If you’ve dipped your toes into artificial intelligence (AI) and are seeking ways to apply it in a technical environment such as architecture, engineering, and construction (AEC) or manufacturing, you have plenty of opportunities to do so. As you dive in deeper, you should have specific benefits identified for your organization, as well as be aware of potential pitfalls in AI. You also need to have well-organized data to apply AI technology. In our first article, we discussed how to evaluate your readiness for AI. Our second article then explored how to start implementing AI at your organization. In this article, we’ll look closer at how to reap benefits and avoid common pitfalls of AI.
Image source: ipopba/stock.adobe.com.
Identifying Benefits
Some of the potential benefits of AI are similar to those that many technical organizations have been seeking for decades, such as time and cost savings, quality and efficiency improvements, risk management, and new design and construction solutions. Some of these benefits potentially help address other issues, such as ongoing workforce shortages and pursuit of competitive advantages.
Tangible benefits are being realized throughout the lifecycle of projects. In the AEC world, benefits are particularly being reaped in construction. With the help of AI, firms can identify construction and safety issues and address them more efficiently than with traditional methods.
For example, AI can help identify trip and fall hazards on jobsites. Using tools such as those in the Autodesk Construction Cloud platform, AI can access construction photos and video footage to identify and track potential safety risks and issues. By automatically tagging photos with relevant keywords, such as those related to safety, teams can tap into the ACC’s AI capabilities to manage risk. AI technology can prioritize safety issues over minor issues such as paint scratches, notifying project managers accordingly. Similar approaches can be used to track and address potential fire hazards, water leaks, and other construction issues.
Using AI within Autodesk Construction Cloud, AI can help you identify trip and fall hazards on jobsites. Image source: AiHRG Design/stock.adobe.com.
The ACC platform makes use of Autodesk’s Construction IQ technology, which uses machine learning to predict and manage risks to cost, schedule, quality, and safety. ACC modules include Build, which includes project management, quality management, safety management, and cost control tools; BIM Collaborate, which automates clash detection and centralizes design for remote teams; Takeoff for automated quantity takeoff and estimating; and Docs, for managing construction documents.
AI can help automate computer-aided manufacturing (CAM) tasks, eliminating tedious work that consumes substantial human resources. By freeing up engineers and designers to concentrate on innovation, manufacturers can advance production of current products and accelerate the launch of new products. For example, in the automotive industry, AI can be used to optimize a vehicle’s aerodynamics and structural design while maintaining aesthetic and functional requirements. Further downstream, AI can use machine vision to detect manufacturing issues in real time, improving project quality and reducing costs. Autodesk has leveraged AI technology in its Autodesk Fusion platform to automate toolpath design and other CAM processes.
AI can help with design aesthetics early in the design process and detect manufacturing issues in real time, helping you reduce costs. Image source Humeyra/stock.adobe.com.
Third-party tools can also be used to leverage AI. T2D2, for example, provides an Inspection Cloud and an AI Damage Detector that work together to streamline data capture and analysis, monitoring, and damage assessments for construction applications. The tools use computer vision trained by numerous forensic images to recognize deterioration and catalog exterior inspection data. A variety of other third-party solutions are available to help track safety, maintenance, and construction progress.
Construction quality can also benefit from AI technology. Using tools from Autodesk and other providers, teams can accelerate and automate processes such as managing punch lists. “You can tie in issues from a construction standpoint,” said Scott Wolslager, Senior Engagement Manager at IMAGINiT Technologies. He cited examples such as improperly tightened bolts and cracked concrete that can be prioritized on punch lists using AI. IMAGINiT works with clients to leverage technology in AEC-related industries, as well as manufacturing, utilities, government, and other areas.
Along with quality management, AI can help manage budget and cost control issues. For example, if project requirements call for a certain type of chiller to be installed in a building, AI can search for alternatives and generate a request for information (RFI) to consider other equivalent equipment. AI technology can determine if the alternative meets cost and technical requirements and guide the approval process.
Autodesk Forma provides AI-powered tools, for example noise similation, which can help you resolve issues early in the design process. Image source: Autodesk.
Design Applications
Use cases for AI in design are still maturing, but some organizations are finding success with commercial and custom AI tools. Autodesk Forma provides AI-powered tools for pre-design and schematic design, and has been used to set up geolocated projects with contextual data and model complex 3D designs. It connects with other tools such as Revit, Rhino, and Dynamo to develop designs,
and also includes tools for massing takeoffs and environmental impact analysis.
As an example, an architect could use Forma to develop a concept design for a building of a certain size on a certain site. The software can show alternatives on how to position the building on the site using generative AI technology. Applying AI further, if similar buildings were to be built on other sites, the designer could integrate other AI tools such as ChatGPT, Google Gemini, or CoPilot to identify other sites within certain regions that might be suitable for the building.
Other Autodesk products are also introducing AI technology, as noted in our second article. For example, the Markup Assist feature in AutoCAD can convert comments, identify handwritten text, add objects, and automate edits through recognized instructional text and strikethroughs from markup files, turning redlines into drawings. Autodesk Fusion uses AI technology to automate drawing, modeling, and product design in manufacturing-related processes.
Third-party AI design tools are also available for design applications. Bimmatch, for example, guides procurement of low-carbon building materials, coupling building material requirements with a material-matching engine. Other third-party tools help teams create and share digital twins for design, construction, manufacturing, and operation.
Advanced users can also use programming tools such as Python, C++, or Dynamo to develop custom AI tools. AI can also be used to help develop the code for custom applications, though human involvement is still required to get proper results.
Potential Pitfalls
Amidst all of the fervor generated by AI, organizations need to be mindful of potential pitfalls with AI. Without proper human involvement in managing AI output, inappropriate outcomes, or hallucinations, can result. People still need to guide AI inputs and closely review outputs to confirm results are realistic and accurate.
“You can’t automatically trust results,” said Wolslager. “For example, if AI was used for quality checking to verify code compliance, did the AI engine use the right code for your location? Human oversight remains essential for these critical decisions. Complacency can lead to liability and risk,” he cautioned.
Data security is another critical concern. “It’s essential to have a robust security model in place,” said Wolslager. “This model should outline clear policies on data usage, ownership, and password complexity to safeguard your information.”
Another key decision is whether to set up a private cloud for your organization or use a public cloud for data storage. If public, the cloud provider should meet standard industry best practices for data security, including data encryption and other security measures. Organizations should clearly understand whether the cloud provider shares your data with others or segregates it.
Data Management
To properly use AI, organizations need to have well-organized, accessible data. In our next article, we’ll explore the importance of data management when using AI.
As noted in our previous articles, you should work with an experienced partner to advance AI in your organization. With experience across entire project lifecycles and a wide range of industries, IMAGINiT Technologies can help you identify
potential benefits of AI for your organization and help you avoid the pitfalls.
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ARTICLE SPONSORED BY IMAGINiT Technologies.
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