As the AEC industry looks toward 2026, leaders are reassessing how their firms are positioned to deliver work reliably, manage risk, and scale in an increasingly complex environment. Conversations with executives across architecture, engineering, and construction reveal a consistent shift away from tool-centric decisions toward more fundamental questions about data, governance, and operational alignment. The focus is no longer on adopting what is new, but on building systems that support consistent outcomes across projects, teams, and regions.
Insights from industry leaders reveal several defining themes shaping the sector today, which are explored in detail in The 2026 State of AEC: Positioning for Growth in a Transforming Industry on-demand webinar.
From AI Buzz to Operational Intelligence
Artificial intelligence has shifted from experimental curiosity to a serious operational consideration. But leaders caution against viewing AI as a standalone solution.
As Joseph Gaffney, Director of Design Technology Services, notes, “AI is just one of the tools related to data. The foundation is still how you treat and manage your data.” This perspective reflects a broader realization across the AEC industry: without strong data governance, AI cannot deliver meaningful value.
What is changing is the nature of AI adoption itself. Rather than isolated tools or novelty use cases, firms are beginning to embed intelligence directly into workflows. As Susan Koenigs, Director of Digital Practice, explains, “AI is no longer experimental. The real shift is moving from general-purpose tools to embedded, agentic workflows that actually change how work gets done.”
This transition marks a turning point, where AI becomes less about experimentation and more about enabling consistent, scalable outcomes.
Productivity Pressure and the Rise of the Digital Worker
Labor shortages and growing project complexity continue to strain the industry. Hiring alone is no longer enough to close the gap. As a result, firms are increasingly viewing AI as a productivity multiplier rather than a replacement for talent.
Digital agents are being positioned as support resources, handling repetitive, time-consuming tasks so experienced professionals can focus on higher-value work. This approach helps reduce burnout, maintain consistency, and improve throughput, especially in environments experiencing rapid growth or frequent mergers and acquisitions.
Rather than “hiring” AI, firms are assigning it responsibilities within defined guardrails. The emerging model is clear: AI prepares, flags, and accelerates and people decide, validate, and deliver.
Data Is the Foundation, and the Bottleneck
Nearly all firms agree that data is their most valuable asset, yet many struggle to fully leverage it due to fragmentation and interoperability challenges. Data sprawl across disconnected systems remains one of the biggest barriers to meaningful transformation.
As AI adoption grows, so does the recognition that intelligence is only as strong as the data behind it. Industry leaders are shifting their focus away from software silos and toward data-centric strategies, normalizing information, leveraging APIs, and developing internal tools that treat data as the true source of truth.
The common data environment (CDE) is becoming central to this conversation, with growing momentum toward contractual requirements. However, the biggest hurdles are no longer technical. Questions around data ownership, stewardship, liability, and long-term access are slowing adoption more than software limitations ever could.
Governance, Security, and Data Sovereignty
As firms rely more heavily on large language models and custom AI agents, concerns around data protection and intellectual property are intensifying. Misconceptions persist in how AI tools use data, making education and literacy critical. Leading organizations are responding with clear policies, AI literacy initiatives, and project-level data execution plans. These frameworks help teams understand what information can be shared, how tools should be used, and how compliance requirements, such as CMMC and client-specific mandates, are met.
Rather than focusing solely on tools, firms are emphasizing intentional decision-making, understanding intent, risk, and outcomes before choosing technology. This mindset is becoming essential as regulatory expectations continue to evolve. Interoperability, Open BIM, and Workflow-Centered Thinking
As conversations around interoperability mature, many firms are reframing how they think about standards and collaboration.
Susan Koenigs, Director of Digital Practice, summarizes this shift succinctly when she says, “Open BIM is not a tool. It’s a philosophy.” Rather than focusing solely on software compatibility, this mindset emphasizes openness, flexibility, and long-term resilience. The goal is to enable teams to collaborate seamlessly across platforms while retaining the freedom to choose the tools that best support their workflows.
Standards such as IFC 5.0 support this vision, but industry leaders agree that true progress comes from understanding workflows first, then applying technology intentionally.
Letting Go of Legacy Practices
One of the clearest signals of industry evolution is a growing willingness to retire outdated workflows. Manual, end-of-project quality control processes, disconnected tracking systems, and overreliance on single-model sources of truth are increasingly viewed as risks rather than safeguards.
Firms are recognizing that automation, continuous QA/QC, and data-driven checks are not just efficiency gains, they are essential for managing scale, reducing liability, and maintaining consistency.
Looking Ahead
The AEC industry is not undergoing a single transformation, but many, technological, cultural, and contractual. The firms best positioned for 2026 are those grounding innovation in strong data foundations, clear governance, and a deep understanding of their workflows.
As leaders navigate the pace and pressure of change, there is also a growing recognition that this transformation is not something firms should tackle in isolation.
As Joseph Gaffney, Director of Design Technology Services, reminds the industry, “This is happening to all of us. Don’t try to figure it out on your own. Find your people.”
AI will continue to evolve, but its role is becoming clearer, not as a replacement for expertise, but as an accelerator of it. As the industry moves forward, success will depend less on chasing what’s new and more on building systems that are intentional, adaptable, and resilient.
The future of AEC is connected, data-driven, and human-led, and that future is already taking shape.
If your firm is ready to partner with experts to drive digital transformation for smarter, faster project delivery, ARKANCE can help. Discover how we empower AEC professionals to achieve better project outcomes by leveraging data, connected workflows, AI, and strategic consulting.