Artificial Intelligence: How to Expand Its Adoption

Abstract

Objective: This study explores the current challenges and opportunities for expanding the adoption of Artificial Intelligence (AI) in business environments, with a focus on fostering trust and transparency in AI systems.

Method: The research adopts a case study approach, examining the implementation of AI in various sectors. It also reviews existing literature on AI technologies, including machine learning and deep learning, to evaluate their potential impact on decision-making processes.

Results: The study identifies three key factors—explainability, transparency, and mathematical certainty—that are crucial for gaining trust in AI systems. Successful AI adoption depends on addressing these elements to reduce biases and improve decision-making reliability. The case studies demonstrate how AI applications can enhance operational efficiency but also highlight the risks associated with a lack of understanding of AI processes.

Conclusion: To fully harness the benefits of AI, businesses must ensure that AI systems are transparent and explainable to users. A robust understanding of AI’s decision-making mechanisms is essential to increasing its adoption and fostering trust among stakeholders.