The release of OpenAI’s new o1pro GPT model puts a spotlight on a critical question for rental housing professionals:

How do we evaluate the value of a tool in relation to the work we’re trying to accomplish?

With generative AI (GenAI) models now spanning a wide price range—$20/month for entry-level GPTs versus $200/month for the o1pro—this isn’t just a cost question. It’s about aligning the tool’s capabilities with the value of the work being done.

For rental housing organizations, the concept of 10X—achieving exponential value from strategic investments—is more relevant than ever. But to achieve that value, we need to get serious about using the right tool for the right job and defining the boundaries between human and AI contributions.

Understanding the Value Equation

Generative AI is already reshaping how we work. Entry-level GPTs can churn out polished emails, draft policies, or generate meeting agendas in seconds. But not all tasks are created equal. Complex, high-stakes work - like analyzing market trends for asset acquisition or drafting compliance reports for investors - may require more advanced models which promise greater capabilities, precision, and analysis.

Here’s the equation we should consider:

Value of the Task >>> Cost of the Tool

In other words, if an AI tool can perform high-value work that would otherwise take hours of highly-skilled labor, the investment in a more advanced model makes sense. On the flip side, paying for a high-powered AI to generate simple correspondence or routine forms may not deliver 10X value.

Monetizing Tasks: A Shift in Thinking

To make informed decisions, housing professionals must evaluate their workflows and ask:

1. What is the monetary value of this task or output?
   Example: A analysis to secure funding for a $25M development carries far greater weight than a monthly investor newsletter.
   
   

2. Can this task be done better - or faster - with AI without sacrificing quality?
   Example: Drafting a multi-year portfolio optimization strategy may benefit from a model trained on advanced analytics, while day-to-day tenant communications might not.
   
   

3. Does this task require human nuance or judgment?
   Example: AI can analyze deal terms for an acquisition, but a human may still need (or want)to negotiate and account for additional contextual factors outside the scope of the AI.

These questions push us to think about how we allocate resources, especially as we evaluate where human expertise adds irreplaceable value versus where GenAI can deliver outputs more efficiently.

The Right Tool for the Right Job

Let’s break down some examples of how different levels of AI align with rental housing work:

• Entry-Level Generic GPTs ($20/month): Ideal for straightforward tasks like drafting resident notices, automating standard emails, summarizing dense written information, or creating marketing copy
  
  

• Advanced GPT Models ($200/month): Better suited for high-value work, such as forecasting portfolio performance using predictive analytics, writing complex funding proposals tailored to regulatory requirements, or summarizing technical data for board presentations

  
  

• Custom LLM Models ($2,000+/month): Suited for industries & organizations with high proprietary, privileged, or confidential data with clean big data stores for deep levels of analysis.

These distinctions matter. Trying to save on AI costs by using a basic model for advanced tasks is like hiring a rookie for a senior-level role—inefficient and ultimately costly.

The 10X Mindset: AI as a Strategic Partner

Rental housing organizations have limited resources, making 10X thinking essential. This means investing where the return is transformational. Advanced AI models aren’t just about doing tasks faster; they’re about unlocking capabilities that were previously out of reach—generating insights, identifying opportunities, and driving innovation.

Here’s how to apply the 10X mindset when evaluating AI tools:

• Identify Bottlenecks: What tasks slow your team down? Can AI take them over entirely or augment the process?
  
  

• Measure Impact: What’s the potential ROI of completing a task faster, with higher accuracy, or at a lower labor cost?
  
  

• Leverage Advanced Capabilities: Use higher-level AI for transformative projects, like analyzing compliance risk or creating data-driven property development strategies.

Balancing Human and AI Contributions

As AI tools become more powerful, rental housing leaders will increasingly face decisions about what’s best left to humans and what can be handed off to AI. The goal isn’t to replace human expertise—it’s to amplify it.

For example:

• Use AI for analysis and automation, but rely on humans for strategic decisions and relationship management.
  
  

• Let AI summarize compliance data, but have humans validate and interpret results to align with organizational values.
  
  

• Allow AI to generate forecasts, while leaving the final call on investments to experienced professionals who can account for market nuance.

This balance ensures organizations stay efficient without sacrificing the human touch that affordable housing requires. BUT - it's important to educate your teams about opportunities for AI partnership and ensure your organization is ready to implement AI tools.

Final Thoughts: It’s About Strategic Alignment

The release of advanced models like o1pro highlights a critical opportunity: to align tools with the value of the work being done. For rental housing professionals, this means choosing AI strategically—not based on price, but on the ability to achieve meaningful, transformational results.

By focusing on the right tool for the right job and adopting a 10X mindset, organizations can position themselves not just to keep up, but to lead in the AI-driven future of affordable housing.

Ready to take the next step? Start evaluating your workflows and discover where the real value lies. It’s time to put AI to work, strategically and effectively.