LLM Adoption in the Enterprise

Chapter 5. From Pilot to Product

An AI product that does not make it into production is not a product at all, but merely a demonstration of the technology’s capabilities. There’s no need to prove that LLMs can do amazing things—we’ve all experienced their skills firsthand. As I have emphasized throughout this report, the real challenge lies not in using these models to process your organization’s data, but in integrating them seamlessly into a relevant business use case. Very few companies have been able to do this. With the obvious potential of LLMs, that will have to change.

AI teams that build their pilots with a business use case in mind are much more likely to see them evolve into mature products than teams that build narrowly focused IT demos. Product leaders must guide their teams through the thick and thin of the AI development cycle so that they can build robust, scalable solutions that evolve and thrive in a production environment. In this chapter, I offer a few final pieces of advice to help demystify this pilot-to-product journey.

Scalable Pilots

Most people who have never brought an actual AI product to production are unaware that the development cycle can realistically consist of hundreds of iterations. Each iteration can change the direction of the product, the user base it targets, the technology it uses, and the data it processes. A pilot therefore serves the dual purpose of proving the concept and laying the groundwork for future product development. From there, ...