have to make decisions – but decision making is complex, and getting it wrong can be costly. Decision intelligence is a relatively new field that harnesses data and elements of applied data science, social science and managerial science to help enterprises make better decisions. DI is also essential in implementing artificial intelligence , and when combined with it, it’s a potent tool that can alleviate decision fatigue.
DI is proving invaluable for the era of AI, because it helps people designing AI strategies and solutions to ensure they’re choosing the right sort of AI and applications for it, and that they’re responsibly creating appropriate metrics, objectives and safety nets, especially for automation at scale.
DI can augment decision-making by, for instance, helping humans decide between a huge array of options or complex data sets. Ultimately, the person still makes the final decision, but DI can help by simplifying the available options or rapidly weighing them against one another. When it comes to automation of the decision process, DI can empower AI to make decisions automatically based on existing rule sets and AI-based predictions.
In the retail sector, DI presents the opportunity to better predict product prices using information on demand, trends and even global macroeconomic variables. For example, software Remi AI lets users adjust their pricing to match customer expectations while also optimising their supply chains. One concern is a DI tool that can assist with ecological challenges too, from individual businesses to those facing society more broadly. One of the key benefits of decision intelligence is its ability to both harness massive historical datasets and also provide predictions that businesses and governments can use to prepare for potential challenges, like extreme weather. Moreover, DI can also help with creating the right strategies to contend with those challenges.