Agentic AI: Eliminating Operational Friction, Not People

Enterprises are struggling to automate work despite massive AI investments. Many business processes remain slow. Here's the thing: current AI systems can retrieve records and analyze data, but this information doesn't move work forward on its own. Critical processes still rely on manual decisions and handoffs across people and systems. What's interesting is that the focus is shifting from static AI to agentic AI. Traditional automation tools like RPA and BPM work well for predictable tasks, but they struggle with unexpected situations. For example, commercial underwriting often stalls due to manual reviews across disconnected applications. Customer onboarding can be complicated by incomplete documentation, and supply chain disruptions require real-time problem-solving beyond fixed scripts. The bottom line is that agentic AI is designed to bridge this gap. It moves beyond rigid rules to handle context-driven coordination, allowing systems to actively participate in getting work done, rather than just answering questions. This could significantly reduce operational friction for businesses.