While many fear that AI will replace engineers, the analysis reveals a more nuanced reality: AI is more likely to augment engineering roles by taking over certain tasks, while the jobs most at risk are knowledge-based and communication-intensive, rather than physical or hands-on.
The AI Applicability Score and Exposed Occupations
To measure AI’s impact, researchers created an “AI applicability score” that quantifies the overlap between an occupation’s tasks and an AI’s capabilities. A higher score indicates a greater potential for AI to assist with core job functions. The study found a clear distinction between knowledge work and manual labor. Jobs with the highest applicability scores are “cushy desk jobs” that involve language, data, and communication. The most exposed professions include interpreters, social scientists, sales representatives, and writers. In contrast, occupations requiring physical skills and on-site labor, such as logging equipment operators, motorboat operators, and dredge operators, have the lowest scores. For the top-ranked job, interpreters and translators, AI performs 49% of their tasks more effectively, but rather than being replaced, many professionals are now using AI to enhance their work.
How Exposed Are Engineers?
Engineering as a profession falls in the middle of the AI applicability spectrum. Engineers perform a mix of knowledge-based tasks (calculations, design) and physical tasks (prototyping, site supervision), with current AI excelling at the former. Surprisingly, CNC tool programmers, not software developers, were found to be the most exposed engineering role with an applicability score of 0.44, indicating nearly half of their tasks could be assisted by AI. Data scientists also have a high score of 0.36, but AI struggles with complex analytical tasks. The applicability scores for traditional fields like mechanical, civil, and electrical engineering are more modest, as much of their work involves the physical world, where AI’s capabilities are limited. This suggests that while digital engineering jobs are highly exposed, roles requiring hands-on, real-world work are relatively protected from full automation.
Automation Versus Augmentation
The study challenges the common belief that AI will simply automate jobs. Instead, it suggests a dynamic of augmentation, where AI assists humans rather than replacing them. The data shows that in many cases, AI performs tasks different from what the user requested, creating new forms of human-AI collaboration. For engineers, AI is not just automating existing work; it’s enabling them to perform tasks traditionally done by others, such as technical writing or research assistance, while also making their core engineering work more efficient.
What Engineers are Using AI For
Engineers are adopting AI tools for three main purposes:
- Information gathering: Using AI as an advanced search tool to research technical specifications and stay informed about new developments.
- Writing and content creation: Using AI to assist with technical documents and design materials, with high satisfaction reported in these areas.
- Problem-solving and explanation: Seeking AI help to troubleshoot issues, understand regulations, and explain complex concepts.
Ultimately, AI is creating a “jagged technological frontier” where it excels at some tasks but fails at others, leading to unpredictable disruption. While manufacturing and software engineering are seeing rapid AI adoption, civil and environmental engineering have lower applicability scores due to the physical nature of their work. The study does not predict job losses, but rather suggests that AI will significantly enhance the engineering profession, enabling engineers to be more productive and take on more ambitious projects.
Did you subscribe to our daily Newsletter?
It’s Free Click here to Subscribe!
Source: Interesting Engineering
