As organizations continue to find creative ways to drive their talent strategy, one untapped (and sometimes non-obvious) lever for doing so is that of employee recognition programs. Within the context of artificial intelligence and analytics, the data contained within employee recognition platforms can be used to derive important talent insights that inform decision-making and talent strategy. In this issue of HRO today (which includes several articles), one of the articles (p. 37-39) covers tactics for strategically leveraging recognition programs for this purpose. Two tactics mentioned include 1) Use of recognition tools to identify rising talent. Since many organizations use technology for peer-to-peer recognition, analytics can look at patterns in these recognition events to determine “rising talent.” This type of data point can be used in conjunction with other talent indicators to identify employees who fall into this category. 2) Predicting Turnover – using analytics that correlates how likely a person is to leave an organization based on their activity within an employee recognition program. The example given is where such an approach can assign each individual employee a score— red, yellow, or green—that indicates the level of retention risk. For those organizations that enable employee recognition programs through technology, you can ask the question: “what type of data and analytics gathered through this platform could we leverage to gain talent insights that inform better talent decisions? The answers to these questions could provide incremental value that enables an organization to accelerate the delivery of its business strategy via talent strategy.