Engineering Tomorrow: Embracing AI for Career Development

By Neil Griffin - LinkedIn

The world has undergone significant change in the past few years. A pandemic led to dramatic transformations in everyday school and work conditions. As we exited those stages of the pandemic, the burgeoning of artificial intelligence (AI) captivated world audiences, generating feelings of excitement and tension. Much of the tension has been attributed to growing concern over job displacement. In this article, we will talk about the future of work and the role of AI in engineering roles.

Despite the projected nearly $7 trillion increase in annual global GDP over a 10 year period from increased productivity gains due to generative AI, there are increasing concerns surrounding widespread automation. According to Politico, ⅔ of occupations are deemed vulnerable to displacement by AI, corresponding to 300 million full-time jobs globally. In short, the transformative impact of AI is undeniable.

However, governments have attempted to develop policies to see the benefits of AI extend to both corporations and workers. The European Union has proposed “The AI Act,” a comprehensive law on AI for businesses in Europe, which effectively limits the risks and applications of AI. For examples, government-run social scoring and CV-scanning tools that rank job applications are respectively banned and limited. In the U.S., President Joe Biden issued an executive order in October 2023, which in part addresses topics such as job displacement, worker’s health and safety, data collection, and labor standards which in turn prevents employers from undermining workers and applicants alike.

Consulting agencies like McKinsey offer sentiments of positive expectations as well. They see generative AI enhancing the way STEM, creative fields, business, and legal professionals work rather than the outright, complete elimination of these industries. Businesses in climate, infrastructure, and green industries will lead to modest net gains in employment due to federal investment, of which civil and environmental engineers make a large portion of such development.

Generally, engineering fields are expected to keep growing. According to the University of Texas at Austin, by 2030 the following areas of engineering are expected to grow:

• Software engineering +24%
• Civil engineering +11%
• Mechanical engineering +7% 
• Biomedical engineering +7%

Historically, STEM occupations have grown significantly - a 79% employment increase since 1990, with a 338% growth in computer occupations.

With these forecasts, we can expect companies in engineering to alleviate their workload through new hires who implement AI in their tasks to improve efficiency, in turn getting more tasks done on time. AI can assist in simulating and analyzing engineering systems to predict system behavior, optimize design, and identify potential failures. 

Furthermore, in an analysis done by Harvard Business Review involving 1,500 companies, firms achieve the most significant performance improvements when humans and machines work together. Certainly, the article emphasizes that AI cannot entirely replace human work, interaction, decision-making, or creativity. In addition, humans need to train machines to perform tasks, to explain outcomes, to sustain the responsible use of machinery, as well as to correct for errors.

And companies have been quick to implement such technologies. For example, Autodesk Generative Design is a tool which uses algorithms to input variables like spatial requirements, weight, and cost, to create feasible designs which test and learn from each iteration. With the addition of AI features implemented into the software, it can guide designers towards better, more efficient designs. The Generative Design tool is currently used across various fields, including automotive, aerospace, architecture, and industrial machinery productions. Recently, General Motors manufactured a seat belt bracket 40% lighter and 20% stronger using Autodesk’s Generative Design software. The University of Cambridge also released a report outlining research where engineers created intelligent 3D printers that can quickly detect and correct errors through a deep learning computer vision model. They showed the computer model about 950,000 images labeled with the printer’s settings. Once trained, the computer model was able to quickly identify and correct errors, even in unfamiliar materials, just by looking at an image. 

This investment in AI across industries like engineering will only continue to grow. In a report by the Upcoming 2024 State of Design & Make, 66% of industry leaders predict that AI will be an integral part of their business within 2-3 years.

So what can you do about it?

Actionable steps:

• Consider learning manufacturing applications such as Autodesk Inventor or other CAD systems, even if they are not AI-based. This may highlight to employers that they can train you in a timely manner for more complex systems, of which some use AI for. Plus, AI features are rapidly being added to traditional software programs.
• Try to engaging in faculty research, look for industry-relevant internships, and take advantage of university career services.
• Join AI clubs and organizations on campus.
• Stay updated on news and emerging technologies about AI and generative design.