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When infrastructure learns: The rise of the AI-native core

Voice and Data

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December 2025

AI-native infrastructure is moving from concept to operational reality, reshaping how organisations build, govern, and scale intelligence across their digital core.

- BY SHUBHENDU PARTH

When infrastructure learns: The rise of the AI-native core

Imagine this: It is early 2026, and a bank in Mumbai launches a new lending product overnight. No marathon development cycles. No months of approvals. Instead, an agentic AI system, threaded across a sovereign cloud, core banking engines, and compliance models, interprets regulations, designs workflows, assesses risk, drafts documentation, and prepares a complete rollout plan before dawn.

Nearly 1,300 Km away, in Delhi, a major hospital is undergoing a similar shift. Clinical monitors and emergency devices begin streaming anomalies into a central AI hub. Before doctors arrive for morning rounds, the system has already prioritised cases, checked insurance eligibility, suggested treatment pathways, and coordinated beds and lab workflows.

While the two organisations represent contrasting worlds, what ties them together is the potential of AI-native infrastructure to transform business operations. Work once scattered across analysts, coders, and coordinators could soon be handled by reasoning agents that instantly grasp data, rules, and intent. Decisions may flow through a unified digital spine—an organism-like backbone capable of reshaping how institutions think, act, and respond.

These scenarios might feel extraordinary today, yet they echo a reality that is fast taking shape across the technology landscape. They were well-painted and discussed by major tech companies—from AWS, HPE, and NetSuite, to Oracle, SAP, Salesforce, and Snowflake— at their annual tech events during the OND quarter. Seen separately, each update feels incremental. But together, they point to a deeper change: the world is no longer adapting AI to existing IT systems—it is rebuilding those systems to be AI-native.

Three shifts capture this transition: infrastructure engineered for intelligence, data platforms purpose-built for AI reasoning, and enterprise software evolving into ecosystems of autonomous agents.

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