When it comes to legal technology, particularly in the era of artificial intelligence, legal departments and law firms face an age-old question: should we build our own tools, or buy from a vendor?
The answer, of course, is rarely absolute.
Most organizations will find themselves somewhere in the middle, combining purchased technology with tailored customization of that technology, to meet their unique needs. The arrival of generative and agentic AI has reignited the build-versus-buy debate.
There’s a perception that AI can “solve everything,” but the reality is more complex. AI may extract or surface information from contracts, discovery documents, or client data, but organizations still need intuitive, user-friendly systems around it: ways to input clean data, ways to present insights to users, and workflows for acting on the output. This is where the decision to buy, build, or blend comes into play.
For most mainstream use cases, such as contract lifecycle management (CLM), buying from a vendor provides significant advantages. Vendors have been asked the same questions thousands of times and have built scalable answers into their platforms. They also offer economies of scale, compliance guardrails, and user-friendly design that individual legal teams would find costly to replicate from scratch.
One consideration that is often left out of the build/buy calculus is the cost of support. 1.0 is only that: the first version of the application. The world will continue to change around it. Regulations, requirements, macroeconomic trends, and technology continue to evolve, and the application has to keep pace, or it will lose value with each day that it cannot respond to those changes.
In these cases, the smarter path is often to buy a platform and take advantage of its built-in capabilities, then extend or configure it to fit the organization’s particular processes.
Then there are scenarios where building becomes the only realistic choice. Specialized industries may require contract structures or workflows so unique that existing platforms fall short. If no vendor supports your use case, building a custom solution may be necessary.
Building can also be a valuable learning exercise. Low-risk, low-cost pilots can help legal teams explore what AI can and cannot do before committing to a long-term vendor investment. Done thoughtfully, custom builds give teams hands-on experience with emerging technologies while illuminating their real-world limitations.