Agentic AI vs. Traditional Automation
Agentic AI is AI that perceives its environment, reasons about the situation, decides on an action, and executes it autonomously. Traditional automation follows pre-defined rules without reasoning. The distinction is between systems that react to triggers and systems that reason about context before acting.
Why It Matters
This distinction matters because enterprise buyers are evaluating both approaches simultaneously. RPA vendors are adding AI labels. Workflow platforms are calling themselves 'agentic.' Understanding the structural difference (reasoning + network intelligence vs. rule-following) is essential for making platform decisions that compound rather than plateau.
The FourKites Perspective
FourKites Digital Workers are agentic: they perceive exceptions through the Digital Twins, reason using the Graph's cross-company intelligence (not just rules), decide on resolution paths based on outcome data from thousands of prior situations, and execute across communication channels. Traditional automation in supply chain follows static if-then logic that does not adapt when carrier patterns shift, facility rules change, or new disruption types emerge.