Feb. 6, 2024, 5:42 a.m. | Wei Sun Scott McFaddin Linh Ha Tran Shivaram Subramanian Kristjan Greenewald Yeshi Tenzin Zack Xue

cs.LG updates on arXiv.org arxiv.org

Prescriptive AI represents a transformative shift in decision-making, offering causal insights and actionable recommendations. Despite its huge potential, enterprise adoption often faces several challenges. The first challenge is caused by the limitations of observational data for accurate causal inference which is typically a prerequisite for good decision-making. The second pertains to the interpretability of recommendations, which is crucial for enterprise decision-making settings. The third challenge is the silos between data scientists and business users, hindering effective collaboration. This paper outlines …

adoption ai solution causal inference challenge challenges cs.lg data decision enterprise enterprises good inference insights interpretability limitations making recommendations shift solution

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