Why Intelligent Data Platforms Will Power Enterprise AI in 2026

Enterprise AI adoption is accelerating, but the next competitive battleground is shifting to the data layer. While large language models and AI agents dominate headlines, many technology leaders argue that long-term advantage will depend on how enterprise data platforms evolve. According to Oracle’s Tirthankar Lahiri, 2026 could mark a turning point for intelligent data infrastructure as organizations begin vectorising enterprise data at scale. 

Vectors (mathematical representations that capture the meaning and relationships of data) already widely used in natural language processing and image recognition. Lahiri believes the next phase will extend vectorisation into enterprise systems such as banking platforms, billing environments, and operational databases. Instead of relying on standalone vector databases, he expects native vector capabilities to be embedded directly into enterprise data platforms. This approach would allow existing applications to become AI-enabled without moving data into separate systems. 

The shift also requires databases to evolve from traditional “systems of record” into “systems of intelligence.” That transition depends on two capabilities: native vector support and explainable enterprise data. Many enterprise schemas today are cryptic machine-generated structures. To support AI, organizations must annotate and contextualize their data so that both humans and machines can understand its meaning. 

Another major change involves architecture. Lahiri argues that fragmented stacks connected through orchestration layers will struggle to support enterprise-scale AI. Instead, organizations should move toward converged data architectures that combine object storage, open table formats, and unified governance policies. Multiple repositories may still exist, but they must manage through a centralized view of enterprise data. 

Data fragmentation remains one of the biggest hidden risks. Many large enterprises still lack visibility into where data resides across departments and systems. As AI agents begin operating directly on enterprise datasets, governance and security must embed directly into the database layer to prevent misuse. 

The message for enterprise leaders is clear: the future of AI depends as much on intelligent data platforms as on model innovation. 

Source: 

https://www.itnews.asia/news/vectorising-the-enterprise-why-2026-is-year-of-intelligent-data-platforms-624060