In 2018, I attended the Toronto Autodesk Accelerate conference – a mini version of Autodesk University, the company’s mammoth user conference. At a reception, I asked an Autodesk executive what the most important new development in design and manufacturing was.  Without a blink, he said, “Generative design.”

At the time, generative software’s ability to create a draft design from engineering instructions was amazing, nearly magic. The software could find the most efficient version of the part. Often this resulted in shapes that resembled the bone structure of the creature in the movie, Alien. Kinda beautiful and kinda scary. Design has stepped into a brave new world.

Much has changed in product design during the ensuing six years. Generative design is still an important tool with growing capabilities. Yet now it is part of a larger concept: artificial intelligence. Where AI was once the next-new-thing as generative design, AI has now become the only thing.

Technology comes in waves of democratization

I’ve seen two mammoth waves on technology change in my lifetime. Both involved technology moving from highly trained experts to the great unwashed – us. The first came in the early 1980s with the personal computer. Previously, the computers lived in large, cooled rooms and were tended by men in white lab coats. That was during the era when IBM had a dress code, down to the color of the shoes. The PC was suddenly on our desks, every desk. It became Time Magazine’s “Man of the Year” in 1982.

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The second massive change arrived with the new century with the infamous Dot Com Bubble. Even though the bubble burst – remember “irrational exuberance”? – the internet changed everything. Gone was the secretary, gone was the travel agent, gone was Border Books, gone was the recording industry. We’re still struggling to adjust to its impact. It has arrived in many stages, starting with email-replaces-snail-mail and evolving to social media that drove teenage angst and political disruption.

In industry, AI appeared many years ago with predictive maintenance and other machine-learning tools. Generative design followed, providing a deeper dive into engineering functions such as the design work itself. Just as the PC revolution and the dot com era required a technology breakthrough (new chips, new software, net connection tools), AI required a major shift – the cloud. Autodesk’s AI tools are backed by considerable computing tools. Developments in faster processing speeds and cheaper memory helped considerably.

Related:Manufacturers Turn to AI to Transform Processes

Taking the dull work out of design engineering

At one of the general sessions at Autodesk University 2024, Jeff Kinder, Autodesk’s EVP of Design & Manufacturing said, “We’ve added AI to our products to reinvent how work gets done, to increase productivity, and to boost profitability.” Just as robots are taking away the dull and dirty work in factories, AI is taking away tedious engineering, the dull and dirty intellectual work.

Autodesk's Jeff Kinder at Autodesk University. Image courtesy of Autodesk.

A good example is the design of the track of a huge earth mover. Once all the design work is done of the left side, the software immediately creates a mirror version of the track for the right side, saving countless hours of design engineering work. “It's so sweet that this happens,” said Kinder. “We're reducing hours or even days in engineering time.”

The engineering benefits of AI

Autodesk sees AI as a tool – or perhaps a mindset – to drive creativity, efficiency, even sustainability. Here are some of the engineering functions of AI according to Autodesk:

AI augments creative problem solving. AI helps engineers explore design possibilities, pushing boundaries, offering solutions outside the envelope.

Automates tedious engineering work. By automating repetitive and mundane engineering tasks, AI lets engineers focus on more strategic and innovative work.

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Enhances decision making. AI offers powerful analysis tools to help engineers make informed decisions by processing large datasets quickly and accurately.

Improves efficiency. AI tools can predict and prevent risks, optimize workflows, and reduce errors and waste.

Supports sustainability. AI can contribute to sustainability practices by optimizing resources and reducing the environmental impact of the design, manufacture, and end-use cycle.