Multifamily AI
Reinforcement Learning from Human Feedback: Revolutionizing AI Training
Reinforcement Learning from Human Feedback (RLHF) is transforming AI development.
Traditional methods depend on predefined rules and algorithms.
RLHF uses human feedback to guide the learning process.
This allows AI systems to learn complex tasks more effectively.
For example, teaching an AI to navigate a new city by showing it the best routes.
Humans offer real-time feedback, shaping the AI’s decisions.
This method accelerates learning and improves accuracy.
RLHF is the bridge between human intuition and machine precision.
AI can now adapt to unpredictable environments and nuanced tasks.
The future of AI is here, learning from us to better serve us.
“AI learns best when it learns from us.” – Mike Brewer
AI’s Growing Influence: A Call to Action for Multifamily Business Leaders
The rise of artificial intelligence (AI) is no longer a distant prospect—it’s here, reshaping our multifamily industry in real time. As AI’s system becomes increasingly sophisticated, we’re witnessing an old but appropriate term: a paradigm shift in how work is conducted, decisions are made, and value is created. This shift presents incredible opportunities and poses interesting challenges across the industry, not just multifamily.
Recent studies have shown that employees increasingly turn to AI for guidance, often preferring these AI-driven solutions over traditional human management in certain areas. This trend signals a fundamental change in workplace dynamics and demands our immediate attention as business leaders.
The implications of this shift are startling, at least, and terrifying, at worst. On one hand, AI promises enhanced efficiency, data-driven insights, and the ability to tackle complex problems at scale. On the other hand, it raises questions about the changing role of human leadership, the need for new skill sets, and the ethical considerations surrounding AI deployment.
For years, we’ve discussed upskilling and reskilling at length in our video and written content. It’s almost too late at this point. If you have not already, the time is now to dive in full body and harness the power or be left out in the cold.
As multifamily leaders, we cannot afford to be passive observers. We must take proactive steps to harness the power of AI while ensuring that our organizations remain human-centric. Here’s what we need to do:
- Embrace AI as a Complementary Force (Agent or Co-Pilot)
First and foremost, we must shift our perspective. Rather than viewing AI as a threat to human roles, we should see it as a powerful tool that can augment human capabilities. AI excels at processing vast amounts of data, identifying patterns, and performing repetitive tasks precisely. By leveraging these strengths, we can free up our human workforce to focus on areas where they excel—creativity, emotional intelligence, and strategic thinking.
Action item: Conduct an audit of your organization’s processes to identify areas where AI can be effectively integrated to enhance efficiency and decision-making. If necessary, bring in outside help.
- Invest in AI Literacy
To effectively lead in an AI-driven world, business leaders must develop a strong understanding of AI technologies, their capabilities, and their limitations. This doesn’t mean becoming technical experts but gaining enough knowledge to ask good questions, make informed decisions about AI adoption, and communicate effectively with technical teams.
Action item: Develop an AI education program for your leadership team and key decision-makers. This could include workshops, seminars, and hands-on experiences with AI tools. Again, if necessary, bring in outside help.
- Cultivate Human Skills
As AI takes on more analytical and technical tasks, the value of uniquely human skills will increase. Emotional intelligence, creativity, critical thinking, and adaptability will become even more crucial. We must invest in developing these skills in our workforce to ensure they remain relevant and valuable in an AI-augmented workplace.
Action item: Review and update your training and development programs to emphasize human skills that complement AI capabilities.
- Reimagine Management and Leadership
The preference for AI guidance in certain areas challenges traditional management concepts. We must reimagine (don’t like the word, but it fits) leadership roles to focus on areas where human judgment and empathy are irreplaceable—shifting from direct task management to more strategic, mentoring, and facilitative roles.
Action item: Initiate a review of management structures and practices to identify areas where AI can support decision-making and where human leadership needs strengthening.
- Prioritize Ethical AI Development and Deployment
Ensuring ethical use is key as AI systems become more prevalent and influential. We must establish clear guidelines and governance structures to prevent bias, ensure transparency, and maintain accountability.
Action item: Develop an AI ethics framework for your organization, including guidelines for data use, algorithm transparency, and impact assessment.
- Foster a Culture of Innovation and Adaptation
To stay competitive, we must cultivate a culture that embraces change, encourages experimentation (celebrates failure as learning), and values continuous learning. This will enable our organizations to adapt quickly.
Action item: Establish innovation labs or cross-functional teams dedicated to exploring and piloting new AI applications in your business. Don’t go at this alone if you’re new to the AI party. Find a good guide to help. It will save you a ton of time.
- Address the Skills Gap
AI will create new roles and eliminate others. It is incumbent upon us to help our teams navigate this transition. This involves identifying future skill needs, providing retraining opportunities, and supporting employees in developing AI-adjacent skills.
Action item: Conduct a skills gap analysis and develop a comprehensive plan for workforce upskilling and reskilling.
