Ten predictions for data science and AI in 2020

This will likely continue to cause confusion as newer entrants to the industry may only see a part of the whole. Today, you may model on enterprise tools if you work for large organizations that can afford them. You may model in a database environment if you are a DBA with MS SQL Server. You could call machine learning APIs and develop an'AI product' if you are a software engineer. You could build and deploy the same model on cloud platforms such as AWS Sagemaker or Azure ML Studio if you have familiarity with cloud offerings. And the list goes on. The net result may be fertile ground for misunderstanding and turf wars due to similar functionality being available in different forms. Against this landscape, the organizations that are able to build high levels of trust across disparate technical teams will be the ones who reap the full benefits of the toolkit available today.