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RESEARCH & RESOURCES

LXT Survey of Executives Reveals State of AI Maturity

This year’s report highlights a major shift from experimentation and pilot tests to AI in production, along with the importance of generative AI to the majority of organizations.

Note: TDWI's editors carefully choose vendor-issued press releases about new or interesting research and services. We have edited and/or condensed this release to highlight key study results or service features but make no claims as to the accuracy of the vendor's statements.

LXT, an emerging leader in global AI training data, today released its third annual executive survey, The Path to AI Maturity. This latest report found that organizations have taken large steps, with nearly three-quarters (72%) reporting they have reached higher levels of AI maturity. The most significant shift is in the mid-range, where nearly a third of companies state that AI is now in production and creating value. To achieve this, half of all organizations invest between $1 million and $50 million, and more than ten percent reported an AI budget between $50 million and $500 million. 

“Last year AI became an imperative for companies of all sizes,” said Mohammad Omar, LXT founder and CEO. “Now more than ever, organizations realize that AI is table stakes to remain competitive, and they are taking the necessary steps to grow in AI maturity. These include the prioritization of powerful technologies such as generative AI, and the use of high-quality training data.”

LXT, in partnership with research firm Censuswide, commissioned a survey in late 2023 of 322 senior decision-makers (more than half from the C-suite) with verified relevant AI experience at US firms with annual revenue of over $100 million and a company size of more than 500 employees.

Shift in AI Maturity

Executives were asked to place their companies on the Gartner AI Maturity Model, and nearly three-quarters (72%) report that they have reached one of the higher levels of maturity (compared to 48% in the 2023 report and 40% in 2022). These stages range from Operational, where AI is in production and creating value, to Transformational, where AI is part of the business DNA.

The greatest shift in AI maturity across all three years is represented by the move from Active to Operational, with the largest jump in this year’s survey. Nearly one-third (32%) report that their organizations have reached the Operational stage, the first of three mature stages. This stage is now the most common AI maturity level, whereas in past years it was the Active stage where companies are undergoing initial experimentation and pilot projects with AI.

To fund these moves, half of all organizations invest between $1 million and $50 million, and more than ten percent (13%) reported an AI budget between $50 million and $500 million.

Importance of Generative AI

According to 69% of respondents, generative AI is more important to their organizations than other AI initiatives, and 11% say it is much more important. The three top uses for generative AI include creating documentation (38%), improving decision-making (36%) and marketing (35%). Only 1% of all organizations do not use generative AI solutions.

Organizations are sourcing the data to train their generative AI solutions by using internal data (36%), collecting data externally through a third party (35%), collecting data externally themselves (35%), and by using publicly available data sets (32%). The biggest bottlenecks include security and privacy concerns (39%), accuracy of the output (38%), and the availability of quality training data (36%).

Despite the value placed on generative AI applications, only 12% of companies have deployed them so far, and only 5% say that they deliver the greatest return on investment (ROI).

Data-centric AI

The majority of respondents stated that their needs for training data will increase in the next two to five years. Nearly twice as many stated that data quality (62%) is more important than data volume (38%) for AI project success, a finding in line with today’s data-centric AI approaches.

Top categories for the ROI of high-quality training data include time-to-market acceleration (32%), higher success rates of AI programs (32%), and increased customer satisfaction (31%).

To learn more and review the complete findings, download The Path to AI Maturity report (short registration required).

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