What I Tell Students About AI and Their Careers

Yesterday I wrote about my experience meeting with first year engineering students at Wentworth Institute of Technology. Here’s a bit more on what was discussed. 

AI always comes up. Whenever I talk to students - AI - it's something we are all concerned about. We worry about career security, whether we will be replaced by a bot, how fast it is moving. I have my own opinions on this from both a career perspective and a classroom perspective. Here's my take.

 

AI is now standard equipment. You'll use AI to draft reports, run design iterations, and analyze data. These tools are already normal day to day for many engineers. I like to compare AI to CAD. In the 1980s, senior engineers worried that CAD would eliminate drafting jobs. It did. But it created more engineering jobs because projects got cheaper and faster. Engineers who learned AutoCAD (arguably the first CAD program to gain widespread adoption is the 1980s) early had an advantage over those who clung to drafting tables. The same pattern applies now.

 

Computers can't make decisions that matter. AI suggests solutions based on parameters you provide. You decide which parameters count. You recognize when outputs look correct but fail in reality. You know when code conflicts with physics. You take responsibility when designs fail. Software doesn't do that.

 

Hands-on work resists automation. Site inspections, equipment troubleshooting, and field verification require presence. Civil, mechanical, and construction engineering involve messy reality. Sensors lie. Materials behave unpredictably. You verify assumptions with your hands and eyes.

 

Communication grows more valuable. Clients need translation between technical reality and business needs. Regulators need convincing. Teams need coordination. AI generates text; you read people and adjust strategy accordingly.

 

Choose your specialization carefully. Deep technical knowledge in stable domains (structural analysis, thermodynamics, electromagnetics) pairs well with computational tools. You provide expertise; computers handle calculations. Broad systems thinking also works. You connect disciplines; software optimizes within constraints you define.

 

Skills that will protect your career with reference to AI:

·       Learning new tools quickly

·       Critical evaluation of automated outputs

·       Client and stakeholder management

·       Hands-on troubleshooting

·       Ethical decision making

·       Cross-disciplinary thinking

 

Many engineering faculty disagree on this topic. Now for the fun stuff. Some professors ban AI tools in their courses. They have concerns about academic integrity and skill development. I understand the concerns and have the same ones, but this stuff is not going away. Employers today expect engineers to use AI tools day one, so I've shifted (and continue to shift) my courses to incorporate AI into assignments and labs. Students need practice evaluating AI outputs and knowing when to trust them. Learning these skills in school sure beats learning them under deadline pressure at a first job.

 

Advice to students. Use AI tools in your coursework when allowed. Learn their limitations through experience. Discover where they fail. If a professor bans AI, respect that rule. But seek out courses that teach you to work with these tools effectively.

Your generation will work alongside AI throughout your careers. Good engineers get better with better tools.