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Data Infrastructure: Key to AI Agent Success in 2026
AI Agents

Data Infrastructure: Key to AI Agent Success in 2026

Source: Technologyreview Original Author: MIT Technology Review Insights 1 min read Intelligence Analysis by Gemini

Sonic Intelligence

00:00 / 00:00
Signal Summary

Strong data infrastructure is critical for scaling AI agents, as their effectiveness depends on the quality and context of the data they access.

Explain Like I'm Five

"Imagine you're teaching a robot to help you. If you give it messy, confusing information, it won't be able to help much. But if you give it clear, organized information, it can be a super helper!"

Original Reporting
Technologyreview

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Deep Intelligence Analysis

The article emphasizes the importance of a robust data infrastructure for the successful implementation and scaling of AI agents. While many companies are experimenting with AI agents, only a small fraction have managed to scale them effectively. A key reason for this is the lack of adequate data architectures that can provide the necessary business context to AI models. Irfan Khan from SAP Data & Analytics stresses that the capabilities of agentic AI are increasingly determined by the soundness of enterprise data architecture and governance, rather than solely by the evolution of the models themselves. The focus should be on delivering business context along with the data, rather than simply accumulating large volumes of data. Overcoming the lack of trust in data requires shared definitions, semantic consistency, and reliable operational context to align data with business meaning. By adopting a modern, business-aware data infrastructure, companies can unlock the full potential of AI agents and achieve better business outcomes.
AI-assisted intelligence report · EU AI Act Art. 50 compliant

Impact Assessment

Many companies face challenges scaling AI agents due to inadequate data architectures. Focusing on business context within data is more crucial than simply accumulating large volumes of data.

Key Details

  • McKinsey reported that nearly two-thirds of companies were experimenting with AI agents in late 2025.
  • 88% of companies were using AI in at least one business function in 2025, up from 78% in 2024.
  • Only one in 10 companies have successfully scaled their AI agents.

Optimistic Outlook

By adopting a modern, business-aware data infrastructure, companies can unlock the full potential of AI agents. This will lead to more efficient operations and better business outcomes.

Pessimistic Outlook

Without a strong data foundation, AI agent deployments will likely fail to scale, leading to wasted investments and unrealized potential. Lack of trust in data can further hinder AI adoption.

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