A new global benchmark by Fivetran, the data foundation for AI, titled “The 2026 agentic AI readiness index,” indicates that only 15% of organizations are fully prepared to support agentic AI workloads in production. This finding emerges even as nearly 60% of surveyed enterprises report investing millions to tens of millions in the technology.
Based on a survey of 400 data professionals across the United States, United Kingdom, EMEA, and Asia-Pacific, the index evaluates organizations on core data requirements for reliable agentic AI operation, including data freshness, lineage, governance, and interoperability. Agentic AI systems are designed to plan, act, and execute across business workflows, which increases both the value and risk of AI adoption. As these systems move into production, deficiencies in data quality, governance, and interoperability can transition from minor issues to operational failures, thereby limiting the safe and scalable automation potential of AI.
George Fraser, CEO of Fivetran, stated that most companies’ AI initiatives falter not due to the models themselves, but because their underlying data is not prepared. He highlighted that organizations deploying agentic AI in production on fragile pipelines, with missing lineage, and systems not designed for autonomy risk faster failures instead of improved outcomes.
The report’s key findings reveal that 41% of organizations are already utilizing agentic AI in production, despite notable gaps in data reliability, governance, and interoperability. The primary obstacles to achieving agentic AI goals include data quality and lineage (cited by 42% of respondents), regulatory compliance and sovereignty (39%), and security and privacy risk (39%). Interoperability is considered important or critical by 86% of data leaders, with 17% deeming it critical for AI and data decisions, yet many organizations face limitations from fragmented systems and vendor lock-in, with data integration platforms identified as the single largest source of this risk.
These findings align with a broader industry trend where, as AI systems become more autonomous, data infrastructure increasingly becomes the limiting factor. Gartner research suggests that up to 60% of AI projects may be abandoned due to insufficient AI-ready data.
The Agentic AI Readiness Index, which forms a composite score, measures the preparedness of an organization’s data foundation across dimensions such as data freshness, lineage, governance, and interoperability. The average readiness score among respondents is approximately 61–62%, indicating that most organizations need to address critical gaps to realize a return on their AI investments. Organizations categorized as fully prepared demonstrate a distinct advantage in both confidence and operational efficiency. These teams are more inclined to implement always-on, automated data pipelines for fresh and reliable information, enforce end-to-end lineage and governance for trust and compliance, and standardize on interoperable architectures to facilitate data flow across their infrastructure. Consequently, they are better positioned to deploy agentic AI broadly across internal workflows and customer-facing products, and exhibit significantly higher confidence in achieving meaningful ROI from their AI investments.
To establish a foundation for agentic AI, the report outlines four core requirements: fresh, reliable data delivered through automated pipelines; transparent lineage for data creation and transformation tracking; strong governance controls for security and compliance; and open interoperability across systems to prevent lock-in and enable flexibility. These capabilities collectively form the baseline for an AI-ready data foundation, enabling organizations to scale agentic AI while maintaining control over cost, risk, and performance.
Fivetran, the data foundation for AI, provides a platform that moves, manages, and transforms data from various business systems into a secure and reliable foundation. This platform is engineered for evolution and offers flexibility across clouds, engines, and tools. Organizations globally, including OpenAI, LVMH, Pfizer, and Verizon, utilize Fivetran to leverage data as a competitive advantage. The methodology for the 2026 Agentic AI Readiness Index was based on a survey conducted by Redpoint Ventures of 400 data professionals in mid-sized and large enterprises, focusing on organizations with at least 2,000 employees in the U.
S. and EMEA, and 500 or more in Japan, Australia, and Singapore, across data-intensive industries such as technology, financial services, healthcare, retail, and manufacturing.
