Artificial intelligence (AI) plays a growing role in business, driving innovation, efficiency, and optimization. However, evaluating the economic feasibility of AI projects presents unique challenges. This paper explores key difficulties in assessing AI investments by conducting a critical literature review and case study analysis. The study highlights financial, organizational, and social factors impacting AI project evaluation. The research, based on case studies across various industries, identifies major economic assessment challenges, including the inability to isolate AI’s specific impact on business performance, high data quality requirements, and compliance costs. Findings suggest that organizations require structured evaluation frameworks to better estimate AI’s return on investment (ROI) and long-term economic impact. The study concludes that AI projects demand more refined assessment approaches that go beyond traditional financial metrics, incorporating ESG (Environmental, Social, Governance) factors and broader business value considerations.