How AI Is Changing CRE Analyst Roles and Reshaping the Talent Pipeline

How AI Is Changing Commercial Real Estate Analyst Roles and Hiring

Artificial intelligence is reshaping the role of analysts in commercial real estate (CRE). Firms are investing heavily in AI tools to boost efficiency, expecting analysts to produce more with advanced technology. This shift brings both opportunity and anxiety about the future of entry-level talent and workforce development.

Pressure to Adopt AI and Increase Output

Executives worry about losing competitive advantage if they don’t fully leverage AI. Meanwhile, analysts see peers using AI to amplify their productivity, creating pressure to keep up. This dynamic is raising expectations for faster, higher-quality output from analysts across the industry.

Instead of reducing headcount, companies are raising the bar on technical and analytical skills for new hires. Entry-level analysts now need stronger data capabilities to make the most of AI tools that assist with data gathering and analysis.

Major Firms Leading AI Integration

• JLL launched its own large-language model in 2023 and has multiple AI products ready for deployment.
• CBRE developed proprietary AI systems like Ellis, which streamlines access to research insights and frees analysts to focus on higher-value work.

These investments reflect a widespread commitment to AI. Around 63% of CRE firms plan to increase their AI budgets by 5% to 25% over the next two years, with some boosting it by more than 25%, according to recent surveys.

AI Tools Are Transforming Analyst Workflows

Analysts typically spend 40% or more of their time on data collection, cleaning, and entry. AI promises to relieve that burden, allowing analysts to focus on interpreting data and crafting meaningful insights.

For example, AI-powered tools like Diald AI and Henry enable faster generation of investment memos and deal decks. Henry’s software can produce underwriting and market analysis documents in hours instead of days, cutting down revision time significantly.

This efficiency lets brokers handle more deals simultaneously, reducing the need to expand analyst teams. AI adoption is thus enabling firms to grow without hiring new analysts at the same rate.

Implications for Entry-Level Hiring and Training

While AI enhances productivity, it raises concerns about the development of early-career talent. Firms increasingly seek candidates who can hit the ground running with strong technical skills, rather than investing heavily in training.

This shift puts pressure on educational institutions to fill the gap. Real estate programs are debating how to incorporate AI training while maintaining critical thinking skills, ensuring students can evaluate AI-generated information effectively.

As AI reshapes the CRE analyst role, balancing technological proficiency with foundational skills will be key to building a resilient talent pipeline.

Key Takeaways for CRE Professionals

• AI is becoming essential for analyst productivity; proficiency with AI tools is now a hiring priority.
• Analyst roles are evolving from data gathering to generating insights and strategic storytelling.
• Entry-level hiring demands stronger technical skills, with less tolerance for steep learning curves.
• Educational institutions and training programs must adapt to prepare talent for a tech-driven CRE environment.

For those looking to strengthen AI skills relevant to real estate and construction roles, exploring specialized courses can be a practical step. Resources like Complete AI Training’s job-specific courses offer targeted learning paths to stay competitive.