The prevailing wisdom that enterprises would build most AI solutions themselves has reversed dramatically. According to Menlo Ventures’ 2025 analysis, 76% of AI use cases are now purchased rather than built in-house, up from a 53/47 split in 2024. The shift reflects maturation of commercial AI offerings and recognition that internal development requires significant investment without guaranteeing competitive advantage.
What Happened
Early AI adoption saw major enterprises—Bloomberg training BloombergGPT for finance, Walmart building Wallaby for retail—investing heavily in custom capabilities. Companies believed that proprietary data, domain expertise, and internal scaffolding would deliver differentiated results. That confidence has faded as commercial solutions improved rapidly and deployment challenges became clear.
Key Data
2024 split: 47% built internally, 53% purchased
2025 split: 24% built internally, 76% purchased
Enterprise AI spending: $37 billion total, with applications leading infrastructure
Internal R&D allocation: About one-third of AI technology budgets
Expert Analysis
“For a while, the prevailing wisdom was that enterprises would build most AI solutions themselves. Today, that confidence still showed in the data—but the balance has shifted dramatically toward purchasing.”
— Menlo Ventures, State of Generative AI in the Enterprise
“Most organizations are still navigating the transition from experimentation to scaled deployment. The experience of the highest-performing companies suggests a path forward.”
— McKinsey, State of AI 2025
What’s Next
Enterprises will continue allocating about one-third of AI budgets to internal R&D, maintaining custom capabilities for differentiated use cases. The buy-first approach dominates for common applications while build strategies focus on proprietary competitive advantages.
Frequently Asked Questions
Why are companies buying rather than building?
Commercial solutions have matured rapidly, time-to-value is faster, and internal AI development requires specialized talent that remains scarce.
About the Author
Daniel Okonkwo holds an MBA from the University of Michigan and previously worked as a technology strategy consultant.
About The Author
