ROI Crisis in AI Investments: Why Companies Are Failing to Meet Expectations

Why Are Expected Returns on AI Investments Not Materializing?

Forbes' latest research has brought a critical truth about artificial intelligence (AI) investments in the business world to light: Many companies are failing to achieve the expected return on investment (ROI) from the significant budgets they allocate to this field. A growing gap between the technology's shiny promises and tangible financial results is drawing attention. This situation necessitates a deep analysis of why AI projects fail and how companies can escape this trap.

According to experts, three main interconnected factors lie at the heart of the crisis: unrealistic, exaggerated expectations; implementation errors stemming from technological infrastructure and human resources; and pressure created by fluctuations in the global economy. While companies tend to view AI as a magic wand, they actually need to be prepared for a complex, disciplined, and long-term transformation process.

ROI Criteria Are Changing: Traditional Approaches Are Falling Short

One dimension of the crisis is also occurring in the criteria used to measure the success of artificial intelligence. Purely financial indicators like traditional return on investment (ROI) or efficiency increases can fall short in fully reflecting the impact of AI projects. Qualitative criteria such as accuracy, reliability, transparency, explainability, and user experience are becoming much more critical, especially in ethics and regulation-focused sectors. An AI model's inability to explain its decision-making process can create costs, such as legal risks and brand reputation loss, which are not easily measured by traditional accounting metrics.

At this point, as emphasized in the Ethical Declaration on Artificial Intelligence Applications published by the Ministry of National Education, the principle that technology should be used only to support clear objectives and enhance quality can also serve as a guide for the business world. AI investments must be tied to a clear business strategy and concrete problem-solving approaches. The transformation requires not just technological adoption but also organizational change management, employee training, and the development of ethical governance frameworks. Companies that focus on incremental, value-driven implementations rather than chasing hype are more likely to see sustainable returns and navigate the current ROI crisis successfully.