The AI Maturity Gap: Leaders Overestimate AI Readiness and Workers Lack Training

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By PR Newswire Last updated Sep 26, 2024

A widening ‘AI maturity gap’ threatens business performance as leaders significantly overestimate their organizations’ AI readiness while employees lack crucial training.

This is according to a new report from AI skills platform, Multiverse, which reveals stark differences between executives and workers over AI effectiveness, how to measure impact, and the need for training and skills. Multiverse believes the disconnect threatens to undermine AI’s return on investment (ROI) and economic growth potential.

The study, which surveyed 810 business leaders and 1,190 employees across the US and UK, exposes a stark contrast between leadership optimism and on-the-ground realities in AI implementation.

Key findings include:

96% said customer and user experience has improved over the last 12 months due to AI.
Four in five tech leaders say implementing AI has led to an increase in revenue generation.
Improved productivity and operational efficiency (96%) are another key benefit – while almost half (48%) say that AI has helped to decrease unnecessary external costs in the last 12 months.

However, there are clear signs of a disconnect:

61% of leaders believe AI is fully implemented across their organization, compared to only 36% of workers
60% of leaders think they’re ahead of competitors in AI maturity, while only 46% of workers agree
Leaders say their biggest blocker to further investment is the inability to fully use existing AI technology (63%), followed by resistance from employees to use AI (58%).
56% of self-proclaimed ‘AI experts’ have had no formal training.
Notably, 45% of organizations categorized by Multiverse as “AI Beginners” still consider AI fully implemented, highlighting a significant perception gap.

Euan Blair, CEO and founder of Multiverse: “AI looks set to upend every aspect of our working lives, if not our lives altogether. The financial promise is huge and optimism is high. But organizations are rushing to implement AI without the necessary foundations in place. To build truly AI native businesses, where AI is baked into your organizational DNA and delivering maximum ROI, tech investments need to be combined with an AI-enabled workforce equipped with the skills and tools to leverage AI to its full potential, not only to realize the true value of the technology, but to proactively mitigate risk.”

The report introduces an AI Maturity Modeland categorized respondents accordingly:

AI Beginner (22%): Proof of concept stage, developing pilot projects
AI Explorer (51%): Early stage, integrating AI into specific business processes
AI Adept (27%): Fully integrated, embedding AI throughout the organization

The findings reveal a significant gap in organizations’ ability to measure and optimize the ROI of their AI initiatives.

While 49% of business leaders say they track AI’s return on investment (ROI), only 44% use this data to improve their AI projects. This gap is holding back further AI adoption, with 57% of leaders saying they can’t clearly show or predict AI’s benefits.

The numbers reveal a significant challenge: although nearly half of companies are trying to measure AI’s impact, many find it difficult to turn these insights into concrete improvements or to justify additional AI spending. The data suggests a clear need for better methods to assess and communicate the value of AI initiatives in business terms.

The skills gap is also evident with 56% of self-proclaimed ‘AI experts’ having received no formal training. This overconfidence raises ethical and data-security questions:

93% of workers are confident they used AI ethically in their last application
90% believe they kept their organization’s data safe
However, only 28% of organizations have established best practices in AI governance and risk management.

Anna Wang, Head of AI at Multiverse said: “As AI evolves, organizations must become AI native to harness its full ROI. However, because of the newness of the technology and the pace of change, many organizations are struggling to get a clear view of their own progress. It’s hard to know what you don’t know. This means best practice isn’t necessarily being established – creating risks and potential missed opportunities for the future.”

To address these challenges, the report from Multiverse recommends:

Developing standardized AI skills assessments
Creating industry-wide AI governance frameworks
Increasing investment in AI education at all levels
Conducting regular audits of AI systems and their economic impact

Multiverse also announced plans to develop a global AI Readiness Index, set to launch in Q2 2025, providing a standardized measure of organizational and national AI maturity.

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