Layla Zulfa
California-based FirstTeam Real Estate, a prominent brokerage that achieved $6.12 billion in transaction volume across 5,978 deals in 2025, ranking it No. 34 nationally for volume and No. 67 for transactions, has announced a significant strategic partnership with Purlin. This collaboration will see FirstTeam implement Purlin’s artificial intelligence (AI)-powered operating system across its entire brokerage network, aiming to revolutionize its operational efficiency and agent productivity. The integration signifies a major step forward in AI adoption within the real estate sector, moving beyond incremental applications to a comprehensive, AI-driven operational framework.
The partnership integrates Purlin’s suite of AI-driven solutions, including PurlinOS, Purlin Close, and Purlin Offer & Negotiate, into a unified platform. This consolidated system is designed to manage the entire lifecycle of real estate transactions, from contract initiation and negotiation to closing and client communication. A key feature of this integration is its multifaceted interaction capability, allowing agents to engage with the platform through voice commands, text messages, email, and a dedicated chatbot, catering to diverse agent preferences and workflows. This move positions FirstTeam at the forefront of brokerages embracing advanced AI for tangible operational improvements.
The announcement was accompanied by an in-depth discussion with HousingWire, featuring insights from Lauren Henss, Vice President of Marketing and Strategic Initiatives at FirstTeam, and Tim Quirk, Chief Revenue Officer at Purlin. Their conversation shed light on the current landscape of AI adoption in the real estate brokerage industry, exploring what differentiates truly transformative AI integrations from superficial software overlays. They also provided guidance on how brokerages can navigate the complexities of AI implementation to avoid costly missteps and maximize return on investment.
The Evolving Landscape of AI in Real Estate Brokerages
The integration of AI into the real estate sector is not a monolithic shift but rather an evolving process, with varying levels of adoption and understanding among professionals. Tim Quirk observed that the impact of AI is often incremental, depending on an individual agent’s fluency and willingness to embrace new technologies. While many agents are experimenting with AI for basic content generation, a more sophisticated tier of users is beginning to leverage AI to automate core business processes and streamline operations.
"We’re starting to see folks streamlining compliance coordination between contract to close with clients," Quirk explained. "There’s others on the front-end side automating marketing and lead nurturing, especially when it comes to sphere-of-influence type of things." However, he highlighted a prevalent challenge: the proliferation of numerous small software providers, each addressing a niche aspect of the transaction. This fragmented landscape makes it difficult for brokerages to identify truly impactful solutions and integrate them effectively into their existing workflows, often leading to an overwhelming array of disconnected tools.
Lauren Henss echoed this sentiment, predicting that a substantial majority of brokerages will undergo digital transformation in the coming years. She cautioned against the "shiny object syndrome," where the allure of new technology can distract from strategic implementation. "When you’re incorporating AI into anything, you look at the entire agent life cycle and you need to understand what you want this technology to do. What are the end goals of it? What do you hope to accomplish with it?" Henss emphasized the importance of aligning AI adoption with clear objectives, such as enabling agents to close more deals faster and enhance client service. The missing piece, she noted, is often a centralized, integrated platform that acts as the nucleus for these AI-driven capabilities, providing a cohesive experience that drives efficiency.
Distinguishing Successful AI Integration from Superficial Layers
A key differentiator between successful AI implementations and those that merely add complexity lies in their approach to adoption and integration. Henss stressed that effective deployment requires comprehensive education and support that meets agents where they are. This goes beyond standard webinars, necessitating communication and training that is accessible on demand, in person, and tailored to individual needs.
"The key that I have found is you need to use your agents as ambassadors," Henss stated. "You need to find some raving fans first, who are part of the process before it even launches. They’re in the software platform. They’re trying to break it, so they feel like they have personal ownership of that success. You’re building it around them." This co-creation approach fosters a sense of ownership and ensures that the technology is being developed and refined with the end-user in mind.
Measuring the return on investment (ROI) is also crucial. Henss looks beyond simple adoption rates to assess how AI impacts agent productivity, deal volume, and transaction value. Metrics like Net Promoter Score (NPS) and Customer Satisfaction (CSAT) are also vital indicators of success. The goal is not simply to introduce new software but to demonstrably improve an agent’s ability to close more deals in less time, directly impacting their bottom line and overall job satisfaction.
The Irreplaceable Human Element in Real Estate Transactions
Despite the rapid advancements in AI, certain aspects of real estate transactions will likely remain firmly in the human domain. Henss believes that agents who evolve into true advisors, rather than mere order-takers, will be the ones who thrive. "We know that there’s a certain amount of the population of agents who do a majority of the deals, and there’s like 1.6 million agents out there right now. I do think that will shrink," she noted, suggesting a potential consolidation in the industry driven by the need for higher-level expertise.
The core of an agent’s enduring value lies in their ability to provide nuanced advice, understand client motivations, and anticipate needs. Quirk elaborated on this, explaining that while AI can provide vast amounts of data about properties and markets, it cannot replicate the human judgment and emotional intelligence required for significant life decisions like buying or selling a home.
