건설 분야의 AI: 생산성, 계획 및 타당성

건설 분야의 AI는 설계, 계획 및 환경 영향을 최적화하여 사람의 작업을 보강하고 생산성을 가속화합니다.

### AI가 건설 산업에 미치는 영향
* 🏗️   AI는 **설계 작업을 자동화**하고 계획과 일정을 최적화하여 복잡한 문제에 집중할 수 있도록 함으로써 건설 업계에 혁신을 불러일으키고 있습니다.
* 🌍  또한  AI는 **설계와 실현 가능성에 대한 환경적 영향을 해결**하고 생산성 격차를 해소하며 현장의 작업을 강화하는 데에도 사용되고 있습니다.
* 💡  인공지능은 흥미로운 기회를 제공하지만, 건설 업계에서는 **인공지능의 한계와 인간과의 상호작용**이 필요하다는 점을 기억하는 것이 중요합니다.
* 📊  업계의 파편화 및 데이터 문제와  AI 기술의 수익화는 **채택과 협업의 핵심 고려 사항**입니다.
* 🏢  기업은 실시간 에너지 최적화를 위해 전략적으로  AI를 도입하고 영업, 마케팅 및 상업적 측면에 가져오는 **변화**를 탐색해야 합니다.
* 🔍   AI 혁신에 대한 접근 방식에는 **가치를 창출하는 사용 사례와 실현 가능성**을 파악하고 파일럿을 실행하며 확장하기 전에 **비즈니스 영향**에 초점을 맞추는 것이 포함됩니다.
* 👷‍♀️  건설 업계가  AI 기술을 수용하고 통합함에 따라 **기술 파트너와의 협업**은 매우 중요합니다.

foreign [Music] use cases. Certainly, a lot of our clients are getting interested and excited about. Probably into three or four buckets, right? So, the first of those is everything around design productivity. The thing that's very cool about. Jenny alone, in fact, AI more broadly, is it allows you to start to automate some of the tasks which take engineers and architects a lot of time at the moment but don't necessarily add huge amounts of values. That might be, you know, generating design specifications. It might be about deciding exactly how high off the ground the door handle should be, right? And the great thing about design optimization is it creates capacity with engineers and architects to really focus on the highly complex novel problems, right? Which is quite an exciting opportunity, I think. The other kind of big collection of use cases we see is everything around planning and scheduling. So, yeah, planning and the construction planning is typically a bit of a dark art in construction. There are some science behind it, but it's definitely as

elements of being a dark art, and that's borne out with some of the um, your schedule adherence. We see typically in construction and infrastructure projects, with projects typically running over budget and over time. There are tools out there and companies out there that actually um, use AI to learn from historic project delivery to improve the accuracy of scheduled forecasting, and actually do that almost in real time. So, you know, day by day or week by week, you're coming up with a more accurate view of the schedule, and actually recommendations on how you might redeploy resources with a schedule. Some of the most exciting opportunities, the most disruptive, are looking at the impact of environmental uh, impact on design and feasibility. So, looking at future scenarios where flooding, uh, winds, storms, excessive heat will impact on a concept. So, as we help clients and we help design and engineering companies plan ahead and think of the optimal design, there are so many different scenarios that we can now generate, um, using AI to really think ahead of the future and make sure that these assets.

is important uh buildings that are getting constructed or road infrastructures are going to stand the test of time. The engineering challenges we have are more complex than whatever you've ever seen before over the next 30 to 50 years, right? We talk about the decarbonization challenge, and we're trying to do that when we've got a capacity constraint in the industry. We don't have enough engineers, we don't have enough architects, we don't have enough capacity in the construction industry. Gen Ai, Ai, and actually digital tools more broadly are a way of bridging that productivity gap. Look, this, look at this, Panacea for all, all solutions, there are going to be limitations for this, and I think you know what we need to be aware of that this technology is not about replacing people. It's about augmenting um the process, about making sure that we're using human interaction on the most complex elements, and that the basics are done right first time. We get to brilliant basics quickly. There's a lot of the buzzing excitement, rightly so.

about gen AI and AI at the moment and some of the use cases. We've described a huge potential mass of exciting but it's really important to remember that construction is the biggest industry in the world. It's one of the most fragmented. It's mainly made up of small and medium, you know, artisanal cross people, and small construction companies, and it's always going to be a hands-on physical business, um, that relies on skilled hard-working people on the front line, and that isn't going to change anytime soon, right? So I think we need to be, need to recognize that, um, AI, as Darren says, as an opportunity to, you know, augment the work that we do on a site. Um, it has an opportunity to accelerate design and streamline the design process, but it's not going to change the kind of physical act of building stuff out on a building side because the other kind of, um, reality check we need to do is that this depends on data as well, and this is something that most industries struggle with at construction.

