Finding Value with AI and Industry 5.0 Transformation

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Finding Value with AI and Industry 5.0 Transformation

“To realize the promise of Industry 5.0, companies must move beyond cost and efficiency to focus on growth, resilience and human-centric outcomes,” says Sachin Lulla, industrial and energy transformation leader at EY Americas. “This requires not only new technologies, but also new ways of working – where people and machines collaborate, and where value is measured not only in dollars saved, but also in new opportunities created.”

An MIT Technology Review Insights survey of 250 industry leaders from around the world shows that most industrial investments still target efficiency. And while data shows that human-centered and sustainable use cases deliver high value, they are underfunded. Research shows that most organizations are not realizing the full value potential of Industry 5.0 due to a combination of the following:

• Culture, skills and collaboration barriers.
• Strategic and misaligned technology investments.
• Use-case prioritization focuses on efficiency over growth, sustainability and welfare.

According to research from EY and Said Business School at the University of Oxford, the hurdle to achieving Industry 5.0 transformation is not just about getting the technology right, but also about strengthening human-centric elements such as strategy, culture and leadership. Companies are investing heavily in digital transformation, but not always in ways that unlock the full human potential of Industry 5.0.

“We’re not doing digital work just for the sake of work, which I call ‘chasing digital fairies’,” says Chris Ware, general manager of iron ore digital at Rio Tinto. “We have to be very clear on what we do and why. Each domain has a unique roadmap on how to deliver the best value.”

Download the full report.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by the editorial staff of MIT Technology Review. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes writing surveys and collecting data for the surveys. The AI ​​tools that may have been used were limited to secondary production processes that underwent thorough human review.

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