Artificial intelligence for engineering: How mature are we?

From self-driving cars, to recognising human faces and emotions, synthesising voices or even making a hair salon appointment; AI has begun to make its mark in our personal lives. Yet ironically, AI has had little impact on the Architecture, Engineering and Construction sectors as Alex Ferguson discusses. 


There's a lot of hype about Artificial Intelligence (#AI), Machine Learning (#ML) and what role these technologies will hold for the future of the human race. Continual research and development of intelligent algorithms for solving human problems is rapidly having an impact upon the world. From self-driving cars, to recognising faces and emotions, synthesising voices or even making a hair salon appointment; AI has begun to make its mark in our personal lives. Yet, somewhat ironically, AI has had little impact on the Architecture, Engineering and Construction sectors (I say this is 'ironic' because these fields are all based on STEM, logic, and rational thought).

Sure, there's been a couple of cool things happening around the place, like automated progress monitoring robots, but these advancements are not all that pervasive, yet. So comfortable in the fact that their job is technically challenging, should the average engineering professional be resting as easily? Or is there an undercurrent that threatens to rise to the surface and in one-quick-move devour an entire industry?

Disruption, after all, isn't a slow and steady process. Instead, it is a ruthless adversary that moves quickly throughout an industry and can wreak havoc in a very short time-frame.

If we look to the banking industry, a very traditional industry now struggling with the emergence of disruptive technology, we can see how slow moving 'big business' is finding it difficult to adapt to this changing world. So how will engineering firms react when advanced Artificial Intelligence starts eating their lunch? In fact, I propose now is the time to look into it because:

  • Gone are the days when we need 150 engineers, scientists and architects to design a 200 KM stretch of road, or a 100 story high rise. Nowadays a small team of engineers and programmers can guide an AI-enabled device to produce a code-compliant and fully-optimized design in accordance with the client’s requirements.
  • Gone are the days when we need a swathe of contractors to carry out all the civil works, steel and form work, fit-out etc. When we have an army of fit for purpose robots that can 3D print what we need, supply to and install on site.

These are but mere examples of a new form of consolidation, and unlike mergers and acquisitions which aggregate body counts and the skills and capabilities of human capital, this consolidation is happening in the cloud. It's all about enabling thousands of pop-up AI-driven service providers to start taking small, but meaningful bites out of our sandwich.

"Yeah right" say the engineers in disbelief, comfortable after 30 years in their professional career that no AI robot could possibly compete with their skills and experience. I mean, thousands of years of scientific advancement has culminated in their ability to achieve great things never thought of in the past! Just like thousands of years of accumulated knowledge in the art of playing Go, a game which has more potential moves than there are stars in the known universe, meant that even the most complex AI couldn't... Oh wait! That's right, after only a few hours of training, an AI robot beat the entire knowledge base of human existence and a lifetime of experience and training, turning the game upside down.

Where are we right now with AI?

Let’s entertain for a moment the idea that Artificial Intelligence will one day be doing our jobs. It’s not hard to believe; a large degree of the engineering profession is about applying well understood rules to the generation of a solution. Take a recent project I worked on where we developed software that carried out an entire design that once took two weeks. The software, programmed to understand the rules, completed the task, error free in just 30 seconds. There's value in efficiency and in getting the right answer the first time, and even greater value in getting a correct and optimised design right off the bat.

Now I hope you're thinking, "Ok, I'm interested, so what?" Well… great! The first step towards solving any problem is realising that we have one, and where we should be applying our efforts towards a solution. So, let’s start with an assessment of where we are right now.

For the past month I've been developing a framework for the engineering industry we can use to assess our current AI maturity. It’s pretty straight forward, we simply consider the most recent projects we've been involved in, and the extent to which these statements represent how we delivered those services.

Where are we going with AI?

So we exist somewhere along a curve. But knowing where we are is only one part of the equation. Let’s also look at where we're going. We need to think about our business and imagine for a moment we're 10 years into the future. Robots are pretty much doing everything, artificially intelligent personal assistants are connecting us with new services, our business is going great because we've fully embraced AI and are leading the industry. So what are we using AI for? What things that humans are doing today, is Artificial Intelligence now doing for us? Has it automated part of our job, or everything we do? We are in control, and we have skilled people working around us, what jobs do they have in this new world?

There's a lot to think about, but the clearer our vision, the easier it will be to discover the next steps to getting there. What's more, there's a great way to do this, I've been working with clients for the past year on creating a vision for their future, and a few simple facilitated workshops with key stakeholders in our industry and business is all we need to get started.

How will we get there?

Now that we have a vision, there's a lot of work to do, and we need to put in place a plan of action. It takes into account not only the gaps in our current capabilities, but also the changes to our business model.

Moving to the world of ubiquitous AI isn't about dropping everything we do either. Some of the same systems, processes and people we have today will be critical to our success, and there are ways of taking people from the organisation along on the journey with us. While there is no one-size-fits-all solution to getting from today to tomorrow, with the right advice, a positive attitude and supported by a clear vision from above, we'll be on our way in no time!

Final words

First and foremost, thanks for making it this far. I hope the framework is useful for discussion, and I'm open to comment and feedback on it. Where do you sit on the scale? As a practitioner of parametric and generative design and with experience in the application of ML algorithms to design optimisation, I'm always looking for ideas on how we might advance the field further - so please feel free to get in touch!

Secondly, as a management consultant, I know the difficulties many people and companies face when considering the changes they need to make to adapt to this rapidly changing world. I would love to have a one-on-one conversation with you about how you can position your company, and yourself, in this new world. I'm happy to present to you the opportunities AI might also offer across a wide range of other industries.

Finally, please feel free to use this framework for your own purposes. I only ask that if you do make some changes, please give me feedback so I can improve it for the greater good!

Ready to hear more about how Beca is making everyday better, by harnessing the power of artificial intelligence and helping our clients integrate it into their own business or organisation? Visit Beca Digital today.
Image thanks to @hautedeyes on Unsplash, Kyoto Prefecture. 

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