Many firms (Amazon, Google, etc) are touting their plug-and-play AI and Machine Learning tool kits as being a quick way for firms to adopt these new technologies without having to invest resources building their own.
Sound like a good idea but I challenge that. If data is going to drive the new economy, it will be a firm’s analytics capabilities that will give it a competitive advantage. In the short-term adopting a third-party framework for analytics will move a firm up the learning curve faster. Over time this competitive edge becomes blunter, as more firms in a sector start to use the same frameworks in the race to be “first”.
This homogenization will be good for a sector but pretty rapidly firms competing in that sector will be soon locked back in to trench warfare with their competitors. Retail distribution is a good example, do retailers use a 3rd party distribution network or do they buy and maintain their own fleet. Using a 3rd party distributer saves upfront capex but it voids an area of competitive advantage. Building their own fleet, while more costly, gives a retailer optionality about growth and expansion plans.
The same is true in the rush for AI/ML capabilities. While the concepts of AI / ML will be the same for all firms, their integration and application has to vary from firm-to-firm to preserve their potential for providing lasting competitive advantage. The majority of firms we have spoken to are developing their own tool kit, they might use established infrastructure providers but everything else is custom and proprietary. This seems to be the smart way to go.