AI in AEC: Where firms should start and how to scale adoption

Artificial intelligence (AI) adoption in the AEC industry is surging, with 53% of firms now using AI tools, according to the 2025 Deltek Clarity Architecture & Engineering (A&E) Industry Study.

But for architecture, engineering, and construction firms, the real question isn’t whether to use AI—it’s where to start and how to apply it effectively.

AI is increasingly viewed as an amplifier of expertise rather than a replacement for human skills. Still, for many firms, knowing how to integrate AI into existing workflows remains a challenge.

Where AEC Firms Should Start with AI Adoption

For many AEC firms, the most effective way to begin is by focusing on practical, high-impact use cases.

Strong starting points include:

• Automating repetitive administrative tasks such as documentation, formatting, and data entry
• Improving early-stage design decision-making with AI-assisted analysis
• Using AI assistants for research, summarization, and workflow support
• Standardizing and centralizing data to enable better AI outputs

Racel Amour, Head of Generative AI, AEC at Autodesk, emphasizes that a strong data foundation is critical.

“Organizing your data with clear standards, such as consistent naming conventions and structured formats, will make it easier for AI to deliver value,” says Amour. “We recommend centralizing your data in a common data environment so it’s accessible, secure, and interoperable across teams and tools.”

Before that, however, firms should ensure they fully understand the problems they are trying to solve.

How to Identify the Right AI Use Cases in AEC

Rather than forcing AI into workflows, firms should identify problems where AI can deliver measurable value.

Look for challenges that:

• Have accessible or easily obtainable data inputs
• Require dynamic or variable decision-making
• Involve repetitive, time-intensive processes
• Are prone to human error or inconsistency
• Require synthesizing information from multiple sources

AI Case Study: Barge Design Solutions

Architecture and engineering firms like Barge Design Solutions have seen attempts to force AI solutions into problems that aren’t fully understood yet. AEC firms should first pinpoint where AI could save time, reduce errors, or improve decision-making.

• Problem: Ensuring every field project included a compliant health and safety plan without adding workload
• Solution: An AI-powered Health and Safety Plan (HaSP) Assistant using historical data and government regulations
• Impact: Reduced plan creation time from 8–10 hours to just 10–15 minutes

This type of targeted application highlights how AI can streamline workflows while improving consistency and compliance.

“Look for problems where you have the needed inputs—or can easily obtain them—but where the answer requires dynamic or somewhat variable logic,” suggests Justin Graham, Director of Innovation, and Jake Dein, Senior Solutions Engineer, Barge Design Solutions.

High-Value Generative AI Use Cases in AEC

• Synthesizing information from multiple sources
• Adapting templates based on project-specific conditions
• Generating structured content that requires customization
• Scaling consistent outputs across multiple projects

How Leading AEC Firms Are Using AI in 2026

Many firms are already applying AI across design, construction, and operations.

Gensler

• Real-time rendering and scenario modeling
• AI-generated video and immersive design previews
• Tools that analyze the carbon impact of design decisions using project data

Turner Construction

• Mining and analyzing data from internal data warehouses
• Streamlining the drafting of more than 30,000 trade contracts

DPR Construction

• Combining AI with reality capture for complex data center projects
• Healthcare applications, including:
  • Automated validation of rough-in work
  • Real-time anomaly detection
  • Simulation of build sequencing to identify bottlenecks

These examples demonstrate how AI is already delivering measurable efficiency, insight, and innovation across the AEC industry.

How AEC Leaders Can Prepare for AI Adoption

Successfully implementing AI requires both technical preparation and cultural alignment.

AEC leaders should focus on:

• Communicating how AI will support—not replace—team members
• Prioritizing practical, time-saving applications
• Providing training on AI tools and workflows
• Ensuring transparency around how AI is used
• Starting small and scaling based on proven success

Amour encourages leaders to keep the conversation grounded and approachable:

“Focus on how AI is a tool that gives your team more time to focus on finding creative solutions to problems," says Amour.

FAQs About AI in the AEC Industry

What are the best AI use cases in AEC?

AI is most effective for automating repetitive tasks, synthesizing data, improving design decisions, and generating project documentation.

How should AEC firms start using AI?

Start with small, high-impact use cases and ensure your data is organized, standardized, and accessible.

Is AI replacing jobs in the AEC industry?

AI is more commonly used to augment human expertise, helping professionals work more efficiently rather than replacing them.