Explainable Artificial Intelligence (XAI) in Management and Entrepreneurship: exploring the applications and implications

• Author(s): Adebayo Rotimi Philip
• Paper ID: 1708573
• Page: 2336-2349
• Published Date: 19-06-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 8 Issue 11 May-2025

Abstract

Explainable AI (XAI) is a crucial aspect of AI model development. Success in XAI will skyrocket the use of AI in management and entrepreneurship, especially in crucial decision-making and resource allocations. This study evaluates how XAI enhances trust in decision-making, assesses the key applications of XAI in management and entrepreneurship, and considers the challenges and ethical considerations that arise in the adoption of XAI in management and entrepreneurship. Existing literature was explored and concrete conclusions were drawn from that literature. Findings show that AI solutions have proven to be effective in business operations etc., however, AI solutions present a huge challenge. High-accurate AI solutions are not explainable. This study shows that managers and entrepreneurs are likelier to trust AI solutions if they are interpretable. Besides, the literature reveals that guided XAI improves confidence in decision-making, particularly in strategic planning and resource allocations. XAI is found to reduce cognitive bias, promote transparency and accountability, and also address ethical concerns.

Keywords

Explainable AI, entrepreneurship, management, SHAP, LIME, Post hoc AI, black box, white box, interpretability, explainability, transparency

Citations

IRE Journals:
Adebayo Rotimi Philip "Explainable Artificial Intelligence (XAI) in Management and Entrepreneurship: exploring the applications and implications" Iconic Research And Engineering Journals Volume 8 Issue 11 2025 Page 2336-2349

IEEE:
Adebayo Rotimi Philip "Explainable Artificial Intelligence (XAI) in Management and Entrepreneurship: exploring the applications and implications" Iconic Research And Engineering Journals, 8(11)