I’m not an engineer by trade. While that may seem like an odd way to open an article about AI and engineering, I’m going to tell you why it matters and how it shaped my journey to where I am today.
My background is in IT. After graduating, I realised quickly that I did not want to sit writing code indefinitely. I wanted to change systems and make them better. That naturally led me into project management and systems analysis. When I started my career, computers were relatively new, and most business processes ran on paper. I was watching people physically move pieces of paper around and thinking, ‘there has to be a better way to do this.’ That instinct became a common thread throughout my entire career.
In fact, it’s what led me into engineering leadership. I am a long-vision person, and I do my best work when I can look at what’s possible in the future and build the strategy to get there. Today, in my role as Transformation Director for Transportation Solutions at TE, I am incredibly fortunate to be able to help drive what the future of AI looks like within our organisation. I get to lead engineers in a field where the results are real and tangible. Our products are in the aircrafts you fly in, the vehicles you drive, and even the spacecraft heading beyond our atmosphere. The stakes of what we build are never abstract. That’s both exciting and a little scary, especially as we navigate how to make AI a fixture in our everyday work.
AI is driving the future, and we are along for the ride
The first thing I tell people about AI, especially my team, is that no matter how you feel about it, AI is here to stay. As a leader, this means navigating two challenges simultaneously: the technology, which is evolving faster than anyone can fully predict, and the people, who are trying to make sense of what it all means for them personally.
In my opinion, the people side is the more important of the two. Engineers are asking whether they will still have jobs and whether the knowledge they spent years building and gaining, mostly by doing, will still matter. As leaders, we can help them through the uncertainty by reinforcing their value.
Engineers are irreplaceable, but their role is changing
The truth is that we will always need engineers. Their job may just look different. The first thing most engineers realise is that AI can be extremely useful for administrative tasks, giving them more time to focus on engineering.
When it comes to engineering knowledge, most, if not all, of it is gained through hands-on experience and trial and error. AI can do what we train it to do, but it cannot replicate instinct, or the ability to look at a result and know, often before you can explain why, whether it is correct or incorrect. That capability belongs to experienced engineers.
AI can also help speed up the process and give engineers solutions they may not have thought of otherwise due to time constraints or over-focus on one solution. In an ideal AI engineering workflow, the engineer prompts AI, AI processes the information and returns a result, then the engineer validates the result, at each stage of the design process. With this model, the design instinct does not disappear but instead becomes the quality control.
AI models need more AI models
If you ask an LLM the same question three times, you will get three different answers. It’s built that way for a reason. In engineering, particularly when products go into cars or medical devices, that variability is not acceptable. As we are building AI models to perform the work, we must simultaneously build AI models that check the health of the model and the work it performs. Both models require human support, with an engineer performing the final validation every time. As time goes on, it’s likely that an engineer will transition to owning and refining the AI model and engineering workflow to master the new toolset and know its limitations and capabilities while ensuring it meets efficiency, accuracy, and reliability goals.
The playing field has levelled, creating opportunity
AI is changing engineering careers overall. Engineers who once would have needed significant infrastructure, budget, or seniority to drive meaningful innovation can now build something genuinely impactful on their laptop. The barriers to innovation have never been lower, and the career trajectories for engineers going forward will look entirely different from what they have in the past.
AI has also levelled the playing field for leaders. Senior leaders who have built their careers on accumulated expertise suddenly find themselves in the same position as everyone else. They’re facing a body of knowledge they do not yet have. And while that shared uncertainty is uncomfortable, it can also be freeing. In today’s new AI age, before anyone, of any level, starts a task, they should ask themselves: what do I not know about this? The willingness to pose that question is what will carry us through this transformation.
We also need to keep talking to one another. The only way we can keep up with the pace is to lose our ego and share what we know. I learn something in every conversation I have. Whether it’s a single phrase that sends me researching something I hadn’t thought of or a like-minded perspective that lets me know we’re on the right track, every new piece of information helps turn strategy into real and impactful results.
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