Bringing predictive analytics to the agentic AI era

In 2026, the focus of enterprise AI has shifted from whether predictive models can outperform traditional statistical forecasts to how these models can make autonomous decisions without straying from business goals.

This marks a transition from predictive analytics—which involves forecasting future trends based on historical data—to agentic AI, where AI systems not only predict outcomes but also take actions independently.

The gap between leading and lagging organizations in adopting this technology is widening, as those who fail to adapt risk falling behind in efficiency and innovation.

According to Vishal Gupta, a partner at research firm Everest Group, businesses are moving away from a backward-looking approach to one that prioritizes forward-thinking strategies.