Artificial intelligence is so important for business success, executives said in a new survey, that most of them fear their companies will fail without it.
Seventy-five percent of executives “believe they risk going out of business in 5 years if they don’t scale AI,” according to a report released Thursday by consulting firm Accenture.
Athena Reilly, a managing director at Accenture who co-authored the report, said the findings show that there’s a “a sense of urgency at the top” about artificial intelligence. If a business ignores the technology, competitors who have mastered it are more likely to gain a big advantage.
Additionally, 76% of respondents said they are struggling to widely adopt A.I. in their businesses.
Reilly explained that such troubles are often the result of failing to properly manage corporate data. For machine-learning projects to succeed, businesses must be able to identify what data is most important to them, and then correctly clean and sort that information so it can be put to use.
“This is a big Achilles heel,” Reilly said.
Accenture’s report was based on a survey of 1,500 C-suite executives worldwide, from industries including banking, energy, life sciences, and travel.
In certain cases, corporate data management problems have ballooned to the point where some executives feel overwhelmed, and they use those problems “as an excuse” to avoid A.I. entirely, according to Reilly, telling themselves, “’I have bad data, therefore I can’t do things like A.I.’”
Adopting A.I. is not as simple as a company merely creating a chatbot or using natural language processing to parse business contracts in order to present workers with the most important information. Although these projects may have some value, they are so broad that they may fail to significantly impact the overall business. In fact, they may not deliver value at all, Reilly said.
Successful A.I. projects “need to be grounded in a business problem” with clear goals and metrics, she said. For instance, a company may want to use the technology to be more successful in collecting payments from clients. The company could set a specific goal—improving collections by a specified percent—and then use a particular statistical or A.I. technique to help achieve that goal.
“That’s grounded in a business problem, versus let’s adopt a technology,” Reilly said.
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