Infrastructure Considerations for Data Leaders: Building Strong Data Foundations to Maximize AI/ML Investments
AI investments stall without a modern data foundation. As organizations race to operationalize AI/ML, many confront the same blockers: siloed and “dark” data, fragmented architectures, skills gaps, and unclear ROI.
Discover IDC’s latest guidance on how to architect AI‑ready data, treat data as a product, and work with services partners to turn enterprise intelligence strategy into measurable business outcomes.our AI investments depend on a strong data foundation.
Who should read this:
This InfoBrief is essential for CIOs, CDOs, data and analytics leaders, and business executives responsible for AI, enterprise intelligence, and digital transformation strategies. It is especially relevant for organizations looking to scale AI beyond pilots, rationalize data and analytics investments, or partner with services providers to modernize their data foundation.
What you'll learn:
- How AI‑ready data architectures improve operational and financial KPIs across the business.
- Why data product disciplines are emerging as a critical success factor for AI and analytics initiatives.
- The four planes of IDC’s Enterprise Intelligence Architecture and how they work together to support AI workloads.
- The top technical and organizational challenges data leaders face, and where services partners can make the greatest impact.
- How buyers are prioritizing data management, generative AI, and data infrastructure investments over the next 18 months.
- What leading organizations expect from services providers in terms of expertise, delivery models, and innovation.
Sneak Peek: Key Statistics
4.4% financial metric uptick
Average improvements with mature enterprise intelligence architectures.
30% of organizations
Will reduce GenAI investments by 2027 due to low ROI from poor planning.
21% revenue growth
Organizations investing in enterprise intelligence services see average improvements.
40% of enterprises
Prefer to work with a single primary services provider to develop and execute their foundational data strategy.
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