This article is part of VentureBeat’s special issue, “The Real Cost of AI: Performance, Efficiency and ROI at Scale.” Read more from this special issue.
AI pilots rarely start with a deep discussion of infrastructure and hardware. But seasoned scalers warn that deploying high-value production workloads will not end happily without strategic, ongoing focus on a key enterprise-grade foundation.
Good news: There’s growing recognition by enterprises about the pivotal role infrastructure plays in enabling and expanding generative, agentic and other intelligent applications that drive revenue, cost reduction and efficiency gains.
According to IDC, organizations in 2025 have boosted spending on compute and storage hardware infrastructure for AI deployments by 97% compared to the same period a year before. Researchers predict global investment in the space will surge from $150 billion today to $200 billion by 2028.
But the competitive edge “doesn’t go to those who spend the most,” John Thompson, best-selling AI author and head of the gen AI Advisory practice at The Hackett Group said in an interview with VentureBeat, “but to those who scale most intelligently.”
Ignore infrastructure and hardware at your own peril
Other experts agree, saying that chances are slim-to-none that enterprises can expand and industrialize AI workloads without careful planning and right-sizing of the finely orchestrated mesh of processors and accelerators, as well as upgraded power and cooling systems. These purpose-built hardware components provide the speed, availability, flexibility and scalability required to handle unprecedented data volume, movement and velocity from edge to on-prem to cloud.
Source: VentureBeat
Study after study identifies infrastructure-related issues, such as performance bottlenecks, mismatched hardware and poor legacy integration, alongside data problems, as major pilot killers. Exploding interest and investment in agentic AI further raise the technological, competitive and financial stakes.
Among tech companies, a bellwether for the entire industry, nearly 50% have agent AI projects underway; the rest will have them going in 24 months. They are allocating half or more of their current AI budgets to agentic, and many plan further increases this year. (Good thing, because the …