Summary:
1. The traditional build versus buy decision-making process for software is being disrupted by the accessibility of AI technology.
2. Companies are now able to quickly build prototypes using AI tools to understand their actual needs before making purchasing decisions.
3. Finance teams can leverage AI to prototype workflows, test solutions, and make informed decisions when evaluating and purchasing software solutions.
Article:
Imagine sitting in a meeting room, on the verge of agreeing to a vendor pitch for a new software solution. Everything seems to align perfectly – the demo is impressive, the pricing fits within budget, and the timeline is reasonable. Just as you are about to say yes, a member of the finance team walks in and presents a working prototype they created in just two hours using an AI tool. This unexpected turn of events challenges the traditional notion of building versus buying software.
For years, companies have followed a simple rule when deciding whether to build or buy software: build if it’s core to your business, buy if it isn’t. However, the rise of AI technology has made building software more accessible to everyone. Tasks that once required weeks of coding can now be completed in a matter of hours using plain English commands. As the cost and complexity of building software decrease, the traditional build versus buy framework is being redefined.
Companies are now finding themselves in a new paradigm where they can build lightweight prototypes using AI tools to understand their actual needs before making purchasing decisions. By developing a clear understanding of what is truly necessary, companies can make more informed decisions when it comes to buying software solutions. This approach allows for controlled experiments, ensuring that software purchases are made based on actual needs rather than perceived ones.
Finance teams, in particular, can leverage AI technology to prototype workflows and test solutions before committing to purchasing software. By understanding what “good” looks like and being able to identify the best solutions for their needs, finance teams can make smarter purchasing decisions. This new approach not only allows for faster implementation and better negotiation but also helps avoid the costly mistake of investing in software that doesn’t truly solve the problem at hand.
In conclusion, the traditional build versus buy decision-making process for software is evolving into a more refined and intelligent approach: build to learn what to buy. Companies that embrace this shift will move faster, spend smarter, and make more informed decisions when it comes to purchasing software solutions. By leveraging AI technology to prototype and test solutions, companies can avoid falling into the trap of purchasing tools that don’t truly address their needs. This new approach is already happening across various industries, signaling a fundamental shift in how companies approach software decision-making.
