Data Contracts Gain Urgency as AI Tests Data Foundations
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Data Contracts Gain Urgency as AI Tests Data Foundations
Enterprises face a technology temptation: give data governance the slip and dive straight into AI deployment and its anticipated business benefits.
Data neglect, however, leads to low-quality data and, downstream, unreliable AI systems. The problem is driving greater focus on data preparation as a critical step toward AI. In a 2026 Drexel University-Precisely survey, 43% of 505 data and analytics leaders identified data readiness as the top barrier to aligning AI with business objectives, slightly ahead of infrastructure at 42% and skills at 41%.
With AI reliability and ROI on the line, CDOs and other data leaders are exploring data contracts as part of broader data governance strategies. A data contract defines the expectations between data producers and consumers, including schema, ownership, availability, quality standards and change management requirements. These formal agreements are machine-readable for integration in automated governance environments.
For CDOs, data contracts align employees on how data is created and consumed. The key here is to delineate the roles and responsibilities of stakeholders. Balazs Fejes, president and CEO of IT consultancy EPAM Systems, said data contracts make ownership and accountability explicit, but data producers, not centralized governance groups, should bear that accountability.
As AI uses more data across domains and workflows, unclear ownership and inconsistent change controls make it difficult to find the source of errors. Data contracts aim to bridge that gap before issues affect downstream systems.
Contracts can define the structure, quality and delivery requirements for data, but they do not necessarily explain the business meaning, Fejes noted. A semantic layer provides the context AI agents need to make a consistent sense of the data, including shared definitions, metrics and relationships.
"Now that agents will start making decisions with minimal human interaction, the richness of the information required to support this data asset grows exponentially," Fejes said.
In addition, data contracts need the right discipline, change management and formalization, he added.
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