Getting Started with AI

AI vs Automation: What's the Difference?

Differences between AI and traditional automation. When to use each.

AI and automation are different things. Often confused. Different deployment patterns.

Traditional automation (RPA)

Rule-based. Predictable. Brittle to changes. Best for stable, structured processes.

Pattern-based. Adaptive. Handles unstructured data. Best for variable, knowledge work.

Modern automation often combines RPA with AI. AI for understanding; RPA for action.

Different tools for different work. Choose appropriately or combine.

Different paradigm. Automation follows rules; AI recognizes patterns. Different deployment, different use cases, often combined.

Stable, structured, rule-based processes. Predictable inputs and outputs. Cost-effective at scale.

Unstructured data, judgment required, variable inputs. Document processing, customer service, knowledge work.

Generally augment rather than replace. RPA still cost-effective for rule-based. AI for unstructured. Combination common.

RPA simpler, more predictable, lower cost. AI more flexible, more powerful, higher complexity. Different skills.

Prometheus does onsite AI consulting and implementation in Milwaukee. We set it up, train your team, and make sure it works.