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Leaders Question AI Software Building vs. Buying

Leaders Question AI Software Building vs. Buying

Enterprise technology leaders are increasingly considering the use of artificial intelligence (AI) to build custom software, a trend that promises potential cost savings by forgoing established platforms like SAP, Workday, or HubSpot. This approach involves CIOs and their teams developing bespoke applications using tools such as Claude Code. The appeal lies in the idea of creating tailored solutions that precisely fit a company's needs, potentially bypassing the limitations and costs associated with off-the-shelf software.

However, a critical evaluation is necessary before committing to an in-house AI development project. The decision to build versus buy is complex and hinges on several strategic questions. A former CIO recounted an experience where his team spent four months developing a custom analytics dashboard for a beverage company. Despite possessing the necessary talent and resources, the project faced numerous setbacks. This led to a crucial realization: the time and resources dedicated to building the dashboard could have been allocated to other initiatives that might have generated greater value for the company. Ultimately, the project was terminated in favor of purchasing an existing software solution.

Now on the other side of the equation, leading a global software company that provides workflow management solutions for HR, customer service, and finance, the author frequently engages with enterprises grappling with this build-or-buy dilemma. These companies seek guidance, trusting the author's expertise gained from firsthand experience. The advice offered is nuanced: while AI-driven custom software development has its place, there are also clear instances where opting for external expertise and purchasing established software is the more prudent and efficient choice. The author emphasizes that the company's future prospects and the CIO's own career can be significantly impacted by this strategic decision.

Before embarking on an AI-powered software development journey, leaders must ask fundamental questions. One of the most critical is whether software development aligns with the company's core competencies. While the availability of engineering talent might initially suggest that building custom software is a straightforward path, it is essential to determine if this endeavor distracts from or detracts from the company's primary business functions. The author observes that some companies, despite having the technical capacity, may find that building software diverts valuable resources and focus away from their core strengths, potentially hindering overall business growth and innovation. This strategic introspection is vital for making informed decisions that support long-term success.

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