The Rise of AI: Why Build vs Buy is a Thing of the Past

In a scenario where a vendor pitch is underway, and a decision on purchasing software is imminent, a surprise revelation from a non-technical member of the team changes everything. This individual, with no coding background, showcases a functional prototype of the software that closely resembles what the vendor is offering, but at a fraction of the cost and time.

This unexpected turn of events challenges the traditional approach of “build versus buy” that companies have adhered to for decades. The conventional wisdom dictated building software only for core business functions and buying for everything else due to the high costs and time investment associated with development. However, the landscape has shifted with the accessibility of AI technology, making software development quicker and more straightforward for non-technical individuals.

The emergence of AI tools has enabled individuals across various departments to create solutions to problems in minutes that previously required extensive engineering resources. This blurring of lines between technical and non-technical roles signifies a significant shift in how software is developed and decisions are made around it.

Instead of the traditional approach of defining a need and then deciding whether to build or buy, the new paradigm involves building lightweight solutions using AI tools to understand the actual requirements before considering purchasing options. This approach allows for controlled experiments to determine the efficacy of a solution before committing to a vendor purchase.

Finance teams, in particular, have a newfound superpower in leveraging AI tools to prototype workflows and assess whether a software purchase is necessary. By testing solutions internally, teams can gain a deeper understanding of their needs, ask informed questions during vendor demos, negotiate better terms, and ultimately choose tools that align with their specific requirements.

The key takeaway from this shift is the importance of building to learn what to buy. Companies that embrace this new approach will operate more efficiently, avoid costly mistakes, and invest in tools that truly add value to their operations. By understanding their needs and capabilities through internal prototyping, organizations can make more informed decisions when purchasing software solutions.

Ultimately, the companies that adapt to this new paradigm will outpace their competitors and make strategic investments in technology that drive real business outcomes. The rules of software development and procurement have changed, and those who embrace this change will thrive in the evolving landscape of AI-powered solutions.