What Gartner’s 2025 Data & Analytics Trends Mean for Asset Intelligence

Gartner’s recently released Top Trends in Data and Analytics for 2025 highlights a rapidly maturing data environment – and signals an inflection point for how organizations manage and apply asset data. While the report focuses broadly on enterprise data trends, its implications for facilities, infrastructure, and equipment-intensive organizations are both urgent and actionable.

One of Gartner’s central takeaways is that organizations are shifting from data-driven to decision-centric models. In this new paradigm, the goal isn’t just amassing more data – it’s ensuring that data directly supports strategic outcomes. For teams managing complex portfolios of physical assets, this shift demands a rethinking of how equipment and infrastructure data is captured, structured, and applied.

This trend is especially relevant given Gartner’s prediction that by 2026, 50% of data and analytics leaders will measure success based on business outcomes rather than data quality or throughput. For asset managers, engineers, and facility leaders, this means outdated or inconsistent data systems that fail to support actionable decisions – such as lifecycle costing, replacement planning, or emissions reporting – will no longer be acceptable.

The report also emphasizes composite AI – the integration of multiple AI techniques – to solve specific business problems. In the asset space, this points to the growing importance of models that can handle messy, unstructured, and fragmented data sets: equipment photos, O&M manuals, PDFs, and handwritten notes. Without the ability to translate those inputs into structured intelligence, organizations will struggle to capitalize on composite AI’s potential.

Meanwhile, Gartner highlights the growing use of data fabric architecture to unify decentralized data environments. This is particularly relevant to asset data, which often lives in disparate CMMS, BMS, spreadsheets, and physical documents. Gartner notes that data fabric deployments will quadruple efficiency in data utilization while cutting integration time in half – offering a compelling ROI for organizations that prioritize unification and interoperability.

Lastly, the report flags the need for adaptive governance, encouraging data leaders to implement flexible policies that promote trusted, real-time decisions rather than rigid control. This aligns closely with asset environments where conditions change dynamically – whether it’s field repairs, supplier substitutions, or real-time monitoring. Only a system that supports ongoing verification, enrichment, and governance at scale will be able to adapt in kind.

This is where EMPEQ steps in. Our software transforms unstructured asset data into reliable, structured intelligence – fueling trusted, real-time decisions across the lifecycle of infrastructure and equipment. Whether you’re modernizing facilities, building digital twins, or preparing for AI-driven operations, EMPEQ gives you the data backbone to do it with confidence.

Get in touch today to learn more about the world’s leading asset data fabric.