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Why Do So Many Data Science And AI Projects Fail? The Missing Human Factor

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          🞛 This publication is a summary or evaluation of another publication 🞛 This publication contains editorial commentary or bias from the source
Nino Letteriello is a data and project management leader, DAMA Award winner, WEF author, UN advisor, MIT lecturer & FIT Group co-founder. A significant percentage of data science projects continue to fail.
The article from Forbes Tech Council, published on April 21, 2025, discusses the high failure rate of data science and AI projects, attributing it primarily to the neglect of the human factor. Despite the technological advancements and the potential of AI, many projects fail because they do not adequately consider human elements such as user experience, ethical considerations, and the need for human oversight. The author emphasizes that successful AI implementations require a balance between technical prowess and human-centric design, advocating for more inclusive development processes that involve diverse stakeholders to ensure that AI solutions meet real human needs and are ethically sound.

Read the Full Forbes Article at:
[ https://www.forbes.com/councils/forbestechcouncil/2025/04/21/why-do-so-many-data-science-and-ai-projects-fail-the-missing-human-factor/ ]