Commissioned by artificial intelligence (AI) software provider Monolith, Forrester Consulting’s study – titled The State of AI in Engineering – surveyed 163 senior engineering leaders at multinational automotive, aerospace and industrial/manufacturing enterprises in the US and Europe.
The study is claimed to be the first of its kind around engineering product development, revealing the challenges and key priorities that engineering leaders face in the validation and verification stage of the development workflow.
“The perfect storm is brewing in engineering as market trends around sustainability and digitalisation are creating even more intractable physics problems that current validation and testing methods are unable to solve," Dr Richard Ahlfeld, CEO and founder of Monolith said in a statement. "As data from this study shows, engineering leaders are at a fork in the road to innovate in new ways as pressure to stay profitable and competitive rises."
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The survey found that engineers are feeling pressure to introduce products to market faster with 71 per cent of engineering leaders indicating they need to find ways to accelerate product development to stay competitive.
To compound the challenge, the new data reveals that many engineering leaders feel unequipped to effect change, with 55 per cent of those surveyed stating that they lack the required tools, and that existing virtual validation and simulation tools are insufficient.
The severity of the impact of these deficiencies on business success is reflected in the survey results, with 82 per cent of respondents noting that a one-month delay in product launch costs their business millions, or even billions, of US dollars.
While existing physical testing and simulation methods fall short in meeting engineers’ needs for product designs to pass validation, industry leaders see AI as being ideally placed to empower their efforts in producing highly effective solutions for the market, and delivering commercial success. According to the research, engineering leaders who have already implemented AI are 43 per cent more likely to see an increase in revenue, profitability, and competitiveness compared to those who haven’t.
Despite this, many engineering organisations are missing out on the full potential of advanced AI technology; less than 19 per cent of engineering leaders reported using unsupervised learning algorithms to analyse historic or current test data, and less than half utilise any of their engineering test data.
Dr Ahlfeld said: “With AI, engineering domain experts can quickly understand and instantly predict complex physics, allowing them to test less, learn more and get to market much quicker. The new insights we have uncovered via the Forrester study underline just how crucial the widespread implementation of technologies such as AI has become. The industry now needs to take the necessary steps to prepare itself for a data-driven future.”
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