Survey Confirms Technology Pressures and Skills Gaps in Engineering.

Will artificial intelligence replace your job? Or instead, will you be replaced by someone who knows AI? 

We asked these questions to employees and executives across the engineering industry to see how AI is impacting work in their sectors today, among other high-priority skills. 

The responses show that technology is being embraced by leaders faster than employees. Data science, Al/ML, and automation remain priority skills. But workers see limited support for upskilling. 

Today's engineering landscape is facing an unprecedented wave of technological pressures. Nowhere is this felt more keenly than in the race to adopt artificial intelligence and automation. Our surveys reveal a critical gap between the pace of technology adoption and engineering workforce readiness, underscoring the urgency for organizations to invest in more upskilling and reskilling.  

AI, machine learning, and data science are skills in high demand, yet many workers need more support in these areas. Companies need to bridge this gap by offering regular, targeted engineering AI training programs and clear career pathways to boost employee confidence and readiness. 

AI Adoption from the View of Executives and Employees. 

In a landmark survey on the future of work, we asked leaders and talent each a slightly different question: To what extent do you agree or disagree with the following statement? 

• Leaders: Refusal or reluctance to adopt Al is a bigger threat to workers' jobs than Al itself. 
• Talent: I don't believe Al is likely to replace me, but someone who masters how to use Al might.
   

Executives and leaders. 

The survey confirms what executives and leaders broadly recognize, with a total of 69% in agreement that failure to embrace Al poses risks to competitiveness and workforce stability. On average, more either “strongly agreed” (33%) or “somewhat agreed” (36%) with the statement. 

Less than average (58%) of leaders in our Industrial Manufacturing category agreed that reluctance to adopt Al is a bigger threat to workers’ jobs than Al itself. More than average (73%) agreed among the Robotics and Semiconductor executives. 

The greater threat is hesitation and inaction rather than Al itself. This highlights the need for leadership alignment and clear adoption strategies.  

Talent and employees. 

63% of workers agree that Al won't replace them, but someone who knows how to use Al might. On average, workers from the survey either “strongly agreed” (19%) or “somewhat agreed” (44%) with the statement. 

Industrial/Manufacturing workers are even more sure (70% agreed) about the statement, while Robotics and Semiconductor employees express more skepticism and concern about displacement (57% agreed). So, employees largely don’t see Al as a direct job replacement.  

How then is AI changing engineering careers? Workers recognize Al literacy as a critical skill for employability. Upskilling is key: All industries and participants confirm that Al mastery, not Al itself, will determine your career resilience moving forward.  

The Re:work survey underscores that both executives and talent agree on the high stakes: reluctance to adopt AI in engineering poses a bigger threat to jobs than the technology itself. While many leaders embrace the opportunity, workers are more concerned about being replaced by peers who master these emerging tools.  

To alleviate such concerns, organizations should focus on fostering a culture of continuous learning. Encourage collaboration between tech-savvy employees and those looking to build their expertise. Make upskilling a core part of your professional development. 

Talent and Executives Identify the Same Workforce Skills Gaps. 

We then asked executives, “Where do employees usually experience a gap in skills?” They see Al/ML and data science as universal priority gaps. See the chart for the key responses indicated by all our STEM participants.

Executives and leaders. 

What skills are most in demand in engineering in 2025? As you might expect, artificial intelligence or machine learning were the top skills gaps listed by our executives, at 70% for Industrial Manufacturing and 66% for our Technology Engineering sectors. Second on their list was skill in data science or big data, at 46% and 47% respectively. 

After the top two, the industries diverged deeper into their specialties. Industrial Manufacturing leaders saw process automation (40%) as their next largest skills gap, followed by basic soft skills (32%) like adaptability or leadership. Across Robotics and Semiconductors, leaders noted cybersecurity (46%) and systems thinking (40%) as the next biggest holes to fill.

Talent and employees. 

We asked employees a related question, to capture their perspective on the same list: “Where do you feel you lack the necessary skills?" Workers themselves confirm what executives and leaders flagged: AI/ML, data science, and big data are the most critical gaps. 

While the industries noted different skills gaps, it’s interesting that both executives and workers agreed on the biggest shortages in those sectors—although often with less confidence. For instance, AI or ML was the top gap cited most often by 70% of execs in Industrial Manufacturing, but just 56% of workers.  

Meanwhile, cybersecurity was noted by 46% of leaders, and 35% of employees in our Technology Engineering sector. Leaders may take note of where these differences are greatest to help manage any gaps in perception as they build each skill set in their organizations. 

Transforming Optimism into Action. 

As technology continues to transform engineering sectors, leaders must turn their optimism into credible action. Closing engineering skills gaps is not just a business imperative—it’s key to future workforce sustainability.  

Why should engineering leaders focus on upskilling? The data makes it clear: AI and machine learning, along with data science, are universal gaps, and targeted support here will pay dividends for retention and competitiveness. To address this, companies should invest in high-impact learning programs. Also, regularly measure your progress to ensure skill-building is effective and aligned with your market needs. 

Moving forward, bridging the divide between executives and employees on skill perceptions will be crucial. Leaders can provide clear communication about the strategic importance of technology adoption in manufacturing and other engineering sectors, while building inclusive training frameworks that invite participation from every level.  

By empowering your talent and prioritizing actionable skills development, your organization will not only navigate its technology pressures, but begin to thrive in an increasingly automated world. 

The Re:work 2025 Surveys in Context. 

These engineering specialty insights were drawn from the broader 2025 Kelly Global Re:work Report, a landmark study on the future of work, based on insights from 6,000+ professionals worldwide. It includes three key surveys: 

• Global Workforce Survey – Insights from executives and workers across 13 countries. 

• U.S. STEM Survey – Focused on science, technology, engineering, and mathematics sectors. 
• Business Professional & Industrial Survey (U.S., Canada, Mexico, Puerto Rico) – Perspectives from business, industrial, and professional talent.
   

Within engineering, the report reveals widening gaps between executives and talent on topics such as: 

• Economic outlook and industry confidence. 

• Adoption of Al and automation. 

• Skills gaps and upskilling effectiveness. 
• Trust, morale, and DEI commitments. 
   

Engineering Industry Segments and Specialties from our Surveys. 

The engineering specialty spans many core industries that form the backbone of global production and innovation. For our surveys, these sectors fell neatly under two main umbrellas: 

We examine the results from the viewpoint of those two main categories, Industrial Manufacturing and Technology Engineering. 

Q&A 

What are the biggest technology pressures in engineering? 

 → AI, machine learning, and data science dominate as the top skills gaps across all engineering sectors, according to the Kelly Rework 2025 Report. 

Why is upskilling critical in engineering? 

 → Leaders and employees agree: reluctance to adopt AI is a bigger threat to jobs than the technology itself. 

How can engineering organizations bridge the AI skills gap? 

 → By offering targeted, ongoing upskilling programs and aligning leadership with worker readiness. Kelly Engineering partners with companies to do exactly that.