Enterprises of all sizes and across virtually all markets are scrambling to augment their analytics capabilities with artificial intelligence (AI) in the hopes of gaining a competitive advantage in a challenging post-pandemic economy.
Plenty of anecdotal evidence points to AI’s ability to improve analytics, but there seems to be less conversation around how it should be implemented in production environments, let alone how organizations should view it strategically over the long term.
Start with a plan
AI may be the latest iteration of digital technology, but like its predecessors, it is not infallible. More often than not, success hinges on deployment and integration into existing environments, not the technology itself. Before rushing headlong into the AI tsunami, enterprise executives would be wise to consider how they plan to use it and to what end.
According to Content Rules founder and CEO Val Swisher, AI can be applied to analytics in three ways: as a descriptive tool, a predictive tool, and a prescriptive tool. Descriptive AI is used to describe something that has happened in the past, usually by grouping data into clusters to detect patterns and outliers. This allows enterprises to answer the question, “What happened?” Predictive AI takes descriptive results and attempts to apply them to the future, again using massive data mining and storing. This answers the question, “What could happen?” Prescriptive AI then takes all this data and resulting analytics to help guide the process to a desired outcome, answering the question “What should happen?”
Continue reading: https://venturebeat.com/2021/10/04/how-to-get-ai-analytics-right/
Plenty of anecdotal evidence points to AI’s ability to improve analytics, but there seems to be less conversation around how it should be implemented in production environments, let alone how organizations should view it strategically over the long term.
Start with a plan
AI may be the latest iteration of digital technology, but like its predecessors, it is not infallible. More often than not, success hinges on deployment and integration into existing environments, not the technology itself. Before rushing headlong into the AI tsunami, enterprise executives would be wise to consider how they plan to use it and to what end.
According to Content Rules founder and CEO Val Swisher, AI can be applied to analytics in three ways: as a descriptive tool, a predictive tool, and a prescriptive tool. Descriptive AI is used to describe something that has happened in the past, usually by grouping data into clusters to detect patterns and outliers. This allows enterprises to answer the question, “What happened?” Predictive AI takes descriptive results and attempts to apply them to the future, again using massive data mining and storing. This answers the question, “What could happen?” Prescriptive AI then takes all this data and resulting analytics to help guide the process to a desired outcome, answering the question “What should happen?”
Continue reading: https://venturebeat.com/2021/10/04/how-to-get-ai-analytics-right/
