Generative artificial intelligence has entered the design engineering workplace. How will engineers use it and how will it impact the future of the profession?

Hate or love it, generative artificial intelligence (AI) has entered the global electronics design chain lexicon, as it has all sectors of the economy. How design engineers are using products such as ChatGPT and the multiple variants unveiled recently, though, remains unclear many months after it took the world by storm late in 2022.

Design engineers contributed to the development of AI and fostered its use with their innovations in semiconductors, communication, data and networking and cloud services but they are themselves only just discovering and exploring the potentials of AI in their professional activities, according to industry observers. Generative AI, they said, will play a significant role in future design activities but the extent to which engineers will rely on it at various points in the design cycle is still unknown. All segments of the economy are facing the same challenge, said Paul Daugherty, group CEO and CTO at Accenture.

“This technology is set to fundamentally transform everything from science, to business, to healthcare, for instance, to society itself,” Daugherty said, in a recent research paper co-authored with other Accenture analysts. “Embedded into the enterprise digital core, generative AI and foundation models will optimize tasks, augment human capabilities, and open up new avenues for growth. In the process, these technologies will create an entirely new language for enterprise reinvention. But reimagining how work gets done, and helping people keep up with technology-driven change, will be essential in realizing the full potential.” 

The technology innovators who fostered and advanced the creation of generative AI are only now beginning to confront the knotty riddle of its existence and future. For some, the mystery of generative AI has been slowly unwinding while many others have taken a wait-and-see attitude, analysts said. They want to first understand how generative AI design solutions will compliment traditional design methodologies, said Swiss engineering consulting firm Neural Concept. What generative AI will immediately unleash is a torrent of simulations that can help cut down on the design cycle, the company said, in a position paper on what it termed “generative AI design.”

“By coupling design and simulation, generative design can optimize a design for specific performance criteria – such as strength, weight, and cost – leading to improved final product performance,” Neural Concept noted. “Engineers can utilize generative design to optimize existing designs to reduce weight, increase performance, or lower production costs, thus giving their companies a competitive edge.”

That is only the beginning. “Generative design has the potential to revolutionize the way we design products and manufacture them because it enables designers and engineers to explore a much more extensive range of design options and find optimal solutions,” the company added. How this process will work, though, is still being explored by enterprises, which must proceed slowly and with caution to avoid overwhelming engineers or tipping off competitors to products under development. 

Going first or last?

Which generation of engineers will gravitate quickly to generative AI is another unknown. The younger generation may see AI as a natural extension of the digital products they grew up using. Familiarity with online products to supplement design activities may not translate into faster adoption, though, according to observers. 

Veteran electronics design engineers may distrust ChatGPT, they noted. This group may even disdain and mock GPT-4 – the latest variant of generative AI from Open AI LP, which can process and accept graphics as well as text inputs. What nobody, irrespective of their professional inclinations, can do anymore is avoid the ubiquitous and fast-growing presence of AI in business. It has already left an indelible mark on how we all operate, according to industry observers. As a result, generative AI may find a home in the arsenal of most engineers irrespective of age and longevity in the industry, they noted. It all comes down to the level of trust people have in technological innovations, according to the results of a survey conducted by Morning Consult. 

“The base group, high in trust, has an almost blind faith in the technology, considering many haven’t used a generative AI tool before,” said Morning Consult analyst Jordan Marlatt, in a report. “The reach group — those who say generative AI outputs aren’t remotely trustworthy — is the least likely to have tried generative AI. They tend to be slightly older than the average adult, but not by much. A third group, the swing cohort, constitutes everyone else. These are the people who are on the fence … This group accounts for a whopping 80% of the population, which isn’t surprising: Generative AI is in such a nascent state that many people have yet to form an opinion on the technology, even if half of adults already believe it is here to stay.” 

The electronics design world is not taking a bet on generative AI’s future or viability. Like most people polled by Morning Consult, engineers are expected to be early adopters, partly because they cannot escape the growing tentacles of its reach and applications. This does not mean they are not skeptical of generative AI’s broad application; they may just be more open to assessing it and learning from experience, Marlatt noted. 

