resolving process inefficiencies and enhancing team collaboration through structured, predictable execution.
Agentic Automation:
Unlike the rule-based logic of traditional automation, agentic workflows use autonomous AI agents to reason, plan, and adapt to real-time data. By breaking complex problems into iterative steps and utilizing specialized tools (APIs, web searches, and multi-agent collaboration), these workflows handle unpredictable conditions with minimal human oversight. This shift from "if-then" logic to dynamic, self-correcting systems improves operational efficiency and generates high-quality data for training future AI models.
For the Workforce:
Employees:
Ask what in your job could be replaced by automation and how you can rebalance your agency within the company to optimize the business process. i.e., Ask yourself, "How can I remain relevant and employed in this company as technology advances?"
Employers & Managers:
Consider making your organization a safe space for people to try new things. Early adoption of new technologies can provide the cutting edge your business needs to excel beyond your competitors. Find new ways to use the people you have in your organization, because new systems will still require humans in the loop to set guardrails and monitor systems. Artificial intelligence can do powerful things, but it's still artificial and will never be as capable in many areas as the people on your payroll.
For Further Reading
World Economic Forum, "Where is AI moving beyond experimentation? 6 leaders on what's actually scaling" World Economic Forum, Mar. 2026. [Online]. Available: https://www.weforum.org/stories/2026/03/where-is-ai-moving-beyond-experimentation-leaders-scaling/
ServiceNow, "What is workflow automation?" ServiceNow. [Online]. Available: https://www.servicenow.com/platform/what-is-workflow-automation.html
IBM, "What is workflow automation?" IBM. [Online]. Available: https://www.ibm.com/think/topics/workflow-automation
C. Stryker and A. Gutowska, "What are agentic workflows?" IBM. [Online]. Available: https://www.ibm.com/think/topics/agentic-workflows