One of the key decisions facing digital health teams is whether to build a bespoke AI chatbot or buy an off-the-shelf solution. The right answer depends on strategy, risk, and the level of differentiation the product needs.
Building a custom solution offers obvious advantages. It can be shaped around the needs of a specific patient population, integrated tightly into existing systems, and designed to support a more distinctive service model.
Custom builds can also create strategic upside, including stronger product differentiation and more control over how regulatory boundaries are handled. But they come with cost, time, and execution demands.
Buying an existing solution can reduce upfront cost and accelerate deployment. It may also reduce maintenance burden, especially when a vendor handles updates, security, and core infrastructure.
The downside is that most off-the-shelf chatbot products were not designed for patient support in high-trust settings. They may be useful for generic customer support but poorly suited for behaviour change, safety-sensitive workflows, or nuanced clinical adjacency.
Integration and customisation can also become limiting factors. A tool may work well enough at first, but fail to support the depth of product experience or governance a serious health service eventually needs.
In practice, the decision is not just build versus buy. It is about how much control, specificity, and long-term product advantage the organisation actually needs, and whether it is prepared to support that choice properly.