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13 I L T A N E T . O R G In recent years, corporate sectors around the globe began to shift towards creating cultures that acknowledge and address Diversity, Equity, and Inclusion (DEI) within the workplace and other professional groups. P rofessional entities approach DEI-related efforts in various ways, from holding space for members of marginalized communities to share personal stories and experiences to profit-focused arguments showing the impact DEI improvements can have on a business's success. Others openly address the belief that DEI is divisive or a waste of community energy and resources. The formats are equally varied, from companies issuing statements regarding their commitment to DEI practices, panel discussions, or diversity training, to name a few. Determining the best path forward for your organization to implement DEI strategies can be overwhelming, given the potential scope of approaches to DEI and the possible positive or negative outcomes of undertaking DEI initiatives. These efforts depend heavily on collecting and analyzing data to identify disparities, track progress, and inform decision-making. Leveraging artificial intelligence (AI) can enhance the depth of insights in the DEI context thanks to its capacity to process and analyze vast amounts of information. When discussing AI, we often focus on the ability of technology rather than the impact of data on specific processes. When it comes to DEI initiatives, having the right pool of data and statistics is just as important as the AI technology we use to analyze it. Data provides the opportunity to progress and can help answer two of the most fundamental questions organizations should assess as a part of their DEI

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