More than one in 10 enterprises to be AI-first by 2030, Gartner predicts

Sovereign AI and agentic data streaming top the analyst firm's data and analytics trends for the next two years.

More than one in 10 enterprises will operate as AI-first businesses by 2030, outperforming competitors through their use of AI agents and converged data and analytics (D&A) platforms, according to Gartner. The analyst firm names these shifts, along with the spread of semantic technologies, as the forces shaping its top data and analytics trends for 2026.

"Organizations are moving rapidly toward an AI-first operating model, where AI is now a core consideration in every business decision, workflow and investment," said Carlie Idoine, VP Analyst at Gartner. She warned that without a clear, enterprise-wide commitment, organisations will struggle to realize that potential consistently across the business.

Solution providers and integrators can read the forecast as a guide to where customer demand is likely to concentrate. Gartner groups its guidance into six trends it recommends D&A leaders build into strategy over the next two years.

Sovereign AI tops the data and analytics agenda

As AI becomes central to economic strength, nation states are prioritising control over their own AI capabilities and reducing reliance on foreign providers, Gartner said. Localising D&A control sits at the heart of that effort, and the firm frames sovereign AI as an external geopolitical reality that organizations must factor into their roadmaps.

"Sovereign AI is fundamentally changing how organizations think about control, innovation and resilience in their AI strategies," Idoine said. Governance features heavily in the remaining priorities. Gartner argues that as AI agents take on more strategic and operational decisions, ungoverned decision-making raises legal and operational risk.

It recommends decision governance, which applies governance principles to automated decisions so they remain explainable and auditable. The firm predicts that explicitly modelled business decisions will be five times more trusted and 80% faster than ungoverned ones by 2029, as decision intelligence platforms gain ground.

Gartner also points to AI governance platforms as a way to keep pace with rising regulatory complexity and the spread of autonomous agents. Such platforms give D&A leaders centralised oversight and let them enforce controls against corporate policy and regulation, the firm said.

Agentic data streaming and management gather pace

Agentic data streaming is emerging as a priority for organisations building AI agents, Gartner said, because traditional batch processing is often too slow for them. Continuous, event-driven data flow lets teams deliver data faster and frees agents to take on more tasks. The firm predicts adoption of data streaming for agentic AI will pass 60% by 2028, up from under 15% in 2025, driven by pressure for real-time responsiveness.

Closely related, Gartner highlights agentic data management, where AI agents handle core data processes such as pattern detection and real-time recommendations. "Integrating AI agents into data management workflows enables data teams to operate more adaptively using self-learning systems," Idoine said, adding that strong governance and continuous monitoring will be essential to keep results business-aligned.

GraphRAG for complex queries

The final trend is about getting AI answers right. Most AI tools today rely on a method called retrieval-augmented generation, or RAG, which lets a model pull in outside information instead of leaning only on what it learned during training. The catch is that RAG tends to stumble on complicated questions that hinge on how separate pieces of information connect.

GraphRAG tackles this by adding knowledge graphs, which map how facts relate to one another, so the AI can follow those links and answer more reliably. Gartner predicts 40% of enterprises will use GraphRAG techniques by 2029 to make their AI more accurate and better at reasoning.