Training gap slows widespread AI adoption

The ‘TE Connectivity Industrial Technology Index’ is an annual report that analyses the current drivers of innovation, based on the responses of 1,000 engineers and executives from China, Germany, India, Japan, and the US. It focused heavily this year on how companies are handling the integration of AI as it becomes a business imperative.

Globally, the survey found that AI adoption is widespread, with 68% of engineers and 70% of executives reporting their company has integrated it to “some extent.” The desire to learn is strong among engineers, yet 42% of executives say their company is not providing training in AI. That may be one of the reasons only 22% of respondents across all five countries report "extensive" adoption of AI in their company.

Survey results indicated that engineers are eager for their companies to lead the way on training and realise that upskilling their workforces will help them use AI tools to their full potential. The training gap is broader in the US, where less than half of executives said their company offers training programmes; it’s less of a gap in Japan and India, where approximately three-quarters of companies offer AI training.

The survey also found disparities in training availability across industries. In both industrial machinery and automotive and commercial transportation, more than half of respondents (55%) said their organisations either haven’t provided AI training or otherwise believe that AI training/upskilling resources are not available.

Nathan Myer, a product development engineer at TE, offered insight into what early career engineers are seeking in an AI training programme. He says a multi-tiered approach that starts with the basics and goes deeper based on a person’s job duties makes the most sense to him.

“Real world examples of the technology in action are key,” Myer says. “One of the things I often struggle with is how to integrate AI in my daily tasks. It’s important to explain the thought process behind identifying the problem, selecting the right type of AI to use and implementing the solution.”

The survey also found that AI adoption rates vary by country. In China, 28% of respondents say their company is using AI extensively and 60% indicate their company has been using AI for at least three years. In contrast, just 15% of respondents in the US say their company is using AI extensively and only 9% say that their company has been using AI for at least three years. In the other countries surveyed, 51% of Japanese respondents say their company has been using AI for at least three years, compared to 38% of Germans and 29% of Indians.

Beyond improvements in productivity, companies that invest in AI could also see a positive impact on their job applicant pipeline, as 80% of the engineers surveyed expressed a desire to work for an organisation that prioritises AI integration. The data show a majority of engineers expect AI to be a large part of their jobs – 81% believe AI will help solve complex problems they currently face, and 73% expect organisations to make AI integration a core part of their company culture.

Since engineers are embracing AI and the companies who are early adopters, TE’s Chief Human Resources Officer Malavika Sagar believes it is imperative that companies understand how to communicate their AI strategy with job seekers.

“Companies should showcase their progress in AI with specific use cases,” Sagar says. “This sends a clear signal to candidates that we’re forward thinking, we value innovation and we’re investing in the future.”

The 2025 Industrial Technology Index also provides a look at the relationship between innovation and sustainability. While long-term sustainability goals have not shifted, organisations are citing external challenges in meeting their goals. Globally, companies agree that economic constraints and competitive market pressures are limiting the investment in innovations to make an organisation more environmentally sustainable. However, Holly Webdale, TE’s vice president of ESG and facilities, says companies should remember that there is longer-term savings in many sustainable efforts.

“Faced with a multitude of economic pressures outside of their control, organisations should take a pragmatic approach to environmental sustainability to continue to pursue their short-term goals. Savings derived from something like an energy efficiency project can free up capital to be invested in further projects,” she says.

As companies look to the future of both AI and sustainability, one can advance the other, says Phil Gilchrist, TE’s Vice President and Chief Transformation Leader for AI and sustainability.

“In nearly all things, AI leads to more sustainable outcomes because, given the right input, AI creates less waste and discovered the right balance point between many competing constraints,” he says.

See the full TE Connectivity 2025 Industrial Technology Index at te.com/techindex.