The Effects of Artificial Intelligence on Firms’ Internal Information Quality

Andrea Rozario, Chanyuan (Abigail) Zhang

Research output: Working paper

Abstract

This study explores whether the implementation of artificial intelligence (AI) in firms’ operations is associated with improvements in firms’ internal information quality (IIQ), as reflected in the quality of management earnings forecasts. We identify non-technology firms that have implemented AI in their operations from 2014 to 2018. We find that AI is associated with more accurate management earnings forecasts after its implementation and that it can more profoundly improve the accuracy of the first management earnings forecast compared to the last. Finally, we find that machine learning (ML) is the primary AI technology that contributes to the improvements in the accuracy of management earnings forecasts. We contribute to the literature by providing initial archival evidence about the association between AI implementation and improvements to IIQ.
Original languageEnglish (US)
DOIs
StatePublished - May 24 2021
Externally publishedYes

Keywords

  • Artificial Intelligence
  • Internal Information Quality
  • Management Earnings Forecasts
  • Forecast Accuracy

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