C-suite executives are paid to make good decisions. That’s why many don’t trust AI to make the right call.
Is AI ready to deliver accurate information outputs?
Not yet, say a surprisingly high percentage of executives who may be doubting their company’s artificial intelligence strategy.
The data comes from Teradata, an artificial intelligence data analysis company that released the survey with NewtonX Trust, a marketing services company.
According to the data, while 56% of executives think their companies have a “clear” AI strategy, only 40% are reasonably confident their data is “not ready “for accurate AI outputs. “That’s not much better than a coin-flip difference between trusting AI outputs and not,” the report said.
Teradata said executives believe they have good reasons to doubt AI-related project outcomes. According to the study, key factors impeding AI project “scale-ups” include the following barriers.
— Scarcity of AI technical talent (39%).
— Lack of budget required to scale AI projects (34%).
— Difficulty in measuring business impact (32%).
— Insufficient technology infrastructure (32%).
Bad Timing
The study comes at a time when Teradata said 84% of senior-level respondents say they’re closing in “year one” AI project outcomes, with 58% saying those results will go live within six months,
“The foundation of AI is clean, reliable, trustworthy data because it is the backbone of AI outputs,” said Jacqueline Woods, Chief Marketing Officer at Teradata. “While achieving complete trust remains elusive for many executives, our survey shows a deepening understanding of how to reach trusted AI at enterprise-scale and confirms that Teradata is well positioned to help its customers with these business objectives.”
“Trusted AI” may be a concept lacking conviction among C-suite executives. Just 28% of senior company leaders say their AI strategy “is closely aligned” with and supports broader business objectives.
Teradata leaves some clues for executives looking for a clear path forward. According to the report, the best AI deployments occurred at the departmental level. Only 12% of companies surveyed say they’ve successfully deployed AI solutions company-wide, while 39% of executives have implemented AI in “select” departments.
To be safe and to generate workers’ productivity, executives tasked with tackling AI projects say they wish to do so by “enhancing internal processes.” That’s because these projects “tend to minimize AI risks and are seen as more likely to improve cost control rather than drive growth,” Teradata noted.
Ticking off customers is another reason execs aren’t confident in their AI deployments, even those that appear to generate higher productivity among the workforce. For those decision makers, annoying customers is too risky to take any chances with unproven technologies.
“More than half (57 percent) of executives surveyed said they are concerned about how AI missteps could impact customer satisfaction, company reputation, or both, noting that there needs to be greater cohesiveness between AI and business planning for it to be successful,” Teradata said. “Even with internal projects, 63 percent of executives surveyed report using a mix of closed and public data sets, while only 29 percent rely exclusively on closed data sets.”
The study tracked C-suite executives and AI decision-makers at large companies (e.g., at least 1,000 employees and $750 million in annual revenue).
Brian O’Connell, a former Wall Street bond trader and best-selling author, is a prominent figure in the finance industry. With a substantial background as an ex-Wall Street trader, he has authored two best-selling books: ‘The 401k Millionaire’ and ‘CNBC’s Creating Wealth’, demonstrating his profound knowledge of finance and investing.
Brian is also a finance and business writer for esteemed national platforms and publications, including CNN, TheStreet.com, CBS News, The Wall Street Journal, U.S. News & World Report, Forbes, and Fox News.
