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AI Workloads Are Failing More Than Anyone Admits

Eye on AI16 July 2026Watch on YouTube

Description

The AI gold rush is real, and it's making companies cut corners they know they shouldn't. Paul Appleby, CEO of Virtana, describes what their AI Factory Reality Check study actually found beneath the surface of enterprise AI investment: a gold rush mentality that is actively overriding the governance principles most companies already have in place. The result is a growing disconnect, business executives are pushing for faster AI investment while IT operators are watching failure rates climb and complexity increase without the controls needed to manage it. The equilibrium will come back, Appleby says. But right now, companies are racing to be in the AI investment cycle without stopping to ask whether they can actually govern what they're building. Are the companies you work with moving fast on AI, or moving fast and careful? Full conversation with Paul Appleby of Virtana on Eye on A.I.

What you'll learn

  • AI projects fail more frequently than companies admit, because management pushes for faster investment without implementing adequate governance controls.
  • A gold rush mentality in enterprise AI causes companies to abandon their own governance principles and ignore risks.
  • IT operators see failure rates and complexity rising, while lacking the controls needed to manage and prevent these issues.

Frequently asked questions

Why do AI projects fail more often than companies admit?
A gold rush mentality drives companies to invest faster without implementing the governance principles they already have in place, resulting in higher failure rates and unmanaged complexity.
What is the perspective difference between business executives and IT operators?
Business executives push for faster AI investment, while IT operators observe rising failure rates and complexity without the controls needed to manage these issues.
What does Paul Appleby suggest about how companies approach AI investments?
Appleby suggests that companies are racing to invest in AI without first asking whether they can actually govern what they're building, which is a fundamental problem.

Topics

enterprise aiai governancefailure ratesrisk management