Why 85% of AI projects fail

Despite increased interest in and adoption of artificial intelligence (AI) in the enterprise, 85% of AI projects ultimately fail to deliver on their intended promises to business, according to a Thursday report from Pactera Technologies.

A major source of AI challenges is found in senior leadership, the report, titled Artificial Intelligence Localization, Winners, Losers, Heroes, Spectators, and You, found. Some 77% of those surveyed said they face barriers to entry from senior management not seeing value or wanting to make the investment in the emerging technology.

SEE: Special report: Managing AI and ML in the enterprise (free PDF) (TechRepublic)

These findings are in line with those from a recent Dimensional Research report, which found that eight out of 10 organizations engaged with AI and machine learning said those projects had stalled, and 96% said they have run into problems with data quality, data labelling, and building model confidence.

Pactera presented the report to a group of tech industry leaders including those from Facebook, Adobe, Amazon, and Microsoft at a recent private event in Seattle. At the event, 100% of leaders said they want to use tools like AI-powered Neural Machine Translation (NMT) because it would allow them to quickly localize content in at least 72 languages. However, only 23% said they currently use the technology, demonstrating that organizations are still cautious about adopting new AI-related technologies, the report noted.

“Interestingly enough, human vision, guidance and input ultimately play a big part of an AI project’s success,” Jose Martinez, vice president of digital innovations and solutions at Pactera, said in a press release. “Identifying business goals that AI can readily achieve, like Neural Machine Translation, and managing the teams that scrutinize data is what ultimately improve a business’s leveraging of AI.”

For more, check out 5 ways to improve AI/ML deployments at TechRepublic.

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