AI has permeated into almost all areas of personal and professional life. Workplaces everywhere are adjusting to this — not quite new (AI was conceptualized in 1956) — but certainly burgeoning technology. Engineers, like everyone else, are finding that AI has changed their job considerably.
In this article, we take a look at some of the many ways AI has changed the engineering field.
The Short Answer
The primary benefit of AI is always to make work easier. This is accomplished through automation. A well-tuned AI algorithm can handle minor, predictable tasks, freeing the engineer up to dedicate more time toward serious work.
There are, of course, limitations. For automation to be reliable, the task itself must be pattern based with a low threshold for variation. Think about how automation is used at the grocery store. It’s great for handling consistent jobs, like inventory. Either an item is on the shelf, or it isn’t.
But what about working drawer? While this task seems straightforward — add, subtract, and accept payment — there are actually hundreds of potential variables. What if a customer asks a question? What if a judgment call needs to be made?
These same limitations are in play when it comes to the field of engineering. For as good as AI is, it can’t replicate the human mind that drives the engineer.
Productivity
AI can be used to generate new designs and run simulations to demonstrate how they will perform once produced. These projections are very useful for working engineers in that it allows them to simulate scenarios at a much quicker and more accurate rate than they ever otherwise would have been able to.
Sensors
Say an engineer is responsible for designing and maintaining machines used in a factory. Historically, when something went wrong, it would be the engineer’s responsibility to diagnose the problem, and then address it accordingly.
They might have had a good idea of what went wrong, but they would still need to manually inspect potentially large quantities of machines and instruments to be sure.
With sensors and AI, running diagnostics can happen in a matter of seconds. Not only can artificial intelligence coupled with sensors identify when something has gone wrong, but it may also be able to spot problems as they are developing reducing the amount of time and effort needed for the eventual repair.
Workflow Management
AI also impacts engineering in ways that are common across sectors of business. Consider the information silo. Legacy technology compartmentalizes information among department lines. If there are different workflows — say, a project manager, an engineer, and an executive division, each department of the operation would historically have relied on its own tech suite.
Now, departments can still use their tools, while passing data points along seamlessly from branch to branch.
Indirectly
Then there are less direct ways that the field of engineering is and will continue to be shaped by AI. For example, even though it’s been almost three years since the pandemic began, design engineers still report that supply chain instability is one of the biggest work-related hurdles that they face.
AI sharply reduces supply chain related issues for everyone by making networks easier to manage. Now, supply chain managers can use AI programs to get accurate forecasts on potential problems — a bad weather system, a viral outbreak — and tweak their routes accordingly.
AI can also be used in the transportation of goods. Internet of Things sensors are often used on long-haul trucks to monitor the condition of the vehicle, and make highly detailed route recommendations that improve productivity.
A world Without Engineers?
No matter how good AI gets, it’s difficult to imagine a world without engineers existing in the near future. In fact, long-term studies show that technological advances usually create more jobs than they end, and on this particular front, engineers with their STEM-driven minds are particularly well adapted to thrive in whatever new work conditions that AI creates for them.
