While AI has long been used for forecasting and customer segmentation, generative AI can transform such basic predictive models. However, many real estate organisations face challenges in effectively implementing and scaling this technology. Success involves many factors and requires overcoming significant obstacles.

Generative AI tools, such as chatbots enhance customer engagement by assisting with inquiries and decision-making. Such tools can create personalised 3D simulations of apartments and commercial space with selected furniture and designs, helping potential buyers or tenants better visualise the spaces. This not only increases customer satisfaction but also helps identify popular design choices, boosting sales and informing future investment and design decisions based on the data collected.

In content creation, generative AI can produce text and images and help develop detailed architectural designs by merging data from various sources. This integration allows architects to create optimised plans that blend functionality with creativity, leading to more appealing and efficient spaces.

For investors, generative AI simplifies decision-making by analysing large and diverse data sets to identify promising opportunities, such as prime data centre properties or thriving commercial spaces. It also streamlines legal document review by summarising key details and organising data into tables, making it easier to take informed decisions. Generative AI aids in interpreting and generating software, thereby streamlining and enhancing real estate processes.

To fully leverage generative AI, real estate companies should adopt up to date strategies. They should develop tech-focused roadmaps that prioritise technology integration and adapt processes to implement new technologies. Executives should assess their roles in the real estate value chain and rethink the experiences of tenants, employees and other stakeholders. This involves redesigning roles and structures to align with AI, challenging traditional hierarchies and adopting new work methods that empower all levels of the organisation. Entities should develop and refine query frameworks for generative AI to ensure they provide actionable insights specific to real estate.

By using proprietary data, companies are able to focus on organising and integrating this information to enhance its value and utility. Management should design and create tools that deliver actionable insights and align with brand and regulatory requirements. Leaders should invest in robust technology with feedback mechanisms to support generative AI and mitigate risk. As portfolios expand, entities must adapt operational models to handle more complex tasks with the support of AI.

While generative AI offers transformative potential, it also carries risks such as biases in training data, legal issues from using unlicensed intellectual property and the need to adjust quickly to changes in AI-generated results. Effective risk management is crucial when integrating AI into business functions.

Despite these challenges, generative AI offers an unprecedented opportunity to innovate in the real estate sector. The industry’s measured adoption of technology may have worked in its favour by having avoided now-outdated practices. Despite having a steep learning curve, generative AI and its insights can bring real business success.

Executives should integrate practical applications offering immediate value and generating interest as they evaluate applications promising long-term transformation. Embracing this digital shift will enable real estate companies to profit fully from generative AI’s potential and flourish in an evolving market.

This article was originally published in India Business Law Journal on 11 September 2024 Written by: Ashoo Gupta, Partner. Click here for original article

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