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7 reasons analytics and ML fail to meet business objectives [Video]

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Data analytics and machine learning can deliver real business value, but too many projects miss their mark. Here are seven mistakes to watch out for, and what to do instead.

Credit: iStock

Foundry’s State of the CIO 2024 reports that 80% of CIOs are tasked with researching and evaluating possible AI additions to their tech stack, and 74% are working more closely with their business leaders on AI applications. Despite facing the demand for delivering business value from data, machine learning, and AI investments, only 54% of CIOs report IT budget increases. AI investments were only the third driver, while security improvements and the rising costs of technology ranked higher.

CIOs, IT, and data science teams must be careful that AI’s excitement doesn’t drive irrational exuberance. One recent studyshows that the most important success metrics for analytics projects include return on investment, revenue growth, and improved efficiencies, yet only 32% of respondents successfully deploy more than 60% of …

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