![opened_golden_safe_amid_abstract_structures_security_wealth_investment_by_violka08_gettyimages-1167344149_2400x1600-100858618-large Why AI investments fail to deliver](https://veille-cyber.com/wp-content/uploads/2021/11/opened_golden_safe_amid_abstract_structures_security_wealth_investment_by_violka08_gettyimages-1167344149_2400x1600-100858618-large-678x381.jpg)
The success or failure of AI initiatives has more to do with people than with technology. If you want to put AI into practice in a way that improves business outcomes, you must avoid these 6 mistakes.
According to two recent Gartner reports, 85% of AI and machine learning projects fail to deliver, and only 53% of projects make it from prototypes to production. Yet the same reports indicate little sign of a slowdown in AI investments. Many organizations plan to increase these investments.
Many of these failures are avoidable with a little common-sense business thinking. The drivers to invest are powerful: FOMO (fear of missing out), a frothy VC investment bubble in AI companies with big marketing budgets, and, to some extent, a recognition of the genuine need to harness AI-driven decision-making and move toward a data-driven enterprise.