This is the final post in a 3–part series on building an Artificial Intelligence and Machine Learning (AI/ML) capability for the first time. In case you missed our post last week, the second article covered how to set a targeted objective through development and communicating results. We will now focus on deploying and transitioning Artificial Intelligence and Machine Learning capability to operations, governance of the capability, and establishing monitoring and maintenance routines to ensure performance holds with passing… Read More
As part of our 3-part series, our next post provides guidance on how to build an Artificial Intelligence & Machine Learning (AI/ML) capability for the first time. In case you missed our post last week, the first article covered three items required before beginning development on an AI/ML initiative. Moving forward, we’ll now focus on the… Read More
Artificial Intelligence and Machine Learning (AI/ML) technology continue to be increasingly accessible with a lower barrier of entry to newcomers. In recent posts, Gartner identifies that one in ten enterprises now use ten or more Artificial Intelligence applications, with the top use cases being chatbots, process optimization, and fraud analysis. Of the companies reporting Machine Learning usage, Algorithmia identified the following area benefits: reducing company costs, generating customer insights and intelligence, and improving customer experiences. Have you… Read More
