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Why Are AI and Data Projects Coming Up Short?

As data processes become more complex, many organizations struggle to get their artificial intelligence (AI) and data analytics projects to work for them. Collecting, organizing, implementing, and streamlining vast amounts of data is a lot of work that involves many different teams with varying capabilities and needs. In the infographic below, see why so many organizations are experiencing AI and data project failure and whether they think the investment is still worth it.


Why are AI and data projects coming up short.Responses from 2,037 global professionals.40% average failure rate for data science projects.What is getting in the way.Key obstacles preventing organizations deploying AI.A result of AI and data setbacks.Organizations still have hope.Altair commissioned an international online survey of 2,037 professionals.

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