In the age of AI, the wrong build vs. buy decision isn’t just costly — it could decide whether your business thrives or becomes irrelevant.
As CIOs, we face this question constantly: should we build custom software solutions or buy off-the-shelf products? Now, more than ever, with the hyper-accelerated development in AI, this decision has taken on new urgency and complexity. Do we adopt commercial AI offerings to accelerate time-to-market, or do we build custom solutions to create meaningful differentiation? Throughout my career leading IT in facility services and construction, I’ve lived on both sides of this decision, sometimes simultaneously. What I’ve learned is that the answer is rarely black and white — it’s about making strategic choices based on your specific business context.
When I built a custom solution — and why it worked
At Assetlink, I faced a significant challenge with our facility management operations. Our teams needed a comprehensive order-to-cash work order management solution that would seamlessly integrate with our unique business processes. After evaluating the market offerings, I realized none of them addressed our specific workflows without significant compromises.
We made the decision to build our own solution. This wasn’t a choice made lightly — it required substantial investment in development resources and time. But our business processes represented a competitive advantage in how we serviced our clients, and standardizing to fit commercial software would have meant sacrificing that edge.
The custom solution we developed became a cornerstone of our operations. It perfectly matched our workflows, integrated seamlessly with our existing systems and gave us complete control over future enhancements. Most importantly, it preserved the unique service approach that differentiated us in the market.
What made this “build” decision successful wasn’t just the technical outcome, but how it aligned with our strategic needs. The solution represented core intellectual property for us — not just a tool, but an embodiment of our business methodology.
When buying made more business sense
Contrast this with my experience at Seymour Whyte, where we faced a different challenge. Our construction projects required sophisticated cost capture capabilities that would feed into our financial information systems. While critical, this function wasn’t a differentiator for us — it was a necessary capability that needed to work reliably and comply with industry standards.
After careful consideration, we opted to purchase a commercial product with robust API capabilities. This allowed us to extend our financial information systems ecosystem without reinventing functionality that was already well-established in the market.
The decision paid dividends almost immediately. Implementation was faster than any custom development would have been. The solution came with built-in best practices from across the industry. And perhaps most importantly, our team could focus its energy on integrating and extending the system rather than building core functionality from scratch.
The APIs provided the flexibility we needed to connect this solution to our broader ecosystem, giving us the best of both worlds: standardized core functionality with customized integration points.
The decision framework that emerged from these experiences
Through these contrasting experiences, I developed a framework for making build vs. buy decisions that goes beyond simplistic cost comparisons. According to research from Forrester, 67% of software projects fail because of wrong build vs. buy choices. Avoiding this fate requires a nuanced approach.
First, I assess whether the function represents core intellectual property or competitive advantage. If the answer is yes, building often makes sense despite higher initial costs. A McKinsey study found that companies that build strategic digital assets aligned with their core business can achieve 20-30% higher profit margins.
Second, I evaluate the uniqueness of our requirements. When I led the Assetlink project, our workflows were genuinely distinctive. But at Seymour Whyte, our cost capture needs, while important, followed industry-standard patterns. Harvard Business Review suggests that organizations often overestimate their uniqueness, leading to unnecessary custom development.
Third, I consider our internal capabilities and focus. Building requires not just initial development resources but ongoing maintenance and enhancement capacity. At Assetlink, we had the team and focus to support a custom solution long-term. At Seymour Whyte, our technical resources were better deployed in integration and business process optimization, not to mention their current modernization initiatives in-flight.
Finding the middle ground with modern approaches
Today’s technology landscape offers more nuanced options than the binary build-or-buy choice I faced earlier in my career. Low-code platforms, API-first commercial solutions and microservices architectures enable hybrid approaches that weren’t previously possible.
In both my Assetlink and Seymour Whyte experiences, I found that the most successful outcomes came not from dogmatically choosing one path, but from thoughtfully determining which components to build and which to buy based on strategic value.
For other CIOs facing similar decisions, I recommend starting with these questions:
- Does this function represent core intellectual property or competitive advantage for your business?
- Are your requirements genuinely unique, or have you fallen into the “we’re special” trap?
- Do you have the capabilities and focus to not just build but maintain and evolve a custom solution?
- Can modern approaches like low-code platforms or API-driven integration give you the best of both worlds?
The AI imperative: Why waiting is no longer safe
The build vs. buy decision has always been complex, but the emergence of AI has fundamentally altered the risk equation. Historically, there was a level of safety in waiting and not being on the leading edge of adopting new technology. The conventional wisdom was to let others work through the early challenges and adopt once solutions matured.
With AI, this calculus has changed dramatically. The pace of AI advancement and its potential for business transformation mean that waiting in the same way now presents a greater risk of jeopardizing your organization’s future viability. Companies that delay AI adoption aren’t just missing opportunities — they’re actively falling behind in ways that may be impossible to recover from.
This doesn’t mean rushing into ill-considered AI implementations. Rather, it means approaching the build vs. buy decision with a new sense of urgency and strategic importance. For capabilities that truly differentiate your business, building custom AI solutions may be essential to maintain a competitive advantage. For others, rapidly adopting best-in-class AI offerings may be the most prudent path.
What’s clear is that the traditional “wait and see” approach is no longer the safe option it once was. The build vs. buy decision isn’t just a technology choice or even a business strategy decision. In the age of AI, it’s increasingly an existential one that will determine which organizations thrive and which struggle to remain relevant.
By applying a thoughtful framework to these decisions, balancing speed with strategic value and recognizing the changed risk landscape, CIOs can help their organizations navigate this new reality with confidence and foresight.
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