By Enterprise Technology Reporting Desk
For the better part of the past decade, enterprise data catalogs and compliance governance tools occupied a quiet, peripheral role in corporate architecture. They were viewed primarily as utilitarian ledgers—useful for satisfying regulatory mandates, maintaining compliance records, and documenting database schemas, but rarely recognized as central engines of corporate strategy. However, the explosive rise of artificial intelligence has dramatically rewritten this dynamic, forcefully pulling data intelligence tools from the background straight into the center of enterprise decision-making.
In the era of generative artificial intelligence and autonomous systems, the underlying principle is absolute: an enterprise model or an AI agent is only as reliable, accurate, and trustworthy as the data feeding it. Consequently, the operational platforms responsible for cataloging, governing, delivering, and protecting that data have ceased to be administrative afterthoughts. They have transformed into foundational strategic decisions that executive leadership must get right to survive and compete.
This critical evolution forms the core thesis of a new assessment from International Data Corporation (IDC). According to findings from IDC’s 2025 Office of the Chief Data Officer (CDO) Survey, a striking 86% of organizations report that they are actively increasing their focus on advanced data management specifically to support generative AI and agentic AI initiatives. Financial budgets and executive attention are rapidly shifting in lockstep with this priority. The modern layer that successfully assembles, validates, and delivers trusted data has become the ultimate battleground where enterprise AI programs either succeed or stall.
This is no longer a conversation confined to compliance officers and data governance committees. It is a broad, high-stakes AI readiness conversation. It is precisely against this evolving macroeconomic and technological backdrop that IDC has officially positioned Precisely in the Leaders category of the 2026 IDC MarketScape: Worldwide Data Intelligence Platform Software Vendor Assessment. Authored by senior industry analysts, the report evaluates how major software vendors are adapting to a corporate landscape where trusted context is the ultimate currency.
The Structural Trends Reshaping Data Intelligence
The 2026 IDC MarketScape evaluates 15 prominent technology vendors, revealing a notable degree of strategic alignment across a diverse and competitive field. According to guest authors Marlanna Harrington, Senior Research Analyst for Data Platforms at IDC, and Stewart Bond, Vice President of Data Intelligence and Integration Software at IDC, the vendor community is moving aggressively to address the infrastructural demands of modern AI systems.
Every vendor evaluated in the 2026 assessment outlined a clear, actionable roadmap to embed generative artificial intelligence—and increasingly, agentic AI—directly into core cataloging, data quality, and governance workflows. Furthermore, nearly all participating vendors now expose governed metadata directly to autonomous AI agents through the Model Context Protocol or equivalent open interface standards. This interoperability ensures that AI models can query and understand corporate data environments with unprecedented precision.
Perhaps the clearest operational signal in the current market is the rapid rise of the digital data steward. These are intelligent software agents designed to shoulder the slow, tedious, and manual labor traditionally required of human data workers: documenting scattered data assets, drafting complex data quality rules, and proactively proposing remediation strategies. Crucially, the reasoning and decisions made by these agents are surfaced clearly for human approval, ensuring necessary oversight.
For most modern enterprises, the real operational constraint is not a shortage of advanced software tools, but a critical shortage of skilled people and available hours. Automation capable of executing stewardship work at scale is fast becoming standard table stakes for any enterprise data platform.
A parallel structural shift is occurring around openness and data architecture. Modern data products and contractual frameworks are increasingly built on open specifications, while data lineage and underlying storage interoperate seamlessly through widely adopted industry standards such as OpenLineage and Apache Iceberg. This open architecture leaves enterprise buyers materially less exposed to vendor lock-in than they were even two years ago, shifting the true competitive separation between platforms to underlying architectural strength and native execution depth.
Looking ahead, the market is being pulled forward by the expanding scope of what needs to be governed. Organizations are moving rapidly from governing the structured data they already understand and manage internally to governing everything that artificial intelligence can now reach across unstructured repositories, external feeds, and complex pipelines.
Underneath every one of these technological shifts lies a single, indispensable job to be done: supplying accurate, contextual meaning. IDC treats context not as a separate, isolated market category, but as an essential new use case that data intelligence exists to serve. An autonomous AI agent that does not understand what a specific dataset actually means, where its numbers originated, or whether its source can be genuinely trusted will inevitably produce confident, articulate, but completely ungoverned—and quite possibly disastrously incorrect—answers. Data intelligence is, ultimately, the critical mechanism that transforms raw, unstructured metadata into reliable context and delivers it dependably to both human decision-makers and machine intelligence.
Why Current Platform Decisions Directly Drive AI ROI
The financial and operational stakes of these platform choices are fully measurable, and the causal link runs directly from deep intelligence about enterprise data to the sophisticated data products built on top of it.
Traditional capabilities such as cataloging, lineage mapping, quality verification, and active governance enable an internal data team to transform a raw, chaotic dataset into a polished data product equipped with accountable ownership, discoverable access controls, and a clearly defined operational purpose.
Recent IDC empirical research directly connects higher levels of data product maturity to superior corporate AI outcomes. Organizations demonstrating high data product maturity are 5.5 times more likely to have successfully pushed generative AI applications into full production, and 4.6 times more likely to have agentic AI running in production, compared to their low-maturity industry peers. Moreover, these mature organizations report roughly three times the overall financial and operational improvement from their technology investments.
This stark performance gap explains why selecting the right data intelligence platform is now recognized as a material driver of enterprise AI return on investment, rather than a secondary technical consideration.
Precisely earned its position as a Leader in the 2026 IDC MarketScape assessment based on a comprehensive evaluation of both its current platform capabilities and its forward-looking strategic vision. The assessment measured vendors against the specific criteria that matter most as the enterprise software market accelerates its pivot toward AI-ready data and trusted organizational context. Enterprise leaders and technology buyers can review an excerpt of the 2026 IDC MarketScape: Worldwide Data Intelligence Platform Software Vendor Assessment directly through Precisely to examine the full market overview and evaluation methodology.
As enterprises grapple with the massive pressures of digital transformation, upcoming industry events are slated to explore these themes further. Precisely has scheduled a virtual event titled Precisely Now: Where Data Meets AI, set for October 8. The event will focus on navigating the new era of AI-ready data and features presentations from Precisely CEO Walid Abu-Hadba, Chief Product Officer Matt Waxman, IDC analyst Stewart Bond, and enterprise customers who are successfully achieving trusted, AI-ready data environments today.
