AI @ CBRE Group
Summary
- CBRE has demonstrated a clear increasing adoption and strategic integration of AI technologies from late 2023 through 2025, spearheaded by key figures like Sandeep Davé and leveraging proprietary platforms such as Capital AI and Ellis AI. These efforts focus on operational efficiency, predictive analytics, lease processing optimization, and enhancing real estate investment strategies.
- Financially, CBRE’s AI initiatives have contributed to tangible outcomes such as a 25% reduction in manual lease processing times, multi-billion dollar annual savings in real estate management through AI-enhanced data collection, and fostering robust AI-driven demand in real estate sectors like data centers, particularly in Asia Pacific.
- CBRE’s AI application maturity spans traditional predictive analytics to generative AI-powered digital assistants, while also pushing agentic AI use cases in autonomous decision-making for facilities management and investment insights. The company maintains a strong internal and external engagement strategy, including employee AI playgrounds and global hackathons to drive innovation.
VIBE METER
5 AI Use Cases at CBRE Group
Predictive Maintenance2025
Talent Analytics2025
Digital Assistance2025
Investment Analysis2024
Lease Processing2023
Timeline
2025 Q4: no updates
2025 Q3
CBRE reported increased demand for AI-specialized tech talent amidst a slower overall tech labor market. Capital AI platform was highlighted for setting new standards in real estate investment intelligence and facilities management, using machine learning on IoT sensor data to predict equipment failures and reduce downtime.
2025 Q2
AI’s boom drove strong demand for data centers, especially colocation and hyperscale types in the Asia Pacific region. CBRE hosted employee hackathons fostering innovation using AI to solve real business challenges. The company also focused on effective implementation of AI and technology in corporate real estate teams to further drive office space demand.
2025 Q1
CBRE partnered with Nvidia to offer AI advisory services focused on expanding clients' AI operations utilizing Nvidia chips. The Ellis AI platform was introduced as a generative AI-powered digital assistant, enhancing productivity and commercial real estate service delivery. CBRE emphasized embedding AI into scalable real-world solutions.
2024 Q4
CBRE expanded AI applications into specialized sectors such as life sciences real estate, helping biotech companies anticipate and respond proactively to market changes. CBRE Investment Management leveraged AI-enhanced data collection to analyze global real estate secondaries, generating annual excess value of up to $23 billion.
2024 Q3
CBRE launched Capital AI, a proprietary AI tool analyzing billions of data points to revolutionize real estate investment strategies. The company integrated AI to enhance operational efficiency and better inform decisions. CBRE also explored AI’s potential to predict societal and economic changes affecting real estate.
- CBRE UK: CBRE's AI journey: Shaping the future of real estate
- CREtech: CBRE Launches Capital AI to Revolutionize Real Estate Investment Strategies
- PitchGrade: CBRE Group: AI Use Cases 2024
- CBRE: CBRE Unveils Capital AI: Unlocking the Power of Real Estate Investment Property Data
- CoStar: Can AI predict societal change? CBRE thinks so
2024 Q2
CBRE publicly discussed the impact of AI on the future workplace, emphasizing net-positive employment effects. AI was applied for market movement predictions, asset failure forecasting, and enhanced building management to reduce costs and increase operational efficiency.
2024 Q1
CBRE continued to solidify its AI leadership position in the real estate industry, noted in comparison to rivals like Cushman & Wakefield who favored partnership models rather than building AI tech internally.
2023 Q4
CBRE launched an internal AI playground platform for employees enabling low-risk access to large language models and generative AI tools. Under leadership including Sandeep Davé, the firm successfully reduced manual lease processing time by 25% using machine learning and AI, while also advancing ESG and operational efficiencies through data and cloud technology adoption.