SAP, ODI Partner to Build AI-Ready Enterprise Data Foundations

SAP said it has partnered with the Open Data Institute (ODI) to help organizations build AI-ready, well-governed data infrastructure, addressing a critical barrier to enterprise AI adoption: data that is not designed for AI use.

The Open Data Institute (ODI) is an independent, non-profit organization co-founded in 2012 by Sir Tim Berners-Lee and Sir Nigel Shadbolt to promote the use of open data to build a trustworthy, efficient data ecosystem.

Sir Tim Berners-Lee is an English computer scientist best known as the inventor of the World Wide Web, HTML, the URL system, and HTTP. Prof. Sir Nigel Shadbolt is a leading researcher in artificial intelligence and was one of the originators of the interdisciplinary field of web science.

Headquartered in London, U.K., the ODI provides training, research, and consultancy to help governments and businesses maximize data benefits.

Bridging the Gap Between Enterprise Data and AI

The collaboration centers on a new program, IDEA (Interchange for Data and Enterprise AI), which combines research, governance, and community engagement to help enterprises prepare their data for AI at scale.

With enterprises accelerating AI investments in 2026, SAP and ODI argue that the real challenge is no longer access to AI models, but whether underlying data is trustworthy, governed, and structured for AI-driven decision-making.

Louise Burke, CEO of ODI, said, “AI will strongly influence the competitiveness of organizations over the next ten years. However, the difference lies not only in the models, but precisely in the quality, governance, and autonomy of the underlying data. Many organizations possess data that is not yet suitable for AI. If this backfires, it can lead to distorted outcomes and regulatory issues.”

A key issue the partnership aims to solve is that most enterprise data was built for human consumption, supporting transactions, compliance, and reporting, rather than AI applications.

As a result, organizations face unreliable AI outputs, increased compliance risks, and inconsistent decision-making when deploying AI on unprepared data.

The IDEA initiative is designed to address this gap by creating frameworks and standards that enable organizations to transform existing data into AI-ready assets.

Three Pillars of the IDEA Program

The SAP-ODI collaboration is structured around three core workstreams:

• Independent governance: ODI and SAP will establish an independent governance model and steering committee, drawing on ODI’s 14 years of experience running multi-stakeholder data initiatives across public and private sectors. This board will set research priorities, oversee outputs, and act as a neutral forum for participants from different industries and vendors.
• Research on AI-ready data: Joint research will offer guidance to CIOs and CDOs on how to make enterprise data “AI-ready” across classical ML, generative AI, and agentic AI, including how these intersect with modern data architectures like data mesh, data fabric, and domain-oriented data products. The agenda includes practical questions such as how to operationalize data quality, access controls, and lineage for AI workloads that span SAP and non-SAP systems.
• Community and open standards: ODI and SAP will curate a broad community of SAP customers, partners, policymakers, and academics to share best practices, shape the research agenda, and feed into open, interoperable standards for enterprise data. The partners explicitly invite additional organizations and funders to join, with the ambition of co-developing an open blueprint for AI-ready data that connects to diverse systems and sources rather than locking into a single vendor stack

Together, these pillars aim to produce an open, interoperable blueprint for enterprise data that extends beyond any single vendor.

From Data Quality to Data Trust

SAP executives emphasize that enterprise competitiveness in the AI era will depend less on models and more on the quality and governance of underlying data.

Irfan Khan, chief product officer for data and analytics at SAP, also emphasizes the importance of a strong data foundation: “As organizations continue to scale AI in 2026, the real gap lies not in the technology, but in trust in data. Organizations with well-integrated and well-managed data often perform better and achieve measurable results faster. An important next step is therefore establishing a business data fabric, so that AI agents have the right context to properly understand the business and act in a targeted manner.”

The initiative highlights a shift toward concepts such as business data fabric, where integrated, contextualized data enables AI agents to operate with greater accuracy and autonomy.

Daniel Dukes, senior director of product marketing at SAP, wrote in a blog post, “A business data fabric brings heterogeneous sources into a consistent state, making it easier to combine SAP and non-SAP data. For data scientists and AI engineers, efficient data access and trusted AI can become the rule, not the exception. Ultimately, operationalizing a data fabric shortens the project cycle—delivering faster time to value,”

By focusing on data trust, governance, and interoperability, SAP and ODI are positioning AI readiness as a data architecture challenge rather than a purely technological one.

Industry-Wide Push Toward Open Standards

A notable aspect of the partnership is its emphasis on open standards and vendor-agnostic frameworks.

During the project, ODI and SAP will form a steering committee, publish research outputs, and convene events and workshops to share early findings with participating organizations.

The program is designed to bring together stakeholders across industries to co-develop shared approaches to enterprise data, reducing fragmentation and helping organizations avoid lock-in as they scale AI initiatives.

SAP and ODI are also inviting broader industry participation and funding, signaling that ODI and SAP expect the blueprint for AI-ready data to be co-created with customers, partners, and other technology providers.

What This Means for SAPinsiders

AI-readiness becomes an architecture problem, not just a model choice. Enterprises investing in AI must prioritize data quality, governance, and context. This partnership reinforces that successful AI on SAP S/4HANA and SAP BTP depend on how you structure, govern, and expose business data across SAP and non-SAP systems, exactly where SAP architects and practitioners make daily decisions. Without this foundation, even advanced AI initiatives risk delivering unreliable outcomes and limited business value.

Open standards will shape enterprise data strategies. The push toward vendor-agnostic frameworks signals a shift away from siloed architectures. Organizations should evaluate how their data strategies align with emerging interoperability standards. This partnership will influence future best practices and reference models SAPinsiders rely on. As ODI and SAP publish guidance on AI-ready data, expect concrete patterns for domains, data products, lineage, and controls that can feed into your SAP S/4HANA transformations, SAP BTP data designs, and clean-core governance playbooks.

Data architecture becomes a competitive differentiator. Approaches like data fabric and data products will define how effectively enterprises scale AI. Leaders must rethink data as a strategic asset, not just an operational byproduct. Furthermore, ODI’s involvement gives more weight to SAP’s data fabric narrative, signaling that open standards, interoperability, and transparent governance will shape how regulators, partners, and boards assess AI initiatives built on SAP platforms.