6 Nov: Gartner® Report: A Journey Guide to Deliver AI Success Through AI-Ready Data

Build the data foundation your AI needs to deliver real outcomes

AI is moving fast, but most initiatives stall when the data is not ready. According to Gartner, “through 2026, organizations that don’t enable and support their AI use cases through an AI-ready data practice will see over 60% of AI projects fail to deliver on business SLAs and be abandoned.”

This Gartner Journey Guide gives data and analytics leaders a practical path to make data clean, governed, and fit for AI so projects move from pilots to production at scale.

Why this research matters

The research explains how to evolve data management, architecture, skills, and processes so AI use cases deliver on business service levels.

Key planning insights highlighted in the report:
• Through 2026, organizations that don’t enable and support their AI use cases through an AI-ready data practice will see over 60% of AI projects fail to deliver on business SLAs and be abandoned.
• Through 2026, thirty percent of generative AI projects will be abandoned after proof of concept due to poor data quality, inadequate risk controls, escalating costs or unclear business value.
• Through 2027, data management tool providers failing to leverage GenAI will exhibit 10% revenue erosion annually.
• Through 2027, GenAI will reduce manually intensive data management costs up to 30% each year while enabling four times as many new use cases.

What you can learn:
• How to assess data readiness for AI using a maturity approach that aligns data to each use case.
• How to support unstructured data for AI, including retrieval augmented generation as a service.
• The skills, roles, and operating model changes needed in the era of generative AI.
• How to establish practical AI governance that balances value and risk.
• How to build a clear business case and success metrics for AI ready data investment.