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5 Key themes shaping the future of AEC technology
Stefanie Richter
Business Development & Microsoft Partnership Manager, sa.global
Insights from EFCG Technology Leadership Conference
The conversations at this year’s EFCG Technology Leadership Conference reflected an industry at an important turning point. While AI continues to dominate headlines, AEC firms are asking much bigger questions: How do we improve profitability? How do we give our people better access to information? How do we make smarter business decisions? And how do we build a technology foundation that supports long-term growth?
Across the sessions and conversations, five themes consistently emerged – providing a clear picture of where leading AEC firms are investing their time, technology, and attention.
Scaling growth through technology
Growth remained a central focus throughout many of the discussions. While the AEC market continues to perform well, firms face ongoing pressure related to talent availability, project complexity, and margin performance. As a result, technology is now treated as a strategic enabler of growth, not a support function. Conversations focused on how automation, connected business systems, and AI can help organizations increase capacity, improve project delivery, and create operational efficiencies that allow firms to scale more effectively. The goal is no longer just efficiency – it is sustainable, profitable growth.
Rethinking utilization in an AI era
For decades, billable utilization has been one of the most important performance metrics in AEC and professional services firms. However, several industry leaders challenged the assumption that maximizing utilization always maximizes value. One phrase surfaced repeatedly throughout the event: ‘Utilization kills innovation’. The message was not that utilization is no longer important. Rather, firms operating at maximum capacity often struggle to create space for experimentation, process improvement, learning, and strategic thinking. As AI transforms how work gets done, organizations may need to reconsider how they balance productivity metrics with the investment required to drive innovation and long-term competitiveness.
AI adoption requires strong foundations
AI discussions have moved beyond the early stages of adoption. The question is no longer whether firms should adopt AI, but how they can deploy it responsibly, securely, and at scale. There was significant excitement around emerging capabilities and new ways of accelerating development and automation. At the same time, many speakers emphasized the importance of governance, security, architecture, and risk management.
As one speaker put it: “Don’t vibe code your way into a vulnerability”. The takeaway was clear: successful AI strategies require both innovation and discipline. Many firms have moved beyond initial experimentation and are now focused on governance, scalability, and identifying where AI can deliver measurable business value.
Data remains the foundation
Nearly every conversation about AI eventually led back to data. Many firms continue to face challenges around data ownership, governance, accessibility, consistency, and trust. While AI often dominates the headlines, the reality is that meaningful business outcomes still depend on having reliable, connected information. Several discussions highlighted that AI readiness is often less about selecting the right AI tool and more about ensuring data is accessible, trusted, and connected across the business. Without trusted data, organizations struggle to automate processes, generate accurate insights, and scale AI initiatives across the enterprise.
Technology is becoming a core business capability
Perhaps the most significant theme to emerge from the conference was a broader shift in mindset. Whether firms are designing buildings, delivering infrastructure, or managing complex projects, technology is increasingly becoming central to business strategy rather than a function operating behind the scenes. Technology leaders are being asked not only to implement systems, but also to help shape how work gets done, how decisions are made, and how organizations create value. Increasingly, they are expected to contribute to business strategy, operational performance, and growth initiatives – not just manage infrastructure and applications. As AI automates more routine activities, human expertise is shifting toward critical thinking, creativity, problem-solving, and decision-making.
Looking ahead
The conversations at EFCG reinforced that the future of the AEC industry isn’t just about engineering excellence and project delivery. It’s also about how firms use technology to improve productivity, make better decisions, foster innovation, and support long-term growth. The firms best positioned for future success will be those that can combine industry expertise with strong data foundations, connected operations, and a thoughtful approach to AI adoption.
Stefanie Richter
Stefanie Richter is a recognized leader in business development and Microsoft partnership strategy, focused on enabling service-based firms to scale with purpose and clarity. At sa.global, she leads the firm’s go-to-market strategy for the Microsoft Service-Centric Cloud, working closely with engineering, legal, and consulting firms to navigate transformation. With a background in sales strategy, operational enablement, and change culture, Stefanie brings a human-first lens to every conversation – championing clarity, trust, and innovation. She’s also an active member of ACEC and a driving force behind Microsoft AI adoption in the AEC industry.