The AEC Industry and AI: What We’ve Seen and what Companies Can Do Now

At Hitachi Solutions, AI is at the forefront of many requests we receive from companies, and the AEC industry is no exception. Contractors, architects and engineers, like everyone else, want to know what’s happening with AI, what people are using AI for, and what kind of success early adopters have had.

Although the construction industry is commonly considered a technology laggard, things are changing and changing fast. In fact, the market for AI in construction management is anticipated to be worth about $4.5 billion by 2026. This year, we anticipate the AEC industry will witness a marked shift towards digitalization, to take advantage of advanced technologies like AI and generative AI to drive efficiencies and maintain the bottom line.

To unpack that future, we sat down with Hitachi Solutions’ Senior Director of Industry Strategy, Jon Loring, to get his take on where technology and AI in the AEC industry is headed, what companies can do now, and what the future holds.

How has AI Changed the AEC industry?

One of the most important ways we’ve seen AI transform the industry is by improving worker safety. Every job site is a data source for AI. Safety managers can’t be on the job all the time. Sensors and cameras can monitor job sites and identify hazards. Examples include the lack of proper safety equipment, incorrect usage like working at heights without a harness, or equipment that has been damaged or shown missing. Videos and photos can be analyzed by AI to pinpoint and alert managers to these issues. This is one way to address what’s happening and encourage worker safety and site security at the same time.

We’ve also seen increasing use of IoT asset tracking using RFID to solve many headaches involved in managing equipment. Think about it: IoT devices, like sensors and alarms, can be located inside heavy machinery, let’s say cranes in a remote location, to monitor performance. Everyone is familiar with unexpected equipment failures that result in unplanned downtime and extended project timelines, and companies are starting to realize that strategic maintenance of their physical assets can have significant impact.

Can AI Help in Sales?

A real eye-opener has been the potential for generative AI to improve the efficiency of workers who are bogged down by repetitive tasks. For customer or owner relations, this often comes down to the speed and accuracy we are seeing in responses to RFPs. Proposal writing can be a huge time suck and prone to error— that’s partly because everyone uses past proposals and continues to copy and paste together. At Hitachi Solutions, our focus has been in understanding data and document quality. Accelerators and templates can solve that by generating initial proposals with pre-populated base information.

It’s much easier to have centralized document management when developing proposals so nothing falls through the cracks. An AEC-focused CRM system like Hitachi Solutions’ CE Sales Accelerator helps with prior work proposal references which can then be combined with a proposal generation GenAI solution. This often is a separate database tailored with all the information from all your systems.

It is hard to build the perfect proposal, and AI can help provide analysis that lets companies create better cost estimates and increase the likelihood that they’ll win the contract. Seeing AI sift through data, hit key insights and put them into plain language is really groundbreaking.

Can AI Streamline Project Delivery?

Everyone wants the execution part of any project to be as seamless as possible. But any one of dozens of variables can send a project off track. Here’s where AI can have substantial value— it can analyze large datasets and identify patterns that might escape attention.

Many organizations we work with are often struggling to use their data for the kind of insights that can really improve performance. AI can analyze data from different types of formats, unstructured documents, financial numbers, IoT sensors, transportation routes, and even social media. We have the potential to build predictive models that can understand the causes and effects a project might encounter so companies can make better decisions to mitigate risks or change course. It’s a level of  proactive management which means fewer surprises for everyone.

AI can give companies the analysis they need to identify exceptions and make course corrections. It can consider external data like weather, trends, and costs and apply those insights to internal project data to predict what could happen throughout the project lifecycle.

With access to a variety of data, companies have the internal capabilities to quickly build visual dashboards, with real-time summaries of key performance indicators, like schedules, costs, and risks.

What Internal Capabilities Do We Need to Adopt Generative AI?

Generative AI is only as helpful as the data underneath, so if you don’t have a strong data strategy, you won’t have a strong AI strategy. When using company data, generative AI often surfaces data quality issues that inhibit how companies can take advantage of what AI can really offer. This is where ERP (enterprise resource planning) and CRM (customer relationship management) tools can help. If data is entered correctly at the source and maintained in a central place, companies will have the foundation they need for AI. 

What are the Most Useful Ways Companies are Adopting AI Right Now?

While many companies are expanding their cloud capabilities to accommodate AI, they can still benefit from out-of-the-box products like Hitachi Solutions’ Enterprise Chat. In fact, our own employees use it and are finding new and interesting use cases every day. Enterprise Chat is simply an AI workspace that lets users interact with a large language model through a chat interface. It’s not unlike ChatGPT, but it’s deployed within a company’s Azure tenant behind a firewall and is completely safe.

There are a lot of simple ways Generative AI can make employees more efficient and improve their work in ways that really stack up to huge time savings. It’s an easy and safe way for companies to get their feet wet in the AI water and learn.

What are the Risks AEC Firms Face when Integrating AI?

Given that AI is becoming more mainstream quickly, it’s important to think about the policies and governance that will be needed. Microsoft Copilot is available to almost all of their tools, so I encourage users to try it and see for yourself. I think it brings a whole new level of productivity and keeps getting better. All of this is a journey that will take time and new competencies will be built over time. The winners in the AI game are going to be those that take a strategic approach to identifying the business processes that can be improved and automated through AI. Where to invest your time, and realizing that you’ll need to pivot as needed, are important with this technology.

Any Advice for Companies that are Hesitant to Adopt AI?

If you have the big picture of your goals and you’ve defined the value proposition, you can tackle the journey in many different ways. Rather than looking at AI and thinking about how to include it, it’s better to think about your business problems and work backward, saying to yourself: “If I had this information, I could do x.”

Ask yourself if you have a pressing business problem, and if so, what would a successful outcome of solving that problem look like? Do you need different data? Do you have data you aren’t using? Almost all organizations are sitting on a wealth of existing data. Rather than looking for new means of information gathering, consider the data you already have. This can be your starting point to experiment. There is lower risk when experimenting and going slow when adopting AI.

Why Hitachi Solutions?

For over a decade, Hitachi Solutions has been working with AEC organizations around the world to enhance their technology and help solve business problems. We can find a solution to help turn your project inefficiencies and expenses into opportunities for growth, increased cost savings and rising productivity. Our goal is to assist you in evaluating your current needs and to work directly with your team to best determine how to foster the power of new innovations, particularly with generative AI.

In our Generative AI and Copilot Workshop, we explore how these technologies work, their unique features, and the potential they hold for transforming business operations.  Hitachi Solutions’ team of expert advisors will work with you to build confidence in your ability to safely adopt AI technology to gain the most ROI and value.

Contact us today to learn more about our AEC and AI solutions built on the Microsoft platform.