Building Connections Episode 9: AEC Firm Structure, AI Adoption, and the Metrics That Will Define the Next Five Years
AEC firm strategy is being stress-tested from multiple directions at once; private equity, AI, ownership transitions, and a shifting performance landscape. To cut through the noise, we sat down with Rebecca Zofnass, Managing Partner at EFCG (Environmental Financial Consulting Group). Founded in 1990, EFCG is an investment bank and management consulting firm that works exclusively with architecture, engineering, and consulting firms, tracking data on roughly 300 privately held AEC firms every year. Here is what the data says and what it means for firm leaders making decisions right now.
Is employee ownership still the right model for AEC firms?
PE-backed firms now represent about 16% of AEC firms above $30M in revenue, which has gone up fast over the last five years but, employee-owned firms still hold 60%+ of the market. The real question is not which model is winning. It is whether your firm is managing the trade-offs of your current model well. Before any structural conversation, Rebecca recommends getting clear on three things: Can you fund your ownership transition internally? What do your shareholders actually want? And what growth rate are you targeting? The answers should drive the decision.
What KPIs should AEC firm leaders be tracking today?
Utilization. Billable hours as a share of total hours has defined AEC firm management for decades. That era is ending. As AI and technology reshape delivery, the leading indicator of firm health is shifting to revenue per FTE and profit per FTE. Firms that are still optimizing for utilization are measuring inputs at the moment the industry is beginning to reward outputs.
How should AEC firms approach AI adoption in 2026?
EFCG already sees proven ROI from AI on the cost side: contract review, proposal prep, and back-office workflows. Rebecca's practical guidance for any AEC firm regardless of size: spend the next 9–12 months organizing your data and build the habit across your team of asking 'is this a good use case for AI?' before defaulting to how work has always been done. Those two steps will compound faster than any software investment.
What is the risk of employees using AI tools with company data?
Free AI models may use inputs to train their underlying models by default, meaning confidential firm data entered without a paid, secure account could end up in the model. Every AEC firm needs a written AI code of conduct that establishes, at minimum: required use of paid/secure accounts, clear guidance on what data is and is not appropriate to input, and employee education on where these tools are reliable and where they are not. This is a governance gap most firms have not yet closed.
Watch the full Building Connections episode for Rebecca's complete take on AEC firm structure, the private equity landscape, growth strategy, and the 5-year industry outlook.
Learn more about EFCG:
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