Expedia Group is among the companies experimenting with “agentic AI” – autonomous systems capable of planning, reasoning, and acting to complete tasks with minimal human oversight, according to Harvard Business School Professor Tsedal Neeley.
The shift towards agentic AI represents a move beyond generative AI’s current capabilities, such as summarizing data or drafting documents. While generative AI assists with specific tasks, agentic AI can carry out entire workflows independently. “People talking about using AI to write an email or draft a document is just the starting point—what we’re doing is taking it to a higher order,” said Ritcha Ranjan, Expedia’s senior vice president of product, in a recent discussion with Neeley.
A McKinsey survey revealed that 39 percent of organizations have begun experimenting with AI agents, with the majority having applied AI to at least one function. This growing interest stems from the potential for agentic AI to dramatically improve work, relationships, and collaborations, according to Neeley. She stated, “I can’t see a future without every individual using AI to dramatically improve their work, their relationships, and their collaborations.”
Genpact identifies agentic AI as the convergence of process and data journeys within enterprises. The “process journey” has evolved through methodologies like Lean Sigma Six, robotic process automation (RPA), and digital workflows, focused on efficiency and scale. Simultaneously, the “data journey” has progressed from traditional business intelligence to machine learning and generative AI. Agentic AI emerges when these paths converge, enabling agents to understand data and act within systems for greater automation.
According to Genpact research, 96% of enterprise IT leaders plan to increase their use of agents in the next 12 months. But, organizations often struggle with identifying where and how to begin scaling agentic AI initiatives. Technical leaders are advised to view agentic workflows as a fusion of decision-making and execution, embedding analytical intelligence directly into workflows to achieve greater efficiency.
The concept of an “agentic enterprise” is described as analogous to a busy international airport, where AI agents function like airplanes, each tasked with an assignment and acting independently to reach their destination while the overall system remains operational. This requires a layer of enterprise-wide intelligence to allow autonomous agents to close the loop between knowing and doing, according to Genpact.
McKinsey advises business leaders to assess task demands before implementing agentic AI solutions.
