Companies are racing to implement AI to better their businesses; however, most have yet to see results. While your company might have the magic algorithm, there’s a good chance it does not have quality data to yet gain insights. The data most organizations currently have was not gathered or created with machine learning in mind; rather, it was traditionally used for measuring physical and financial assets. But how could these same measures apply in a marketplace where the majority of assets are now intangible? In order for your data (and insights) to have meaning, it must be curated around key knowledge and differentiated from your competitors’ data. When making important decisions, what matters most to your company? How can you capture this knowledge and data to make the best use of it?