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In this 23-minute conference talk from DSC EUROPE 24, Matevz Cerne explores the common pitfalls that lead to AI implementation failures and provides valuable insights for avoiding these mistakes. Discover the critical issues in scope definition, including unrealistic expectations, misapplication of AI to problems better solved with simpler approaches, and the absence of clear success metrics. Learn about the crucial role of proper data preparation and the risks associated with insufficient, irrelevant, or biased datasets that can compromise AI model performance. Understand how communication breakdowns with clients—such as misinterpreting their needs, underestimating project complexity, and failing to transparently communicate challenges—can ultimately lead to project failure. This presentation, delivered on November 21st at DSC EUROPE 24 in Belgrade, offers essential guidance for professionals looking to improve their AI implementation success rates.
