AI, Managed Services And The CIO's Balancing Act
Hitachi Vantara, Monday, April 6th, 2026
For today's CIOs, the promise of AI comes with a paradox: delivering transformative new applications while managing infrastructure complexity that few internal IT teams are equipped to handle.
AI workloads often include massive datasets and query loads. AI training requires processing terabytes or petabytes of data, which can be challenging for traditional infrastructure to manage across systems. The data must also be cleaned, labeled, normalized and structured-otherwise challenges can crop up. In fact, a recent MIT study found that 95% of AI projects fall short, often due to data problems.
Enterprises are accelerating AI adoption, which is putting pressure on CIOs to quickly deploy reliable, high-performance infrastructure. Much is riding on these infrastructure decisions, because organizations can't afford to have AI applications underperform. Competitors are often moving fast to put their models into operation.