"If you’re going to go buy a property in a location that you’re not familiar with, you can get a lot of information online about it, but you still can’t get the particulars about that particular market, that particular neighborhood, what’s going on within that area. Along with, is it a good investment? Is it a good decision for you?" Quirk asked. He emphasized that most people engage in real estate transactions infrequently and require confidence from a trusted professional. This human element of reassurance and personalized guidance is something that technology, however advanced, cannot replace.
This human touch extends to complex negotiations and emotional considerations. While AI can facilitate the offer and negotiation process, the ultimate decision-making often hinges on factors beyond pure data. "At the end of the day, what you can’t replace is what someone is willing to pay for a property if they love it, if they want to raise their children in that neighborhood. They might way overpay just to be able to get into that market," Quirk explained. Understanding these deeply personal motivations and helping clients rationalize their decisions remains a distinctly human capability, supported but not supplanted by AI.
Safeguarding AI Implementation: Governance, Privacy, and Compliance
The implementation of AI in real estate necessitates robust governance and operational safeguards, particularly concerning data accuracy, privacy, and compliance. Quirk issued a strong warning about the misuse of general AI models for sensitive real estate transactions. "If you look at the spectrum of where people are in terms of their AI fluency – if you’re using an OpenAI model and starting to either try and create contracts or upload things that have personal information, you’re going to get yourself into trouble very quickly."
He highlighted the dangers of relying on generic AI platforms like Claude or ChatGPT for real estate advice, as these systems lack specific industry knowledge and can provide inaccurate or misleading information. This can lead to unrealistic expectations regarding property values or investment potential, potentially causing significant financial harm to consumers.
For brokerages, the adoption of AI solutions must prioritize platforms that possess a fundamental understanding of real estate rules, regulations, and fair housing principles. Rigorous internal testing is essential to validate the accuracy and reliability of these AI systems. "When it comes to contract compliance, as our clients adopt it and start to see it, all of a sudden they start to realize that it’s actually more accurate than the human when it comes to catching different issues and concerns," Quirk noted. This enhanced accuracy, when integrated into a consistent process, can improve compliance and reduce human error. Ultimately, the deployment of specialized AI in real estate is not about replacing human oversight but about augmenting it, allowing professionals to focus on higher-value tasks. The potential benefits extend to insurance, with providers increasingly factoring AI deployment into risk assessments and potentially offering lower premiums for brokerages that demonstrate reduced human error rates.
Defining and Measuring Return on Investment with AI
To effectively gauge the success of AI investments, brokerage leaders must move beyond superficial metrics and focus on tangible business outcomes. Henss advocates for a deep dive into "time to value" and "true adoption." This means tracking not just monthly usage but daily engagement and the average session length within AI-powered platforms.
"I want utilization numbers. I want to know what areas of the AI that they’re using, like the average time per session," Henss stated. By analyzing where agents spend their time within the AI tools, brokerages can identify which functionalities are most effective and which may require refinement. For instance, if agents are consistently engaging with AI-driven marketing tools for extended periods, it signals a successful application of that technology. Conversely, if agents are not utilizing features designed for growth projections or metric tracking, it suggests a need to re-evaluate the interface or user experience to encourage engagement with these critical areas.
"Because we know that those areas are working," Henss explained. "For example, in our platform, if they’re sitting here and they’re going to the marketing section of AI, they’re using that daily. I have 60% of agents in there daily with an average session time of 20 minutes per day. I would consider that a success." This granular approach allows for continuous improvement and ensures that AI investments are directly contributing to the brokerage’s strategic objectives.
Strategic Guidance for Independent Brokerages Embarking on AI Adoption
For independent brokerages that have yet to fully embrace AI, a strategic and phased approach is paramount over the next 12 to 24 months. Quirk advises seeking guidance from trusted resources and conducting a thorough assessment of their current business and technology ecosystem. "AI for the sake of AI doesn’t do anything," he cautioned. "Don’t just jump in. You see something that looks cool and you just go with it without looking at what else is out there."
A common pitfall is adopting solutions that appear impressive but fail to integrate with existing systems or, worse, create additional work. A truly effective AI solution should seamlessly augment current workflows, not disrupt them.
Henss concurs, emphasizing the need for a comprehensive business audit. "What are your business goals now, but also what are your business goals over the next three years? Is that expansion? Is it agent recruitment? What is your overall retention rate now and why do agents leave your brokerage?" Understanding these fundamental business drivers is essential for selecting AI tools that address specific needs and contribute to long-term success. She also stresses the importance of leadership buy-in and establishing a dedicated team responsible for measuring success and ensuring alignment between the vendor and internal stakeholders. By prioritizing strategic alignment, agent-centric adoption, and a clear understanding of business objectives, independent brokerages can successfully navigate the AI revolution and unlock its transformative potential.
