Artificial Intelligence (AI), or the general ability of computers to emulate human thought and learning processes and, ultimately, to perform tasks in real-world environments, has grown and evolved significantly in recent years. It’s an empirical fact: in 2022, the global AI market swelled to $136.55 billion, with projections hinting at a surge of $1.8 trillion to $2.6 trillion within the next 10 years.
The banking, financial services, and insurance (BFSI) sector has also embraced AI. Anticipated to hold a significant 33.9 percent market share by 2030, this sector is primed for growth in the coming years. AI’s increasing presence in banking spans various functions, whether account inquiries and loan applications or more advanced roles such as fraud detection and credit score monitoring.
Amid this surge of AI technology adoption, a useful array of tools has emerged, ones becoming ever more advanced and even more accessible. Such tools include natural language processing (NLP); deep learning; machine learning; neural networks; and, notably, generative AI.
Generative AI is distinct from other AI tools and is primarily used for content creation, be it imagery, text, computer code, video, or other forms of output. Although the terms AI and machine learning are often used interchangeably, it’s important to note that machine learning is actually a subset of AI, one that describes the technologies and algorithms that enable systems to identify patterns, make decisions, and improve through experience and data.
Firms active in real estate capital markets are already employing generative AI to enhance operations at all levels of the transaction process—a foregone conclusion as generative models, such as GPT, LlaMA, and BERT, are constantly improving and being incorporated into user-friendly, no-code platforms. Chat-based tools such as ChatGPT have revolutionized content creation by streamlining tasks, including producing copy for marketing campaigns and drafting emails; such image-generation AI tools as Midjourney enable lightning-fast and cost-effective rendering of visuals.
Explore the below interactive graphic to learn more about how generative AI is changing real estate capital markets.
With financial and real estate technology providers increasingly integrating AI components into their platforms, users benefit from more holistic and relevant analytics, and can more easily troubleshoot issues, import and export information, and even execute customized workflows, if necessary, among many other benefits.
Some of the real estate industry’s major players are launching their own AI-powered tools for lead generation. JLL, for example, through a collaboration with multinational technology firm Nvidia, has been integrating generative AI into a product offering to optimize internal workflows and client processes, in quest of enhancing transactions and decision-making. JLL’s tool crunches large volumes of carefully cleaned public and proprietary data to offer assistance with transaction management and lead generation, based on portfolio characteristics, to clients who opt in to the service.
Yao Morin, JLL chief technology officer, explains: “Similar to how you use a software application on your phone, you use algorithms to generate leads and surface leads and insights in the user interface.” The tool’s rapid uptake and impact to date is thought provoking: “One in five transactions in capital markets was [affected],” says Emilio Portes, global head of capital markets innovation and capital markets quants at JLL.
Portes and Morin emphasize the importance of transparency, of doing the homework that cleaning input data for models entails, and of staunch adherence to ethical standards—particularly around data privacy and security in using AI for lead generation and enhanced transactions.
