AI is changing the economics of software development. Teams can now prototype faster, automate more, and create new workflows with fewer technical barriers. But that does not make the build vs. buy decision any simpler.
In the latest episode of ProcureTech Unpacked, Matthew Buckingham and Joël Collin-Demers look beyond the usual sticker-price comparison and ask a more important question: how much technology does your organization actually want to own?
Key Takeaways
- Why build vs. buy is rarely a simple binary choice, especially as AI lowers the barriers to custom development
- Where hidden ownership costs can emerge, including maintenance, upgrades, technical debt, and internal support
- How talent, governance, security, and integration can significantly change the total cost of ownership
- Why a “buy to build” approach can offer a practical middle ground between custom development and prebuilt solutions
- When building technology in-house can make sense for strategically important or highly differentiated capabilities
The conversation also highlights why the best decision is not necessarily the option with the lowest upfront cost. The right approach depends on how much control, flexibility, responsibility, and long-term ownership an organization is prepared to take on.
For procurement and IT leaders evaluating AI capabilities, internal builds, or another best-of-breed tool, this episode offers a practical framework for making the decision with the full technology lifecycle in mind.
