Strengthen data privacy so AI can catalyze success in real estate

Commercial real estate leaders need to evaluate privacy risks as they seek to realize the benefits of generative artificial intelligence. With privacy by design as the guiding principle, organizations across the industry can tap into the wealth of possibilities gen AI presents while avoiding unforeseen and costly risks.

What opportunities does gen AI hold for Canada’s real estate industry?

By identifying issues and surfacing data insights quickly, gen AI creates opportunities for organizations to speed up operations and drive proactive decision-making. Stakeholders tend to focus on the ways gen AI can improve property operations. In fact, property managers are already implementing AI to better manage areas like energy. With gen AI, these organizations could take that further, optimizing energy in much more dynamic ways.

Similar benefits exist for security and access control. What’s more, gen AI can also make processes like maintenance requests, account information and rent collection even more efficient, as tenant chatbots become pervasive. Reporting can become more robust. Marketing and leasing processes can be significantly enhanced. Generations of marketing materials, tenant acquisition, leasing and creation of presentations and reports will be impacted by gen AI tools.

That said, Gen AI’s potential isn’t limited to these more known operational areas. Potential use cases abound right across the real estate value chain. What does that look like?

That said, without a mature data management framework, gen AI could also introduce greater risk of costly data leaks or breaches.

The time to balance opportunities and risks with a security by design foundation is here and now.

What data privacy considerations should commercial real estate companies keep in mind?

In the near term, poor data management and governance practices can lead to everything from high exposure during gen AI integration to low-quality outcomes when decisions are made using gen AI tools. If data is used for illegitimate purposes or reasons to which individuals haven’t consented, the business may face compliance channels, reputational damage and other negative consequences.

These risks are compounded by the fact that failing to get a privacy by design framework in place early on also holds real estate organizations back from capitalizing on emerging gen AI use cases down the road. For instance, as gen AI surfaces even greater insights over time, real estate companies can draw on data intelligence to refine smart building techniques, yield better market forecasts and proactively reinforce sustainability and climate resilience. None of this is possible if the building blocks for safe, secure and protected data use aren’t in place well in advance.

How can real estate companies manage risk through responsible gen AI?

At EY, we’ve built a Responsible AI Framework that is grounded in purposeful design, agile governance and vigilant supervision for the AI development and use lifecycle. The Framework comprises nine principles:

• Accountability
• Explainability
• Reliability
• Fairness
• Transparency
• Security
• Compliance
• Sustainability
• Data protection

In the real estate context, adopting gen AI responsibly requires a firm understanding of the types of data collected and why it is sensitive. Commercial properties are now enabled with smart technologies that allow the building itself to gather data or personal information. This could span everything from visitor logs to surveillance videos, or even health and accessibility data indirectly corrected, covering race, ethnicity, gender.

Meanwhile, when folks buy a residential property, the process requires them to provide a remarkably vast amount of personal information. Protecting data privacy requires real estate organizations that collect this information to understand exactly what they have access to, and implement effective guardrails accordingly.

Armed with an understanding of the data set itself and potential sensitivities, organizations will be better positioned to start exploring privacy regulations, data requirements and broader public safety concerns that may come into play and prepare to strengthen security measures and governance frameworks. Only then can real estate organizations incorporate gen AI responsibly.

To achieve this, we recommend embracing a deliberate and structured approach to embed privacy by design from the get go:

1.      Carry out a fulsome data audit. This is how you get a firm grasp of what data you have, where it resides and why it’s sensitive.

2.      Cleanse and structure your data. Ensuring data is accurate, consistent and in formats useable for gen AI plays a direct part in how effectively you can use gen AI overall.

3.      Establish a clear data governance structure. Once ready to adopt gen AI, teams and individuals across the business must understand the role they play in managing data throughout its lifecycle and adhere to policies that help govern the data effectively.

4.      Carry out regular compliance checks. None of this is a one-and-done process. Organizations must continuously confirm that processes and policies around gen AI meet applicable privacy laws and regulations.

5.      Incorporate privacy by design in program and product development. By making sure this is reflected at every stage of innovation and adoption, you nurture and grow a culture of privacy in the company. This can have a lasting and sustainable impact over time, setting you up to adopt additional emerging technologies as they arise because the organization itself will already be well positioned to do so from a security and governance perspective.