Two Types of "AI Agents" - And Why the Distinction Matters

Working on AI implementations, I keep running into confusion around the term "AI agent." Turns out we're talking about two completely different things.

Type 1: Autonomous AI Agents These are the systems getting all the buzz. An AI agent can perceive its environment, decide which tools to use, and execute actions without constant hand-holding. Think customer service bots that access your CRM, check inventory, process returns, and escalate issues - all while maintaining context and making smart decisions.

Type 2: AI-Enhanced Workflows
This is AI plugged into traditional automation platforms like Zapier, Make, Power Automate, ServiceNow, or custom solutions. The AI handles specific tasks within a larger, predictable process flow.

Real example I'm building: Staff scan shipping labels with a mobile app. AI extracts supplier info, model numbers, delivery dates, and populates our equipment database. Standard workflow automation then triggers notifications to procurement, project managers, and finance.

But here's where it gets interesting: The system also compares delivery timelines against project schedules. When procurement suggests equipment substitutions for cost savings, AI evaluates whether the new supplier's lead times will mess up critical milestones. If there's a conflict, it sends up an alert that can be acted upon.

The key difference: Workflows excel at consistent, repeatable processes. Autonomous agents shine when you need adaptive decision-making across multiple variables.

The most powerful implementations combine both - workflow automation for operational consistency, enhanced with AI agents for complex decisions.

In leveraging AI for business operations, getting this distinction right can save serious time and headaches during deployment.

What are you seeing out there? Are you building agents or workflows?