Despite almost 80% of industrial companies not knowing how to use AI, over 80% of companies expect the technology to provide new services and better results.

Technology is not the silver bullet that guarantees digital transformation success. 

Research from McKinsey shows that 70% of digital transformation efforts fail to achieve their stated goals. In many cases, the failure of a digital transformation stems from a lack of strategic vision. Successfully implementing a digital transformation doesn’t just mean buying new technology. Success comes from integrating that technology in a way that supports an overall business strategy.

Digital transformation strategies are widespread enough that the wisdom of strategy over shiny new toys would appear to have become conventional. However, in the industrial manufacturing sector, new research seems to indicate business leaders are in danger of ignoring reality in favour of the allure posed by the shiniest new toy to hit the market in over a decade: artificial intelligence (AI). 

Industrial leaders expect AI to deliver… but don’t know what that means

A new report from product lifecycle management and digital thread solutions firm Aras, has highlighted the fact that nearly 80% of industrial companies lack the knowledge or capacity to successfully implement and make use of AI. 

Despite being broadly unprepared to leverage AI, 84% of companies expect AI to provide them with new or better services. Simultaneously, 82% expect an increase in  the quality of their services. 

Aras’ study surveyed 835 executive-level experts across the United States, Europe, and Japan. Respondents comprised senior management decision-makers from various industries. These included automotive, aerospace & defence, machinery & plant engineering, chemicals, pharmaceuticals, food & beverage, medical, energy, and other sectors. 

One of the principal hurdles to leveraging AI, the report found, was lacking access to “a rich data set.” Across the leaders surveyed, a majority agreed that there were multiple barriers to taking advantage of AI. These included lacking knowledge (77%), lacking the necessary capacity (79%), having problems with the quality of available data (70%), and having the right data locked away in siloes where it can’t be used to its full potential (75%). 

Barriers to AI adoption were highest in Japan and lowest in the US and the Nordics. Japanese firms in particular expressed concerns over the quality of their data. The UK, France, and Nordics, by contrast, were relatively confident in their data. 

“Adapting and modernising the existing IT landscape can remove barriers and enable companies to reap the benefits of AI,” said Roque Martin, CEO of Aras. “A more proactive and company-wide AI integration, from development to production to sales is what is required.”

  • Data & AI
  • Infrastructure & Cloud

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