The most popular type of AI tool used by survey respondents was writing tools (77.93%), followed by Chatbots or AI assistants (47.03%), image editing tools (39.19%) and market analysis or pricing tools (38.74%).
Reflecting this, the areas AI delivers the most impact, according to respondents, include writing listing descriptions (68.47%), creating social media content (59.46%) and writing emails or newsletters (53.15%). Despite heavy AI adoption regarding these routine tasks, respondents’ confidence in AI drops when it comes to using AI for pricing, interpretation and compliance-sensitive client conversations.
In addition, 63% of respondents cited accuracy of outputs as their top concern when it comes to AI usage. Other top concerns included compliance or legal issues (cited by 49%), misinterpretation of market data (47%), learning curve for AI usage (30%) and fair housing concerns (28%).
Despite their concerns, roughly 67% of respondents are either somewhat confident or confident in using AI-generated content with clients. However, nearly 17% reported feeling “not confident,” while 17% reported feeling “very confident.”
“AI adoption is no longer the question. Agents are already using it,” Reggie Nicolay, RPR’s senior vice president of marketing and training, said in a statement. “The real opportunity now is confidence. Confidence in output quality, confidence in compliance and confidence in how AI is used in client conversations.”
Based on these results, RPR said that now that agents have widely adopted AI, trade organizations and brokerages need help provide stronger training on AI usage. Supporting this assertion is that of the respondents who cited barriers to using AI more regularly, the most common barrier was not enough training (16.82%), too many tools to choose from (15.91%) and not being sure where to start (12.73%).
Respondents said the most helpful forms of AI training would be short video tutorials (69%), hands-on workshops (57%) and use-case training tied to real tasks like CMA creation (56%).
“These findings point to a practical reality,” Nicolay added. “Agents are not resisting AI. They’re using it where it adds clear value and asking the right questions where risk is higher.”
