To Build Or Buy AI Agents? Here Are The Pros, Cons And Complexities

Steve Karp is Chief Innovation Officer at Unanet with 30+ years of experience in enterprise software, fintech and product innovation.

Whether you build or buy AI agents, be sure the choice is driven by value above all else.

​To build or to buy? Companies have been grappling with some version of that question since the dawn of the digital era.​

During the internet’s adolescence, it meant deciding whether to take a DIY approach to designing and building a business website using in-house resources or to outsource.

Later, with the ascendance of software-as-a-service (SaaS) solutions, the focus of the question shifted to whether to develop custom software internally or to invest in a third-party SaaS offering.​

Now, organizations have access to a growing array of foundational AI models and agent frameworks that give them tools to build their own AI agents to execute tasks, dialogue with employees and oversee other AI agents. The question is whether it’s wiser to build your own agents on top of your existing tech stack or to use software solutions with integrated AI agents.​

As is often the case with fundamental business questions, the answer is, “It depends.”​

As CIO at Unanet, I spend a lot of time evaluating emerging technologies and deciding where it makes sense for us to build, where to partner and where an existing solution can get us to the right outcome faster.

Throughout my career in technology, I’ve learned that these decisions often come down to balancing differentiation and control with cost, complexity and long-term value.​

Factors To Consider​

The case for using AI agents and conversational copilots has become clear: for their ability to autonomously execute tasks; gather and analyze large amounts of information quickly to inform and improve decision making; and put knowledge at people’s fingertips.​

• Integratability: How readily can a built AI tool integrate with the systems of record in your tech stack?