Bringing predictive analytics to the agentic AI era
In 2026, the question for enterprise AI is no longer whether predictive models can outperform statistical forecasts—that argument is settled.
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Key points
- The big question now is how to enable predictive systems to act on their own conclusions without drifting from business intent.
- Intelligent analytics, powered by technologies like deep learning and generative AI, are making this possible.
- As a result, AI-powered analytics are moving enterprises from passive hindsight to pragmatic foresight.
- AI takes predictive analytics—a broad discipline that includes predictive modeling, data prep, analysis workflows, interpretation of results, and decision-making applications—to new heights. “In many ways I think the word ‘analytics’ is giving way to AI,” says Gupta. “Everything is becoming AI.”
Sources (1)
- [1]Bringing predictive analytics to the agentic AI eraMIT Technology Review (AI) · Oct 5, 01:29 PM
In 2026, the question for enterprise AI is no longer whether predictive models can outperform statistical forecasts—that argument is settled.
The big question now is how to enable predictive systems to act on their own conclusions without drifting from business intent.
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