Agentic AI marks a new phase of automation – but only if systems are implemented with proper governance.
As AI adoption enters its next phase, businesses are looking beyond copilots and conversational assistants toward a more transformative concept: agentic AI. These autonomous systems don’t just respond but proactively complete tasks according to changing variables. They can plan, reason, and execute tasks across multiple applications and data sources, taking AI from assistant to autonomous collaborator.
Yet amid all the excitement, the mood in the industry is mixed. Some leaders see agentic AI as the dawn of true digital autonomy, while others urge caution, warning that the road from demonstration to dependable enterprise deployment is longer than it looks.
“Optimism is driven by agentic AI’s proactive capabilities,” says Tolga Kurtoglu, chief technology officer at Lenovo. “We’re seeing agents that can complete multi-step tasks, understand user intent, and orchestrate across systems. That’s a leap beyond generative AI. But skepticism is natural – integrating multiple data sources while maintaining governance is complex, and failure rates remain high.”
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