Build vs. Buy

The Enterprise Cloud Application AI Decision

Why this report matters

Enterprise AI spending hit $30-40 billion in 2024, yet 95% of organizations still report zero measurable ROI from GenAI investments. This research report synthesizes findings from MIT Sloan CISR, the World Quality Report 2025–26, and analysis of 300+ GenAI initiatives to show why most internal AI builds stall before production; and why purpose-built platforms deploy at twice the success rate for cloud application lifecycle management.

What you’ll learn

• Why 95% of enterprise AI pilots never reach production and how to avoid the pilot trap
• The three structural failure modes that sink internal AI builds: integration gaps, learning limitations, and workflow fragmentation
• What deployment data reveals about build vs. buy success rates, timelines, and ROI
• Why only 6% of enterprises apply AI to ERP testing despite it being the highest-value opportunity
• How domain-specific platforms trained on enterprise application patterns outperform general-purpose AI tools
• A practical decision framework to determine when to build internally and when to partner

Who should read this

Enterprise leaders evaluating AI investments for Oracle, Workday, Salesforce, or other cloud applications. IT directors, QE leaders, and program managers responsible for testing, deployment, and lifecycle management in complex ERP environments.