AI Readiness: Reducing App Sprawl, Data Debt, and Integration Risk to Scale Enterprise AI

This IDC Perspective examines why many enterprise AI initiatives stall between experimentation and scaled impact. The document argues that the limiting factor is often not model access but the condition of the digital core: app sprawl, fragmented data, brittle integration, and uneven governance. The document also outlines why technology leaders should treat infrastructure readiness as a business capability and provides guidance for reducing structural complexity so AI can be deployed with greater speed, control, and enterprise value."AI readiness depends on infrastructure readiness. Enterprises cannot consistently scale AI on top of fragmented application portfolios, brittle integration layers, and poorly governed data estates," says Dr. Ken Knapton, adjunct research advisor for IDC's IT Executive Programs (IEP). "As AI adoption accelerates, buyers should focus less on adding isolated tools and more on simplifying the application estate, governing data, and modernizing the integration patterns that determine whether AI can scale safely and deliver measurable value."