company that’s putting artificial intelligence at the center of its business, you’ll probably hear a predictable list of technology powerhouses: Alphabet , Meta , Amazon, Microsoft, Tencent, and Alibaba. But at legacy organizations in other industries many leaders feel that it’s beyond the capabilities of their companies to transform themselves using AI.
Each of the 10 undertakings we list in this article will bring your business closer to transformation—but to fully achieve it, you must avoid piecemeal efforts and attack all 10 tasks. The accompanying examples detail how some organizations succeeded. Your business may choose to handle the tasks differently or to approach them in a different order.Ambitious companies have a specific sense of how they mean to apply AI.
But what exactly does “mastering analytics” mean? In this context it requires a commitment to using data and analytics for most decisions, which means changing the way you deal with customers, embedding AI in products and services, and conducting many tasks—even entire business processes—in a more automated and intelligent fashion.
Capital One, which has been recognized for decades as an analytics powerhouse, has used analytics to understand consumer spending patterns, reduce credit risk, and improve customer service. In 2011 Capital One made a strategic decision to reinvent and modernize its culture, operating processes, and core technology infrastructure.
Some branches of the U.S. government identified specific tasks and workflows that were ideal for AI speed and scale. NASA, for example, launched pilot projects in accounts payable and receivable, IT spending, and human resources. The Social Security Administration has used AI and machine learning in its adjudication work to address challenges from heavy caseloads and to ensure accuracy and consistency in decision-making.
Cleveland Clinic also uses AI to assess risk in the population health area, where it has built a predictive model that helps prioritize the use of scarce resources to deliver care to the patients most in need. The predictive risk score is now its primary method for determining who gets a phone call to check in. A diabetic patient who has difficulty managing the disease, for example, would get a high-risk score.
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