By Raj Shukla – A financial crime investigator who once received large volumes of suspicious activity alerts requiring tedious investigation work manually gathering data across systems in order to weed out false positives and draft Suspicious Activity Reports (SARs) on the others. Today, she receives prioritized alerts with automated research and suggested content that can generate SARs in minutes.

A retail category planner who previously did hours-long analysis of past weeks’ reports to try to uncover insights into which products are underperforming, and why, now uses AI to provide deep-dive insights that surface problem areas and suggest corrective actions, prioritized for maximum business impact. An industrial maintenance engineer uses a copilot that conducts 24/7 asset health monitoring and predicts issues and generates warning at the early stages of mechanical or performance problems, slashing unplanned downtime.

These transformations are happening across enterprises today, signaling a fundamental shift: vertical applications combining predictive, generative, and emerging agentic AI are augmenting and transforming workflow automation, providing targeted, sophisticated capabilities that address far more complex and contextual challenges than earlier solutions.

Gartner’s 2024 Hype Cycle for Emerging Technologies highlighted autonomous AI as one of the year’s top four emerging technology trends—and with good reason. With non-AI agents, users had to define what they had to automate and how to do it in great detail. But applications combining predictive, generative, and soon agentic AI with specialized vertical knowledge sources and workflows can pull information from disparate sources enterprise-wide, speed and automate repetitive tasks, and make recommendations for high-impact actions. Enterprises using these applications realize faster and more accurate decision-making, rapid problem identification and remediation, and even preventive measures to stop problems from occurring in the first place.

AI agents represent the next wave in enterprise AI. They build upon the foundations of predictive and generative AI but take a significant leap forward in terms of autonomy and adaptability. AI agents are not just tools for analysis or content generation—they are intelligent systems capable of independent decision-making, problem-solving, and continuous learning. This progression marks a shift from AI as a support tool to AI as an active participant in business processes, capable of initiating actions and adapting strategies in real time.    Read On: