Top AI Risks Every Real Estate Professional Should Know

Welcome to the Property AI Tools Newsletter!

As artificial intelligence becomes a more central part of the real estate industry, it presents risks that could potentially blindside you. In today’s newsletter, I’m going to cover the most common risk factors so you can weigh up the potential exposure of your AI implementations and take the necessary precautions to avoid being stung.

Today I’ll be exploring:

• The top 4 risks AI to your operations

• Risk management strategies to help you navigate AI safely

• A simple risk management framework you can implement from today

Identifying the Risks of AI in Real Estate

AI raises questions about data handling, fairness, and accountability. All these areas need to be considered in order to protect your clients and your business. This section will break down the risks you need to watch for, so you can protect your business and make informed decisions.

Data Privacy Concerns

AI systems rely on gathering and processing huge amounts of data, much of which is sensitive. This includes financial details, personal identification, and even behavioural data collected from online interactions, studies and even social media. While these systems help streamline operations, they also pose serious risks to privacy. If this information is mishandled or exposed, it could break client trust and even lead to legal trouble.

Think about it: would your clients be comfortable knowing their personal details could potentially be accessed by the wrong hands? Ensuring your risk management strategy includes robust data protection measures isn’t just optional—it’s a must.

For more detailed insights, check out What are the Limitations of AI?: Technical, Ethical, and Social Challenges.

Bias in AI Algorithms

AI systems are only as good as the data they’re trained on, and that data can often contain hidden biases. If the training data reflects historical inequalities, the AI could unintentionally reinforce them. For example, a biased algorithm might undervalue properties in certain communities or favour specific demographics in contract approvals. I explore this in a bit more detail in a previous newsletter here: Can AI Bias Impact Real Estate Transactions? 

Hidden bias is more than a technical glitch, it’s an ethical issue that can impact your reputation. Unfair outcomes can not only lead to disputes but also damage the trust your clients place in you. Addressing bias in AI means regularly auditing algorithms and questioning the fairness of their processes.

Over-reliance on Technology

AI can process information faster than any human, but it’s not infallible. Relying too heavily on AI for important decisions, such as investment opportunities or property valuations, can lead to significant errors. Keep in mind, AI lacks the human ability to apply context, react to complex social cues or adapt to situations it cannot predict.

If you let it drive every decision, you may overlook critical human insight that could have prevented the poor outcome. A balanced approach to risk management means combining AI with human judgement and emotional intelligence.

Security Vulnerabilities

Every technology comes with security risks, and AI is no exception. Cybercriminals are always looking for weaknesses to exploit, and AI systems filled with high-value data are prime targets. From hacking attempts to ransomware attacks, failing to secure your systems could lead to catastrophic breaches.

This makes it essential to strengthen cybersecurity measures, invest in regular updates, and stay one step ahead of potential threats.

Liability and Accountability Issues

AI might make life easier, but it complicates responsibility. When something goes wrong, such as an incorrect property valuation or a incorrect rental agreement generated by an AI tool, who is liable? Is it the software provider (you), the developer, or the end user?

This grey area can lead to uncertainty, putting your business at risk. To stay protected, establish clear protocols for how AI is used in your operations and ensure any third-party tools come with strong accountability measures. Risk management here means preparing for the “what ifs” long before they become a problem.

Risk Management Strategies

Effectively managing the risks associated with AI in real estate requires a proactive, predictive and structured approach. By addressing issues pre-emptively as well as head-on, you can reduce potential harm to your operations, maintain trust with clients, and stay ahead of regulatory changes. Below are key strategies to ensure AI-driven tools are used responsibly and securely.

Implementing Data Protection Measures

Clients entrust you with sensitive information like financial records, identification details, and property history. If this data falls into the wrong hands, the consequences could range from identity theft to legal repercussions. That’s why implementing robust data protection measures is non-negotiable.

Start by ensuring compliance with data privacy laws like the GDPR, find the data protection law that applies to your country before proceeding. These regulations are in place to safeguard personal data and outline clear standards for its use and storage. Encrypt sensitive information, limit access to only essential personnel, and establish protocols for secure data sharing.

Regular Algorithm Audits

AI algorithms don’t operate in a silo. They’re built on data, and if that data carries biases, the results can unknowingly reflect those prejudices.

Regularly auditing your AI systems helps uncover and address biases early. This means reviewing the data used to train the algorithms and testing outputs for any red flags. Partner with tech experts when necessary to ensure a thorough examination. A review schedule keeps your tools fair, accurate, and aligned with ethical AI standards.

Continuous Training and Development

AI evolves, and so should you. To effectively manage risks, you need to understand the technologies you’re using. Comprehensive training ensures you’re not just relying on AI blindly, but using it wisely.

Provide regular upskilling sessions for your team, focusing on how these tools work and where they might fall short. You don’t have to become a data scientist, but being well-informed allows you to identify potential issues early. This is especially critical as new legislation around AI continues to emerge.

Plus, keeping your team up to speed builds confidence. The more they understand, the fewer mistakes they will make and the more efficient they will become.

Developing a Risk Management Framework

You need a clear, actionable plan, a ‘risk management framework’. This framework serves as your roadmap for identifying, assessing, and addressing AI-related risks in your operations.

To start, outline potential risks in a spreadsheet, include data breaches, biased predictions and system errors. Then, using a traffic light system determine how severe these risks are and what measures you will take to address them. For example:

Risk: Potential data breach.

Severity: Red

Action: Invest in top-tier cybersecurity software and conduct quarterly penetration tests.

Risk: Algorithmic bias.

Severity: Yellow

Action: Conduct third-party audits every six months and retrain algorithms with diverse datasets.

By documenting these processes, you create a living guide that ensures consistency and accountability. Share this plan with your team so everyone knows their role in mitigating risks.

Conclusion

By addressing the critical issues that come with implementing AI, you’re not only protecting your team but also safeguarding the trust your clients place in you. The stakes are high, but so are the rewards for those willing to take a thoughtful, proactive approach.

Will you proceed with a plan or wait you wait for something bad to happen?

Signing out!

Danielle 

P.S If you’ve made it this far, I’m starting a new slack community for real estate professionals to discuss, share and learn about AI and AI tools. If you’re a business owner, tech founder or professional and are interested in becoming one of the first members, simply respond ‘community’ to this email.