By Rebecca W.E. Edmunds, AIA, MFA, 2026 PMKC Chair, with Google Gemini
“AI is less about automation and more about amplification. Done well, AI does not replace people, it empowers them to do their best work.”
– Evelyn Lee, FAIA, NOMA, 2025 AIA President, "Amplification, not automation," AIA Architect, September 4, 2025
Artificial intelligence (AI) is reshaping industries worldwide. News of unprecedented efficiencies and innovation are everywhere. Many AIA25 sessions highlighted AI’s uses and value. Yet, in architecture, full AI adoption in business functions--I’ll leave the project design side to others--like finance, human resources, marketing, and training lags. We’ve discussed AI as a management tool in previous PM Digest editions, but complex practical concerns, ethical dilemmas, and deeply held values about human creativity have kept many firms from fully integrating AI into their operations. The focus has shifted from simple large language models (LLMs) to specialized, AEC-specific tools, and "Agentic AI" that can manage multi-step, complex business tasks.
As someone who is always playing with AI, I thought I’d employ Google Gemini to explore our industry's cautious approach to AI, with pros and cons.[1]
The Allure of Algorithms: Perceived Business Benefits of AI in Architecture
For those professionals and firms embracing AI, the advantages are compelling:
- AI can revolutionize financial planning. It automates data collection and analysis, accelerating budgeting and forecasting cycles. AI tools offer real-time scenario adjustments, allowing firms to quickly adapt to volatile market conditions by instantly updating financial projections. This leads to enhanced collaboration between finance and other departments with visual modeling, making complex financial concepts accessible. AI also supports data-driven decision-making, providing recommendations for resource allocation and strategic investments, and it can help control manual errors in data processing, reducing costs. Several financial offerings exist; even OpenAI has a financial management subscription.
- AI can automate time-consuming HR tasks. In our last issue, I shared how AI can sift and screen applicants, schedule interviews, and customize interviews, freeing HR for more strategic activities. It aids decision-making by providing data-driven insights for hiring, promotions, and workforce management. AI can personalize employee relationships by recommending tailored training based on performance and career goals, identifying opportunities, and monitoring employee sentiment to address dissatisfaction early. Chatbots can provide 24/7 support for employee onboarding and common queries.
- AI can enhance a firm’s marketing efforts. It automates repetitive, time-consuming tasks, such as keyword research, content optimization, and social media scheduling. AI can analyze data-driven insights into content performance, audience behavior, and industry trends, enabling firms to produce content that resonates with potential clients. AI-integrated visualization tools allow architects to generate instant design options for client presentations, enhancing engagement. On a more basic level, AI is a great source for templates for press releases, hiring or retiring announcements, and project news blasts.
- AI can personalize employee training. By analyzing individual performance and career goals, AI can uncover specific courses that address their needs for any aspect of firm operations, including the practical application of AI tools in design, effective prompting, and transforming sketches and models into detailed renderings. This “upskilling” can ensure greater job competency in an evolving landscape. Firms can utilize AI to identify skill gaps and tailor learning paths for their teams. Most of us are familiar with programs like Grammarly and ProwritingAid, which are a form of training on the basics of writing. Firms are also now leveraging internal AI systems (often called RAG) to create central, searchable knowledge bases, turning years of project documentation, specs, and internal standards into an instant training and reference resource for all employees.
The Human Element: Concerns and Drawbacks of AI in Business Practices
Despite all the promise, many in the architectural community remain wary and express concerns:
- Initial investment in AI software. AI requires robust, costly infrastructure. While high-performance server and cloud integration costs remain a concern for large-scale adoption, the barrier to entry for many smaller firms has lowered. This is due to the proliferation of low-cost, subscription-based specialized AI tools that can be integrated incrementally, softening the immediate financial impact. Operational costs, including software updates, maintenance fees, and increased energy consumption for computational power, also contribute. And, without paying for secure, enterprise-level AI, your sensitive information may become fodder for the general AI data cloud.
- Integrating AI into established workflows and software ecosystems can be challenging. Many of us lack formal training in AI. These skill gaps require significant investment in training. Self-directed learning is prevalent but may not be scalable or efficient enough for firm-wide adoption. And the challenge of aligning AI implementation across departments can lead to inconsistent user adoption.
- AI models are only as good as the data they’re trained on. Inaccurate, incomplete, or biased data can lead to flawed financial predictions, HR decisions, or marketing strategies. Firms also worry about over-reliance on AI reducing critical human oversight and decision-making.
- Privacy and security of sensitive client, project, financial, and employee data. Ensuring privacy and security with any cloud-based system is paramount. Costs to secure data for every staff member can add up. Then there are the ethical implications if breaches occur.
- Intellectual property and copyright for AI-generated content in marketing are also issues. The legal landscape remains highly fragmented, with little clear precedent on ownership and usage rights for content derived from training on copyrighted works.
- AI's role in decision-making raises ethical questions. Hiring algorithms can have inherent biases. Financial forecasting could lead to financial risk. Accountability—who is responsible if an AI-driven financial model leads to losses or an AI-generated marketing campaign misrepresents a firm's capabilities—remains a concern.
- The industry has historically been slow to adopt new technologies. Firm leaders and staff alike may be hesitant to embrace the level of change AI implies. Automating tasks could diminish human control over intricate financial processes, nuanced HR interactions, creative marketing messaging, and tailored training approaches.
- AI can “hallucinate.” Incorrect or nonsensical outputs ("hallucinations") could be detrimental however you use AI. The lack of transparency in how some AI models generate their results raises concerns about trust and verification, making it difficult for firms to fully rely on AI outputs without extensive human validation.
The Path Forward: Strategic Integration and Human Augmentation
AI can enhance, rather than replace, human expertise in business operations. Putting AI to use in architectural practice requires a strategic approach to data-intensive tasks, automating repetitive processes, and providing rapid insights across finance, HR, marketing, and training. The result: human professionals get more time to focus on strategic planning, nuanced decision-making, fostering client relationships, and injecting the human touch into every aspect of business. And, of course, vigilance and human oversight of AI data and results.
For robust AI adoption, our industry must address challenges around cost-effective implementation, robust data security, ethical guidelines, seamless software integration, and development of more AEC-specific AI tools. As we overcome these challenges and firm leaders gain clarity and confidence in AI's reliability and relevance, the industry's hesitancy with AI can become more harmonious and productive, driving both design innovation and business growth.
Footnotes
- As with any AI that uses the LLMs (large language models), the results required significant editing and reshaping. On top of everything, AI likes jargon and, for lack of a better term, flowery language.
Sources:
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A licensed architect, Rebecca W.E. Edmunds has devoted much of her career to an alternative practice model—providing leadership in creating consistent, comprehensive communications, branding and writing on design, management, leadership and technical performance for firms across the country. She also serves as a ghostwriter for architects nationally, which requires regular research into evolving design issues for health and wellness, K-20 education, urban mixed-use development and the workplace. This work informs her service on the Practice Management Knowledge Community and in various positions for AIA Virginia.
(Return to the cover of the October 2025 PM Digest)