Growth of AI Text Tools
The use of artificial intelligence (AI) tools, especially text-based generator AI, is continuing to increase. Almost two-thirds (64%) of those voted using text-based tools at least weekly. in fact, The change in AJ's practice survey was filmed by about 200 people, mainly by UK-based architects and students.revealed that 40% use large language models every day.
As one respondent said, “I regularly use ChatGpt for simple text-based tasks. On bidding documents, presentations, planning documents, and building management statements.
“These are all very common uses and are by no means innovative, but they allow for a more efficient approach, save time and reduce the need for a larger team.”
In comparison, only 26% said they used AI for image-based tasks or image generation at least weekly, but only 8% relied on each day. This contrasts with only 11% of respondents. 2024 Survey Who said they use all kinds of AI every day.
How, when, and why do architects use AI?
The rise in AI as a text generator is reflected in the most popular among AJ leaders and the most popular among the tasks that are performed on a regular basis. Chat GPT is currently used by 77% of respondents, but Microsoft Copilot usage doubled from 13% in 2024 to 27%.
Interestingly, compared to last year, the use of image models from two texts has significantly reduced. Stable diffusion fell from 21% to 8%, while Midi Joanie fell from 42% to 22%.
When architects rely on AI, the survey shows that a significant percentage (39%) was used in requests at the proposal or bid stage. This is the same percentage used in concept design. Similarly, more architects use AI for practice management tasks (over 40%) than for early feasibility tasks and competitions (33%). It looks like AI applications in Business applications will also grow. 38% say they are using AI to “exploring options” in this area.
AI is increasingly being used not only for the interests of the architects themselves, but also for both within practice and for clients. The percentage of people who said AI is being deployed for reasons that “internally and in the face of clients” has increased from 48% in 2024 to 60% this year.
Barriers using AI
Inaccuracy was the most commonly cited barrier to actually using AI. 55% of respondents said that many people block absorption when they have to thoroughly check the materials produced. This was followed by “generic or insufficient output” (47%).
Last year's top blocker, lack of knowledge and expertise (42%), was also a major concern, as was the lack of time to learn, uncertainty about actual benefits, and carbon costs.
Financial costs were cited as a barrier by 17% of those voted. One respondent said, “The cost of trying the tool could even be banned for testing.”
However, 60% of those who voted said their practices had no formal budget approved for AI spending (up 69% for practices with fewer than 10).
As to whether the practice itself has stopped staff from exploring generation tools, 47% said they were unaware of restrictions on AI use. This suggests that companies are more open to experimentation. The figure for 2024 was 32%. Only 2% said they were banned from using AI.
Future use in practice and higher education
With plans, many architects are considering how AI can help with tasks such as budgeting, contract compliance, and automating proposal requests.
Given the lack of investment promised for AI development, there appears to be little strategic thinking, but over half of respondents (56%) said they plan to integrate AI into a more broadly common daily workflow. This is up from 49% in 2024.
Most people recognize that these advancements, particularly the incorporation of text-based tools, will affect how future architects will be taught. Over three-quarters of those surveyed say AI will affect architect education.
Stephen Parnell, a former senior lecturer at Newcastle University and AI consultant, said AI “will affect every life” and “fundamentally change higher education.”
He told AJ:
“Essays as evaluations are as good as they are already dead, and teachers need to concentrate more on the process and less on the product. Perhaps architectural education is not in the university after all?”
The impact of opportunity, danger, and productivity
Respondents split over whether they view AI as a threat or an opportunity to advance their profession. There were real concerns about the loss or misappropriation of their intellectual property. However, architects were generally more optimistic than pessimistic about how AI could improve its prospects and how it could improve in a more productive way.
Again, there was a significant difference in how we viewed the benefits of language-based tools compared to generative visualization applications.
When asked how text-generating AI tools have an impact on productivity, 72% said AI would increase productivity. This dropped to 52% due to image generation.
It was widely recognized that AI's unstoppable forward momentum would change the way architects work. A quarter (26%) thought that the emergence of AI would lead to a “fundamental change into architectural practice,” but it rose to 35% in practice 10 stories downstairs, but instead “53%), which rarely raises brows, has seen a noticeable change in some parts of the architect.”
One respondent said: “It's the same as when CAD comes in. People are expected to be more productive, so there's a commercial advantage to the practice of taking it in the short term. But when it's ubiquitous, people who don't use it fall on the roadside.”
Comment: Keir Regan-Alexander, Director of Arka Works
AJ's research revealed the paradoxes that are conveyed. 64% of architects use text-based AI Weekly, but 60% of practices don't have a formal AI budget.
This cutting between massive grassroots adoption and lack of institutional strategies explains what I call a “pain washing machine.” This is a cycle in which teams become excited by the possibilities of AI, unhappy with the ad hoc outcomes, then retreat to the familiar ways.
The survey data examines several important trends we observe on the ground.
The growth in Midjourney usage (42% to 22%) and ChatGpt's advantage (77%) indicates a clear flight to the utility.
Text-based tools solve immediate daily problems, such as drafting reports and analyzing briefs, but image generation requires critical skills to integrate beyond general results into professional workflows.
Similarly, the discovery that AI is used to request proposals and bids emphasizes that, like concept design, real concrete values have been found. This organic adoption is happening in a governance vacuum, creating a “shadow AI” economy where staff use personal or free tools to fill strategic blanks. This is not just a risk in terms of privacy and accuracy. The failure of leadership to utilize is the clearest possible signal of proven demand.
The pulling practices ahead are those that have the most advanced software, not those that have the plan
This makes us an important point. The main barrier to achieving value from AI is not to sourcing the right technology. The market is saturated with tools. The real challenge is one of the behavioral changes, and the gradual systematic adaptation of existing workflows.
The pulling practices ahead are those that have the most advanced software, not those that have the plan. They systematically map opportunities to identify simple, impactful, low-risk applications. They are building a repeatable, quality-controlled prompt workflow that turns individual experiments into reliable team assets. They create an integrated culture of change. There it is woven into the structure of how new features work.
Research shows that a grassroots AI revolution is already underway. The question of leadership is not whether AI is actually used, but whether its adoption is strategic and value-driven or contingent and confusing. Technology is no longer a bottleneck. That's what we are willing to adapt our systems.
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