CData's Vision for AI Connectivity: Validated by Analysts, Driven by Customer Needs

AI adoption is increasingly constrained by data infrastructure rather than models or computing capacity, with a CData survey reporting that only 6% of AI leaders consider their infrastructure AI-ready. The passage argues that effective enterprise AI requires real-time data access, governance, and semantic context, and identifies the Model Context Protocol (MCP) as an emerging standard for enabling secure communication between AI models and enterprise systems. It also describes a need for AI-native data pipelines that support automation, natural-language document workflows, validation, monitoring, governance, and collaboration across business and technical users. CData presents its Connect AI managed MCP service, integrations with platforms such as Agent Bricks and Microsoft Copilot, and Vibe Querying natural-language data exploration as tools intended to help organizations discover AI use cases and operationalize them. Looking toward 2026, the passage emphasizes growing governance requirements, trust, and evolving developer tools as central considerations for deploying AI at scale.

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