LXT Releases AI Maturity Survey
Nearly half of organizations now rate themselves as AI mature and believe this will help navigate economic downturns through improved business agility, resilience, and time-to-market.
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LXT, a specialist in global AI training data, has released its second annual executive survey, The Path to AI Maturity. The new report found that organizations have evolved in their AI journeys, with 48% of respondents rating themselves at the mature level, where AI is in production or already a part of business DNA.
“As organizations continue to make progress in their AI deployments, the business value is becoming increasingly clear,” said Mohammad Omar, LXT co-founder and CEO. “Given the current economic climate, businesses see the benefit of successful AI deployments in improved business agility, business resilience, and quicker time-to-market. We are pleased to see that over 80% of enterprises have implemented a data strategy to drive the success of their AI initiatives.”
LXT, in partnership with research firm Reputation Leaders, commissioned a survey in late 2022 of 315 senior decision makers with verified relevant AI experience at U.S. firms with annual revenue of over $100 million and a company size of more than 500 employees.
At 48% of organizations, AI is in production or already a part of business DNA. In the survey, executives were asked to place their companies on the Gartner AI Maturity Model scale. Nearly half reported that their organizations have reached AI maturity (48% vs. 40% in 2021), improving from Operational (AI in production, creating value) to Transformational (AI is part of business DNA). However, 46% of all AI projects on average still fail to reach their goals, although success improves with greater maturity. The top challenges in getting to AI maturity are a balance of technology (integration, quality data) and human (talent, training) factors.
AI investment remains strong, with nearly half of organizations investing $76 million or more annually. Of all organizations, 49% invest $76 million or more annually in AI, while only 1% spend $1 million or less. For companies with revenue over $500 million, 58% invest more than $75 million. Training data and product development accounted for the largest share of AI budgets; 87% are willing to spend more for higher-quality AI training data.
AI strategies are primarily driven by the need for business agility, anticipating customer needs, and technological innovation -- cost savings is not a dominant driver. To support these strategies, the most mature organizations rely more on supervised machine learning methods.
NLP and speech/voice recognition are the most highly deployed AI applications. Natural language processing (NLP) and speech/voice recognition solutions are the most highly deployed AI applications, followed by predictive analytics and conversational AI (CAI). There were just two industries where NLP and speech/voice recognition solutions were not the top applications deployed: financial services (financial reporting) and manufacturing/supply chain (robotics). However, in an open-ended question, organizations cited CAI applications as having the greatest ROI.
More than 90% say they have made good or excellent progress in managing AI bias. “The importance of responsible AI is top of mind in most organizations,” commented Phil Hall, LXT chief growth officer. “Diversity in data and the workforce behind it is essential to success in managing bias.” The survey found that data diversity and risk management are extremely or very important to more than 90% of respondents. Nine out of ten believe they have made excellent or good progress when it comes to managing bias in AI models. The most important way stated by respondents to ensure this is to manage diversity in annotation teams.
To learn more and review the complete findings, download The Path to AI Maturity report. Short registration is required for access.