In a recent discussion on HBR IdeaCast, Iavor Bojinov highlighted the challenges faced by organizations in executing AI projects, with a staggering 80% failure rate. He explained that unlike IT projects, which typically yield consistent results, AI projects are probabilistic, leading to unpredictability. Factors such as uncertainty in outcomes and project complexity contribute to these failures. Bojinov emphasized that understanding the unique nature of AI is critical for leaders to implement best practices that ensure their projects remain on track and deliver value.
AI projects differ from IT projects due to their probabilistic nature, leading to increased uncertainty and complexity, which contributes to a high failure rate.
Around 80% of AI projects fail, primarily because they are not deterministic; they can produce different outputs from the same inputs, adding layers of unpredictability.
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