The infrastructure industry stands at a transformational crossroad. For the first time in the history of civil engineering, we’re witnessing a technological shift so profound that it rivals the introduction of CAD itself. Artificial intelligence (AI) isn’t just another software upgrade—it’s fundamentally changing how engineering firms compete, deliver, and create value.
The question is no longer whether AI will transform your firm. The question is: Will you lead this transformation, or will you be forced to follow? Industry experts including Kyle Rosenmeyer, Bentley Model-Based Design Lead, VHB, Mark Coates, Vice President of Infrastructure Policy Advancement, Bentley Systems, and Scott Urbas, Manager, Civil Content Development, Bentley Systems, spoke to the State of AI in the podcast hosted by Engineering News Record (ENR) named “The State of Infrastructure AI.”
AI Adoption in Infrastructure: Data-Driven Leaders are Already Ahead
Recent survey results found in “The Impact of Artificial Intelligence on the Build Environment” report paint a clear picture of the current landscape. According to the report, 40% of organizations are already using or trialing AI to improve productivity in design and engineering processes. Another 43% have implemented AI for automating document-heavy workflows like contract drafting, RFIs, and change requests.
These leaders actively using AI or actively piloting are all gaining ground while others hesitate. Another benefit that Mark Coates mentioned is how AI and data go hand in hand. Firms with quality infrastructure data are now securing lower interest rates from insurers and financiers. Mark said “Good value data, good value insights […] is getting you lower interest rates […] now you’re starting to see people value that data because it has a value for them.” Mark Coates is also the co-author of the whitepaper “How Finance and Digital Twins Can Shape a Better Future for the Planet.” In this whitepaper, the authors found that a key driver for this shift is the increasing demand from the financial community for better data to de-risk investments and meet Environmental, Social, and Governance (ESG) mandates.
As the earlier whitepaper highlights, your data isn’t just an operational asset anymore—it’s a financial one. In the whitepaper, for instance, real estate investment trust Great Portland Estates secured a 450 million euro credit facility where the interest rate can be reduced by up to 2.5 basis points based on performance against its ESG targets which are targets that rely on high-quality asset data.
The market is already rewarding digital maturity, and that reward is measurable on your bottom line.
The Productivity Revolution with AI powered Capabilities
Imagine your engineering teams exploring hundreds of design options—considering cost, carbon impact, and constructability—in minutes instead of weeks. That’s not a future vision. That’s happening today with generative AI tools. The survey results show current use cases include real-time tracking of site progress, delays, resources, and quality, real-time monitoring for predictive maintenance and performance, and automating document processes, just to name a few.
Kyle Rosenmeyer shared that he has a team member who’ve said, “I can’t learn without it” when referring to their AI learning assistant on Bentley software. Rosenmeyer recently presented at a couple of Bentley User Conferences to share with other engineers on how he’s built a copilot for Bentley software to accelerate learning for his team. When your workforce becomes dependent on a tool because it makes them that much more effective, you know you’ve found something transformative.
Why AI Empowers Engineers Instead of Replacing Them
Let’s address the elephant in the room which is job displacement fears. Bentley’s vision is for AI to augment the work that engineers do—not replace them.
You can think of AI as giving your engineers superpowers:
- The ability to process massive datasets faster than ever before
- The capacity to find patterns and insights within infrastructure data that would otherwise remain hidden
- The freedom to focus on strategic decisions rather than repetitive tasks
At the end of the day, you still need an engineer. As Kyle mentioned in the podcast, the concept of requiring a “human in the loop” is going to stick around for a long time in our industry. Scott also added “AI should not be feared as a job replacement tool. Instead, it should be viewed as a personal engineering assistant or virtual co-worker that helps designers quickly obtain answers and make better engineering decisions.” AI provides insights, but it’s the people that provide the judgment, creativity, and requirements that infrastructure projects demand. AI is a tool to enhance capabilities, not replace people.
AI and Digital Twins: Unlocking the Next Era of Digital Delivery
Here’s where it gets exciting. For years, in this industry we’ve talked about digital twins, model-based design, and BIM. But the true value of structured, high-quality infrastructure data is now really becoming apparent. When you combine well-structured 3D models and digital infrastructure data with AI tools and optimize that data and workflows for digital delivery, you create something powerful. As a result, organizations learn faster, deliver smarter products, and adapt quicker than their competition.
How to Implement AI in Infrastructure Projects: A 4-Step Roadmap
The firms winning with AI aren’t the ones with the biggest budgets or the most technical expertise. They’re the ones who start smart and scale strategically. During the podcast, Kyle, Mark, and Scott shared tips on the following when asked what recommendations they would provide for someone looking to implement AI in their organization.
1. Establish Governance and Data Security First
Every successful AI implementation begins with a responsible use policy. Set your guardrails early including ethics, data standards, and data security policies. Define where AI can and cannot be used. Make sure that humans remain accountable for all critical decisions. This foundation builds trust with your team and protects your firm.
2. Start with Learning as Low-Risk Automation
Don’t try to solve your hardest problems first. Begin where the barrier to entry is lowest and the value is highest, such as workforce learning. You can Implement AI assistants that help your teams master Bentley software and navigate technical documentation faster. This builds confidence and demonstrates value quickly.
3. Focus on Problem Solving
AI implementation isn’t about buying the shiniest new tool. It’s about identifying specific business problems to deliver value in your infrastructure projects—whether that’s productivity, document automation, or design optimization—and finding the right AI solution for that outcome.
4. Invest in Your Data Infrastructure
The hard truth is that AI is only as good as the data you feed it. You need to invest time and resources ensuring your data is:
- Accurate and trustworthy
- Compatible across systems
- Consistently structured
Quality data is an AI prerequisite and the foundation of digital maturity that financial markets are already rewarding.
Act Now or Fall Behind: The AI Decision Facing Engineering Leaders
Every engineering leader faces the same decision today. You have the choice to wait and see how AI plays out, watching from the sidelines while competitors gain advantages in productivity, talent retention, and client satisfaction. Or you can act now. The survey data shows that 40% of your peers have already made their choice.
The AI revolution in infrastructure is here. The only question that matters is whether you’ll shape this transformation or be shaped by it.
Take the Lead on AI in Infrastructure
Top engineering firms are already using AI to deliver faster, smarter projects. Don’t get left behind. Explore how Bentley partners with engineering firms to implement AI digital delivery, and data-driven design.