particularly struggles with because of this level of fragmentation, and you need to have a solid data layer to be able to deliver many of these use cases. One of the challenges is that the industry, from an engineering perspective, is based on hours, and suddenly there's a potential to do things instantly, in a nanosecond, at zero real cost. Um, how do we monetize that? How do we incentivize the technology companies, the engineering companies, and the owners to collaborate? Ultimately, an owner will benefit when their schedules reduce, their cost to build and time to market is reduced, and we're talking about projects that are often in the millions, if not billions. So how do we help the ecosystem, the supply chain ecosystem, benefit from that transformation? Because otherwise, there'll be as much of a risk of low and slow adoption as there is of going too fast and getting it wrong. Question that I'm hearing a lot is, what does this mean for my business? Is it kind of exciting hype that I can kind of ignore for a few

months, or is it something that's fundamentally going to change the business? And yeah, every business will be different, right? Um, but the way we think about it is as an engineering company, how can we use AI to more accurately predict and monitor energy consumption in an office building in real time, and offer, yeah, real-time solutions to optimize energy consumption? I would be looking, guiding organizations towards finding some low-hanging fruit, something that is contained and managed that you can change there's a whole system level, because this isn't just about adopting technology quickly, it's about changing the sales and marketing teams, the incentives for those sales teams to sell a new solution in a different commercial way, and the potential impact of working new in a new way where it's not an hours-based business or a lump sum type business is quite huge, and I can see some companies getting stuck with of this. So picking something that is relatively easy to adopt the technology but run the whole changes through the entire life cycle of the services that.

are provided to the clients through to commercials and billing and make sure the whole team are working in that way almost as a product team and taking that to Market and learning from that is really important although the technology is relatively new actually the approach to transformation is one that we've we've seen before we're familiar with right so that and there's two Dimensions to it the first is you know identify the business domains and the use cases where this is going to create most value right so it might be to improve your win rate and tendering it might be to reduce accidents on site it might be to improve engineering productivity but which use cases are going to create real business value and then on the feasibility right so do we have the data to be able to do this do we have the systems and if not is it going to be significant investment to get the right systems in place do we have um actually the skills to help us build and administer the technology and either build or integrate with the right models

and then from that develop the list of a short list of use cases and go and execute the pilots before scaling, right? But it's very easy to get excited about the technology, that technology side, but it must be grounded in business impact. At the end of the day, I think Ace companies need to focus on the value ports, where is this going to have the biggest impact, but not go too large at the beginning. Really get something proven and working and deployed and get the rest of the organization behind it. That's how I'd be tackling this, but also, you know, Engineers like to design, they like to own and build, and there's going to be a preference to own and build this technology. And I think their existing technology companies and startups are pure play invested in this area already and have already been moving in this direction. So adopting and working with the right technology Partners from the outset is really important.

Harnessing generative AI in architecture, engineering & construction

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AI는 설계 작업을 자동화하여 엔지니어가 복잡한 문제에 집중할 수 있도록 함으로써 업계에 혁신을 일으키고 있습니다.

또한 AI는 프로젝트 일정 및 예측의 정확성을 개선하여 지연과 예산 초과를 줄이는 데에도 사용되고 있습니다.

건설 분야에서 AI의 또 다른 주요 용도는 설계 타당성에 대한 환경 영향을 평가하여 자산 복원력을 최적화하기 위한 다양한 미래 시나리오를 생성하는 것입니다.

AI와 디지털 도구가 건설 산업에 미치는 영향

건설 업계는 복잡한 엔지니어링 과제와 용량 제약에 직면해 있지만, AI와 디지털 도구는 생산성 격차를 해소할 수 있는 방법을 제시합니다.

그러나 이러한 기술은 건설 프로세스를 보강하기 위한 것이지, 실제 물리적 비즈니스에서 중요한 역할을 하는 인간 근로자를 대체하기 위한 것이 아니라는 점을 명심해야 합니다.

숙련된 근로자에 대한 의존도가 높은 건설업계는 데이터 의존도 또한 높아지면서 AI 및 디지털 도구의 도입에 큰 어려움을 겪고 있습니다.

기술 혁신으로 수익 창출 및 인센티브 제공

엔지니어링 업계는 즉각적이고 저렴한 기술 솔루션으로 수익을 창출해야 하는 과제에 직면해 있으며, 이를 위해서는 협업과 인센티브가 필요합니다.

실시간 기술로의 전환은 비즈니스 일정과 비용에 영향을 미칠 뿐만 아니라 영업, 마케팅 및 전반적인 비즈니스 접근 방식에도 변화를 요구합니다.

기업은 쉽게 채택할 수 있는 기술에 집중하고 서비스의 전체 라이프사이클을 탐색하여 성공적으로 전환을 구현하는 것이 좋습니다.

비즈니스에서 신기술을 구현하기 위한 전략

회사에 가장 큰 가치를 창출할 수 있는 비즈니스 영역과 사용 사례를 파악합니다.

데이터 가용성, 시스템 요구사항, 기술 구현에 필요한 기술 등 실현 가능성을 평가합니다.

비교적 새로운 기술이라 할지라도 제품 팀으로서 혁신 프로세스에 접근하고 이를 통해 배우는 것이 중요합니다.

비즈니스 영향력에서 접지 기술의 중요성

새로운 기술을 도입할 때는 신기술에 대한 기대감에 휩쓸리기보다는 비즈니스에 미치는 영향에 초점을 맞추는 것이 중요합니다.

기업은 규모를 확장하기 전에 검증된 소규모 파일럿으로 시작하여 기술이 가장 큰 영향을 미칠 수 있는 영역에 우선순위를 두어야 합니다.

또한 성공적인 구현을 위해 처음부터 적합한 기술 파트너와 협력하는 것도 중요합니다.