In today’s rapidly evolving landscape, real estate professionals face the same pressing questions: “How do I become AI savvy?” and “Which AI tools should I adopt?” This curiosity is well-founded as AI represents the most significant business transformation in decades, offering agents the potential to reduce costs, increase productivity and minimize administrative errors.
Many real estate companies are already leveraging AI applications, including:
- Conversational chatbots to support employee HR needs
- Auto-generated listings and purchase agreement preparation
- Candidate sourcing to support recruitment
- Enhanced Automatic Valuation Models (AVMs) with effective accuracy and speed
- Predictive analytics revealing market trends before they emerge
- Client-facing chatbots providing 24/7 responsiveness
- Virtual staging tools transforming property views
With innovation accelerating daily, professionals understandably worry about falling behind. There’s a growing urgency to master AI fundamentals and integrate these powerful tools into daily workflows and broader business operations.
AI promises to revolutionize the real estate industry with remarkable efficiency and insights. However, like any transformative technology, it brings both opportunity and responsibility. As organizations embrace these advancements, establishing thoughtful governance and appropriate guardrails becomes essential at the organizational and individual agent levels to protect against financial risks, reputation damage, and potential legal complications.
Why Responsible AI Matters in Real Estate
AI tools process vast amounts of sensitive data – client financial profiles, personal details, property specifications, and market intelligence. They increasingly influence high-stakes decisions, from property pricing and mortgage eligibility assessments to marketing campaigns and client interactions. Without clear rules, oversight, and ethical guidelines, the potential for misuse or unintended consequences is enormous.
There are many regulations at the federal, state, and local levels that real estate organizations must consider when selecting and implementing AI products. These regulations are designed to ensure consumer protection, prevent discrimination, and safeguard data privacy. Here are some considerations when using AI responsibly:
- The Fair Housing Act: The FHA prohibits discrimination in housing-related activities—including property listings, lending, pricing, tenant screening, and marketing—based on protected classes such as race, gender, and national origin. Any AI system used in these areas must be designed and monitored to avoid both intentional and unintentional discriminatory outcomes.
- The Federal Trade Commission Act: The FTC also applies here in prohibiting unfair or deceptive practices. This includes the use of “black box or opaque” AI models, where the internal reasoning behind decisions is not easily explainable. If an AI system influences decisions affecting consumers—such as loan approvals or rental eligibility—its outputs must be transparent and accountable.
- Privacy laws: For example, the California Consumer Privacy Act (CCPA) grants California residents greater control over how their personal data is collected and used. AI systems that process personal data must comply with these requirements, including providing disclosures, honoring opt-out requests, and ensuring data minimization.
AI tools used in real estate must be continuously monitored for fairness, equity, and regulatory compliance. Organizations should adopt governance frameworks such as the NIST AI Risk Management Framework and others to assess bias, document decision-making processes, and ensure that security and human oversight is incorporated into AI tools.
The Risk for Real Estate Companies and Agents
Understanding the potential challenges of AI is your first step toward harnessing its power safely. While real estate companies are accountable for developing comprehensive safeguards, equipping agents with proper education creates an additional layer of protection. Here are some areas to prioritize:
- Data privacy: Real estate transactions involve some of life’s most sensitive information, from social security numbers to financial histories. AI systems can become prime targets for cyberattacks, especially when trained on large datasets that contain valuable sensitive datasets. Ensure your AI tools are secure and collect only the data necessary for the task.
- Algorithmic bias: Even the most sophisticated AI can inadvertently perpetuate existing patterns of bias. Imagine implementing an exciting new lead-scoring system that mysteriously deprioritizes specific neighborhoods, potentially violating Fair Housing standards while missing market opportunities.
- Accuracy and reliability issues: Over-reliance on flawed AI outputs can lead to poor business decisions. That lightning-fast AI writing assistant might sound impressive, but what happens when it pulls outdated school district information or incorrect zoning details? Suddenly, that time-saving tool becomes a liability, leading to misrepresentation. Remember, efficiency should never compromise accuracy.
- Lack of transparency or the “Black Box” problem: Many sophisticated AI models are incredibly complex, making it difficult for creators to understand precisely how they arrive at a specific output. When a client asks, “How did you arrive at this valuation?” or a regulator requires justification for a lending decision, vague references to complex algorithms won’t suffice. The inability to clearly explain AI-driven conclusions creates vulnerability in an industry that strives to be transparent and build client trust.
Ensuring AI compliance is a shared responsibility among developers, businesses, and users of the tech. For example, businesses that deploy AI are responsible for continuously monitoring the technology for compliance risks, performing impact assessments, and carefully reviewing vendor contracts to safeguard their legal and operational interests. When each party fulfills its role, the result is a more robust and trustworthy AI system that remains compliant not just at deployment, but over time.
Building Your AI Governance Framework: 9 Steps to Take
Implementing effective AI governance in the evolving AI landscape can be tricky. But there are several regulatory laws, guidelines and governance frameworks which need to be followed based on your geographic location, customers, how you collect data, decisions your AI tools make and more., Some of the AI frameworks include the NIST AI Risk Management Framework, the EU AI Act, the OECD AI Principles, the ISO/IEC AI Management System Standard, Microsoft’s Responsible AI Standard, and the World Economic Forum’s AI Governance Toolkit and more. There are specific laws, guidelines and frameworks that need to be followed, but below are some of the foundational steps for responsible AI governance.
