In this series we explore the most important parts of moving AI/ML projects from lab scale to production.
In our experience, building momentum around AI/ML initiatives is the biggest factor in success overall. To build momentum you need to put your best foot forward from the start and that means knowing what will have the most impact to your business. There are quick and easy ways to try out some smart stuff for sure, but if they are not going to help deliver something meaningful, the business rarely cares enough to double down (as it should). Once you have done a couple of POCs, picking an outcome that will grab the attention of decision makers and influencers across the organisation is often essential.
Typically it will be an outcome connected to the strategic goals of the company like; new revenue, improved user metrics, reduced cost, new efficiency, better customer satisfaction etc. There is often a roadmap for the use case to be fully proven and this should align with the improving performance of the AI/ML model or the timeline for the feedback loop to deliver increased value. The hero use case will act as a magnet for resources, talent and marketing support, all vital on the journey to scale.
Step 2 | Understanding Operations