Scale AI to value
The infrastructure strategy for production-first CIOs
Organizations are rapidly adopting AI, but most still struggle to turn pilots into production results. This executive summary outlines the strategic infrastructure foundations CIOs need to scale AI efficiently, securely, and with measurable business impact.
The challenge: Most AI pilots never make it to production.
Enterprise AI teams spend as much as 70% of their time on data preparation and pipeline management.[1] A major reason projects stall before delivering real value.
CIOs who modernize their data environments gain a decisive advantage: faster outcomes, lower costs, and clearer ROI.
#1
Data management is the #1 AI adoption roadblock.[2]
Production-first CIOs prioritize these three fundamentals
Unified data platforms
Make all data instantly available and easily manageable across the pipeline—from on-premises to cloud to edge—all under one view.
Hybrid cloud strategy
Use any major cloud—compute meets data, not the other way around. Stop costly data movement, make use of the best cloud data services, and simplify management—without vendor lock-in.
Enterprise cyber resilience
Build in data protection and security at the data layer, eliminating the compliance, security, and governance gaps that slow AI deployments.
The strategic question facing CIOs
How do you scale AI from lab experiments to real business impact — flexibly, efficiently, and securely?
The organizations winning the AI race have already laid the groundwork. Leaders who build AI-ready infrastructure today will shape and dominate tomorrow's AI-driven markets.
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