In early 2023, ChatGPT made its mainstream appearance. It wasn’t long before others arrived, including Bing Chat, YouChat and Google Bard. Large language models (LLMs) are trained on large sets of data, and they use statistical models to analyze and learn patterns and connections between phrases and words.
But are they a panacea? No. They can’t determine accuracy and may invent facts or sources that aren’t true or don’t exist.
Does that mean LLMs and generative artificial intelligence (AI) don’t have their uses? Not at all! Many industries and specific roles within sectors find these AI-driven tools quite valuable. And there’s no need to worry that they’ll eliminate the need for human workers, either — though as they grow and become more complex, their capabilities will keep evolving and improving.
People continue to find innovative ways to use these AI tools to streamline processes and so much more. In fact, generative AI offers many benefits for commercial real estate professionals, empowering them with advanced analytics, automation, strategic insights, and visualization.
By embracing this technology, CRE professionals can enhance their decision-making processes, improve operational efficiency, and gain a competitive edge in the market.
Behind the Curtain
These language models generate human-like text based on the input they receive. They can produce coherent, contextually-relevant responses, making them useful for diverse applications like chatbots, content generation, language translation, and more.
LLMs can understand and interpret human language — to an extent. The AI will miss nuances humans are wired to catch, but these models can extract information and identify entities, intents, relationships, and sentiments.
If you’ve got a lengthy document or article to read, you can ask an LLM to summarize it and extract essential information and main points. This AI can answer questions based on context and analyze sentiment — which is helpful for social media monitoring, customer feedback analysis, and brand reputation management.
Most people use generative AI and LLMs interchangeably. They’re closely related but have a few differences.
- Generative AI encompasses a broader scope of generating different content — images, music, text — whereas LLMs (like GPT-3) primarily focus on text-based output.
- LLMs are designed to perform many language-related tasks — translation, summarization, and question answering — and have a generalized language understanding and generation capabilities. Generative AI models can specialize in specific tasks — music composition, image generation, and text-to-speech synthesis.
- LLMs excel in understanding and generating speech in specific contexts. Generative AI models can learn context from training data but lack the same contextual understanding as LLMs.
- The creative fields are exploring uses for generative AI models. Many industries are exploring how to use LLMs for natural language processing (NLP) and understanding tasks — like chatbots, content generation, and language translation.
Most experts consider LLMs a subset of generative AI because they can create text-based output. And with that ability to develop and simulate new content, they offer several practical applications for the CRE industry.
Design and visualization
AI can assist CRE professionals in designing and visualizing architectural plans and interior layouts. After people input specific parameters and constraints, the AI produces multiple design options, providing creative and innovative solutions — and saving time and resources compared to traditional manual design processes.
Space Utilization Optimization
CRE professionals can leverage generative AI to optimize space utilization within properties. AI can analyze data such as floor plans, traffic patterns, and user preferences to recommend optimal layouts, helping to maximize occupancy and functionality. This function enables professionals to make data-driven decisions about space allocation and improve operational efficiency.
Tenant Profiling and Segmentation
AI can analyze large datasets to create detailed tenant profiles and segments. By considering demographics, preferences, and behavior patterns, AI creates insights helping CRE professionals understand their target audience better. This knowledge facilitates effective marketing strategies, leasing decisions, and tenant retention efforts.
Predictive Analytics
AI algorithms can process historical and real-time data to accurately predict market trends, demand, and pricing in commercial real estate. Professionals can leverage these insights to identify emerging opportunities, anticipate market fluctuations, and optimize investment strategies. This application informs decision-making capabilities and reduces property valuation and investment risks.
Property Valuation and Investment Analysis
AI analyzes location, property attributes, market data, and comparable sales to create comprehensive and accurate valuation models. A streamlined property valuation and investment analysis enable professionals to make informed investment decisions and negotiate deals based on reliable data-driven insights.
Risk Assessment and Mitigation
AI can help CRE professionals assess and mitigate property development and management risks by analyzing various risk factors, such as market volatility, regulatory changes, and environmental considerations.
Energy Efficiency and Sustainability
AI contributes to CRE’s sustainable practices and helps building owners and operators optimize energy usage, meet sustainability goals and ESG initiatives, and comply with evolving regulations. It can analyze energy consumption patterns, building performance data, and environmental factors and offers recommendations for improving energy efficiency and reducing carbon footprints.
Enhanced Customer Experience
Generative AI can enhance the customer experience within CRE properties by enabling brokers to offer virtual tours, interactive floor plans, and realistic 3D visualizations so prospective tenants or buyers can make informed decisions — even if they’ve only viewed a property remotely. This approach improves engagement, streamlines the leasing or sales process, and fosters positive customer relationships.
Workflow Automation
The CRE world is full of repetitive, time-consuming tasks which AI can automate. For example, it can assist in generating reports, analyzing market data, managing lease agreements, or handling maintenance requests. Automating these duties frees professionals to focus on higher-value activities, increase productivity, and deliver superior service to clients.
Competitive Advantage
Embracing generative AI generates a competitive advantage and positions CRE professionals as industry leaders. When they leverage this technology’s capabilities, CRE professionals differentiate themselves by offering innovative services, better property insights, and more efficient operations — and attract clients, investors, and tenants who value advanced technology and data-driven decision-making.
A final caveat: Generative AI is an incredibly valuable tool that enhances efficiency and helps all professionals involved in commercial real estate make informed decisions and provide more engaging client experiences. However, it should always be used in conjunction with human expertise and careful consideration of ethical and legal implications.
Are you a commercial real estate investor or looking for a specific property to meet your company’s needs? We invite you to talk to the professionals at CREA United: an organization of CRE professionals from 92 firms representing all disciplines within the CRE industry, from brokers to subcontractors, financial services to security systems, interior designers to architects, movers to IT, and more.