- Chart your course with a governance committee: Every journey needs a compass! For larger organizations, assemble a diverse team from IT (e.g., data, security, AI) and core functional leaders (e.g., human resources, legal, finance and marketing) to understand risks and create a strategic plan. Be sure to include those who are already using AI tools. Smaller companies may leverage key internal leaders as well as external experts. This committee will become your organization’s AI steward, overseeing your technology portfolio, conducting ethical reviews, ensuring AI value, allocating resources to prevent potential pitfalls, and embracing excellence. Ensure you have someone on your team, whether internal or external, with a strong AI governance background who understands the laws and knows how to structure the governance appropriately.
- Define your organizational AI principles and policies: As the saying goes, if you don’t set the rules, someone else will! Take a proactive approach by clearly documenting your organization’s stance on AI tools from internal systems like AVMs to popular external resources like ChatGPT. Create thorough but straightforward guidance covering acceptable use and protecting ethical boundaries that drive fairness, accountability, data handling guidelines, human oversight checkpoints, and transparency expectations.
- Make data governance your foundation: AI is only as brilliant as the data it consumes. Implement robust data management practices that answer the essential questions: What information do we have? Where does it come from? Who can access it? Is it accurate, secure, and legally obtained? Are we collecting only the information we need? Give special attention to sensitive client information and ensure you have trustworthy hands managing this crucial asset.
- Have humans-in-the-loop reviews: While AI can impressively handle tasks independently, human judgment remains essential for high-stakes decisions and reputational information, such as market-facing materials, employment decisions, or finalizing pricing. Workflows require the appropriate human review for property valuations, AI-suggested contract clauses, complex client guidance, and any outputs with potential legal or fair housing implications.
- Assess and audit regularly: Before welcoming any new AI tool into your toolkit, examine it for potential bias, security vulnerabilities, accuracy limitations, and compliance risks. Build periodic reviews on your existing systems with acceptable parameters, as even the best model data can drift over time. Ask vendors tough questions about testing methodologies, transparency, and bias mitigation strategies.
- Champion transparency: Sophisticated AI systems often operate as “black boxes,” which means there is limited understanding of how conclusions were drawn from the inputs. So, request transparency from vendors about their AI reasoning process, what data it was trained on and where it comes from, and what safeguards are in place to protect against unexpected outcomes. Ask for documentation of this information and relevant insights into challenges they’ve encountered. Also, inform clients when using AI, whether they are engaging with a chatbot or their data is used in key decision-making and processing. Clients generally need to be informed about how their data is collected, used, and retained, and how they are impacted by AI. Informing clients with AI disclosures on listing descriptions or onboarding documents and using phrases like “AI-assisted valuation” or “chat support powered by AI” provides transparency, builds trust and is often legally required.
- Invest in agent and employee education and communication: Ensure everyone understands the basics of your AI tools, company policies, potential risks (especially regarding bias and privacy), and their role in responsible implementation. Remember that many employees feel uncertain about AI’s impact on their future—building trust through transparency and ongoing learning opportunities is key to enthusiastic adoption.
- Choose AI vendors wisely: That exciting property technology or “proptech” solution might promise revolutionary results, but have you examined their testing protocols for bias? Without proper due diligence, you might unknowingly adopt an AI tool with inherent biases, poor security practices, or non-compliant data handling. A sophisticated AVM that consistently undervalues homes in historically marginalized communities creates serious liability for everyone involved in its use.When selecting proptech vendors, look beyond flashy features and attractive pricing. Examine their AI governance practices, training data sources, security certifications, privacy policies, and contractual accountability and obligations should you experience AI failures. Understand your risk exposure should anything go awry.
- Stay regulation-ready: The compliance landscape is complex, from core data regulations like the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Fair Housing Act to AI-specific regulations that continue to evolve rapidly. Anticipating future regulations requires constant vigilance. Using AI tools that are not compliant could lead to hefty fines and lawsuits.Assign someone to monitor evolving AI regulations at the local, state and federal levels, particularly regarding data privacy and fair housing. Use this intelligence to keep your policies current and your team well-informed.
The good news? With thoughtful implementation, clear governance frameworks and ongoing education, these risks become manageable rather than insurmountable obstacles. The goal isn’t to avoid innovation—it’s to embrace it responsibly, ensuring AI enhances rather than undermines real estate organizations’ commitment to fairness, accuracy, and trust!
Navigate the AI Revolution with Trust and Confidence
Artificial intelligence isn’t just changing our industry—it’s reimagining what’s possible. These powerful tools offer a world where real estate professionals can work with remarkable efficiency, uncover deeper market insights, and create truly personalized client experiences that were once the stuff of science fiction.
Remember, robust governance isn’t just about playing defense and compliance—it’s about creating trust with your clients, communities, agents, employees and regulators. When they know you’re approaching AI purposefully and responsibly, you’re building something more valuable than keeping up with the AI Jones. You are creating a brighter and more efficient real estate future for everyone.
Author
Colleen Campbell is the Founder and AI Strategist for A-Human-I, an AI people, process and technology organization which streamlines the complex AI strategy, governance and workforce development journey for business and technology leaders.