“There may be no group more excited by the prospect of generative AI than those working in tech, particularly in roles like software development and IT,” he added. “Among software developers, 71% say workers in their field have more to gain than to lose from adopting generative AI tools, and 77% of IT specialists say that generative AI will create new types of jobs. About three-quarters of tech workers (74%) also say that embracing generative AI tools will be important to the future of their career.”

Concerns about the use, reliability, and long-term utility of AI in the workplace have grown with the rapid adoption by many segments of the economy. For electronics design engineers, AI poses a significant dilemma; they are both its protagonists and its antagonists. They fostered its creation and must now try to manage – or even curb – its applications, power, and influence on growing areas of the economy. They are even being asked to help understand and improve the reliability of generative AI, and the extent to which users should depend on its output. 

The question is not whether electronics design engineers will use generative AI. The knotty issues revolve around how engineers will use it, for which applications and processes, and to what extent. Technology enterprises must also deploy generative AI in the design environment while preserving the unique mindset and independence of thoughts that engineers are reputed for. 

Already in use

Many engineers in the semiconductor industry may have been quietly using generative AI for a host of other activities before chart GPT forcefully thrust itself into global consciousness. Companies like Nvidia Corp. said it has been working on generative AI for more than one decade and has now become one of the major providers of hardware and software products fundamental to the proper working of the technology.

Generative AI will change the face of the design world and reshape how engineers relate to the existing resource ecosystem, the company noted. It will redefine how they source information, the speed with which they access data and other resources, and even alter the engagements with internal and external sources.

How will design engineers use generative AI? We identified seven possibilities:

1. Simulation and simulation evaluation 

2. Research

3. Development of design solutions following engineering input

4. Further customization

5. Improving and accelerating tedious design processes

6. Creating and unlocking new products

7. Management of product obsolescence

Generative AI will not exist today without the innovations and huge processing powers unleashed by the electronics industry, especially semiconductor suppliers like Nvidia that supplies the advanced processors used by the data centers that support the sector. Nvidia executives said they foresee a new world of “accelerated computing and AI” emerging, enveloping engineers, developers, investors, and ordinary investors in a system marked by intense creativity and fast productivity fostered by a combo of semiconductors, other electronic hardware, and software. 

As described by CEO Jensen Huang, a new future is unfolding, fueled by generative AI, and desired by all segments of the economy. Nvidia expects to be at the center of this new universe where all segments of the economy would be infused with and elevate artificial intelligence to a prominent role in all enterprise activities. Huang said AI will result in what he termed a “cloud first world.” 

Speaking at the company’s recent GTS conference, Huang said: “We are at the iPhone moment of AI. Startups are racing to build disruptive business models, while incumbents are looking to respond. Generative AI has triggered a sense of urgency in enterprises worldwide.”

What can engineers do with generative AI that they may not be doing now? It turns out that AI is non-discriminating. Engineers will have to accept that many of the functions they can ask AI to perform are like the ones non-technical users may also request. Some of the tasks AI will perform for users will encroach on what engineers currently do, according to Nvidia’s Huang. 

“Everyone can direct a computer to solve problems,” Huang said, in his keynote speech at GTS. “This was a domain only for computer programmers. Now, everyone is a programmer. Generative AI is a new computing platform like PC, internet, mobile and cloud. And like in previous computing eras, first movers are creating new applications and founding new companies to capitalize on generative AI’s ability to automate and co-create.” 

As if these challenges are not difficult enough, the high-tech community has also been dragged into the task of helping to answer ethical questions about how generative AI is used and who owns the intellectual property rights over the content or graphics created. They will have to attempt all these even as they try to resolve the same riddles in their own use of generative AI in both professional and personal settings. 

The conclusion? Even if generative AI’s usage results in engineers having to yield parts of their current turfs for those with interesting ideas but no engineering education, it will still help in advancing product development and expand the universe they and their employers serve.