AI as a Decision Companion: Supporting Executive Pricing and FX Decisions in Global Enterprises Through LSTM Forecasting

Wesley Leeroy () and Gordon C. Leeroy
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Wesley Leeroy: School of Engineering and Applied Science, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA 19104-6389, USA
Gordon C. Leeroy: Department of Accounting, McCombs School of Business, The University of Texas at Austin, Austin, TX 78712-1179, USA

JRFM, 2025, vol. 18, issue 10, 1-19

Abstract: Global enterprises face increasingly volatile market conditions, with foreign exchange (FX) movements often forcing executives to make rapid pricing and strategy decisions under uncertainty. While artificial intelligence (AI) has transformed operational decision-making, its role in supporting board-level strategic choices remains underexplored. This paper examines how AI and advanced analytics can serve as a ‘decision companion’ for management teams and executives confronted with global shocks. Using Roblox Corporation as a case study, we apply a Long Short-Term Memory (LSTM) neural network to forecast bookings and simulate counterfactual scenarios involving euro depreciation and European price adjustments. The analysis reveals that a ten percent depreciation of the euro reduces consolidated bookings and profits by approximately six percent, and that raising European prices does not offset these losses due to demand elasticity. Regional attribution shows that the majority of the decline is concentrated in Europe, with only minor spillovers elsewhere. The findings demonstrate that AI enhances strategic agility by clarifying risks, quantifying trade-offs, and isolating regional effects, while ensuring that ultimate decisions remain with human executives.

Keywords: artificial intelligence (AI); machine learning (ML) executive decision-making; foreign exchange (FX) risk; long short-term memory (LSTM); scenario simulation; agent-based modeling (ABM); global enterprise strategy (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2025
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