Charles Willow, Ph.D., associate professor in the Leon Hess Business School, recently published an article in the Journal of Technology Research (Vol. 13, 2026) examining how artificial intelligence can be used to predict inflation while addressing potential biases in AI-generated results.
In “Inflation Predictor Model Using Artificial Intelligence and Deep Machine Learning,” Willow developed a traditional artificial intelligence (TAI) model to predict potential global inflation. The model incorporates economic and global indicators, including commodity prices, gross domestic product, conflicts, and pandemics. His research compares the specialized TAI approach with generative AI (GAI) tools and examines concerns that data and algorithmic biases in GAI could affect business decision-making.
The model predicts inflation in 2030 with 95% confidence, while also predicting no inflation for 2050 and 2060. Willow concludes that purpose-built AI models may provide more reliable and consistent results than general-purpose generative AI for specialized business applications.
The research is part of Willow’s ongoing studies examining artificial intelligence, including AI agents, agentic AI, social responsibility, and the potential use of AI in Social Security privatization.