In a recent Forbes article, contributor Gary Drenik spoke with Covail’s VP, AI & Automation, Brian Sampsel, about how companies are responding to AI as a tool for business forecasting.
In the article, Drenik asks an important question — With the flurry of hype around data science, machine learning and AI, are companies actually using these tools? Not as often or as well as they should, says Sampsel. He notes that while most large enterprises have departments such as IT and finance that make predictions all the time, they still tend to use inefficient and manual approaches (such as Excel worksheets).
Sampsel further comments on how AI fits into a traditional approach to forecasting, commenting that it is less important to focus on the “how” than the “why.” Sampsel lists several key benefits of incorporating analytics into the forecasting process, including freeing up people for other value-added activities; understanding variability and a range of likely outcomes; and having the ability to fuse outside data with internal data for better forecasting.
Drenik and Sampsel further discuss some of the speed bumps enterprises may expect along the way to incorporating AI, but ultimately the takeaway is clear: Enterprises should be adding AI into their processes to improve both the accuracy and the consistency of their forecasting models.
Be sure to read the full Forbes article, Improved Forecasting Through Machine Learning & Artificial Intelligence or contact Brian Sampsel directly at email@example.com for more information about the benefits of integrating AI and machine learning into your company’s forecasting model.