- Collaborate and Share Best Practices
No single organization has all the answers when it comes to navigating the AI revolution. We must foster collaboration within and across the industry to share best practices and collectively shape the future of work in the multifamily space.
Action item: Join or establish industry consortiums focused on AI adoption and its impact on the workforce. NMHC and NAA are good places to start, but you must seek out and find businesses outside the industry from which to draw inspiration.
- Engage with Policymakers
The rapid advancement of AI raises important policy questions around data privacy, algorithmic accountability, and the future of work. As Multifamily leaders, we are responsible for engaging with policymakers to help shape regulations that foster innovation while protecting societal interests.
Action item: Actively participate in policy discussions and advocacy efforts related to AI governance and regulation. Again, NMHC is the place to start.
- Maintain a Human-Centric Approach
We must never lose sight of the human element in our businesses. Our customers, team members, clients, vendor partners, and investors are ultimately human, with needs and expectations beyond what AI can provide. Maintaining a balance between AI and human values is important.
Action item: Ensure that AI initiatives regarding team member satisfaction, customer experience, and organizational culture are always subject to review and change.
The influence of AI in the workplace calls for reimagining the very nature of work, leadership, and value creation. It’s the most important Call to Action (CTA) of our lifetime. As multifamily leaders, we have the opportunity—and the responsibility—to shape this transformation to benefit our organizations, team members, and society.
The time for action is now. We must be bold in our vision and strategic approach and undeterred in our commitment to ethical, human-centric AI adoption. By doing so, we can leverage the best of both human and artificial intelligence to drive the next iteration of business.
Let us embrace this challenge with enthusiasm and determination.
Next Frontier for AI: The Power of Chain-of-Thought Learning
AI is evolving. The new game-changer is Chain-of-Thought (CoT) learning. This technique allows AI to reason step-by-step, much like humans. Instead of jumping to conclusions, CoT guides AI through a logical sequence, improving decision-making and problem-solving.
Why is this revolutionary? CoT enhances AI’s ability to handle complex tasks. By thinking in steps, AI can offer more accurate and reliable solutions, making it a trusted partner in various fields, including multifamily.
What’s the future? As CoT integrates into AI systems, expect smarter, more intuitive technology.
“AI that thinks step-by-step is AI that truly understands.”
AI Impact on Multifamily Property Management
AI will revolutionize multifamily property management.
The landscape is shifting to predictive maintenance (PdM) systems that anticipate issues before they occur and provide instant resident support by AI agents.
Leasing processes are becoming seamless with virtual tours and automated applications, while energy management systems optimize utilities to cut costs and promote sustainability.
Even rent collection is becoming more efficient with AI monitoring and reminding residents, reducing late payments.
Visionaries are are already embracing this change, and soon, the rest of the industry will follow suit.
Leadership’s Scary Evolution: From Digital Assistant to Commander
Photo by Steve Johnson on Unsplash
I think we’ve always thrived on human-centric leadership in multifamily. It’s the backbone of our systems, processes, strategies, and marketing campaigns. However, we’re entering an era where artificial intelligence (AI) is poised to transform our understanding of leadership roles, particularly in complex fields in multifamily.
In the early innings, AI serves as a copilot or digital assistant, handling data analytics, automating repetitive tasks, and streamlining workflow. But as machine learning algorithms grow smarter and more capable, it’s worth asking: What happens when AI takes the steering wheel?
Consider this: We already use advanced AI platforms to identify and predict market trends. Machine learning models analyze data from multiple sources—rental rates, occupancy levels, local regulations—and provide actionable insights beyond human intuition or traditional market analysis methods. The deeper the data, the better the predictive power of the AI. AI is not new – think about the calculator. The wave is cresting, and it’s making landfall.
But here’s where it gets interesting—what if we let AI manage all the variables that influence rent pricing? High-level, dynamic pricing models governed by machine learning could consider hundreds of factors, from local events and governmental actions to seasonal patterns, essentially making every pricing decision optimized and justified.
In customer relations and community engagement, AI chatbots are no longer limited to answering frequently asked questions. Natural language processing allows them to interpret intent, mood, and context, enabling them to handle complex interactions. These aren’t your run-of-the-mill chatbots; these systems can interpret emotions, de-escalate situations, and offer tailored solutions, essentially serving as virtual community managers. And companies can bolt together the technology in-house. You don’t need to rely on third parties for the platform. Think chatbot platforms.
Now, let’s discuss decision-making. AI can also be involved in shaping strategies. Picture an AI system that analyzes human behavior in communal spaces to optimize the use and maintenance of these areas. Instead of simple analytics, the AI could proactively suggest changes in communal space designs or services offered, directly affecting the quality of life for the community. Essentially, the AI becomes a proactive strategist rather than a reactive analyst.
It’s tempting to resist these changes, viewing AI as a potential threat to the essence of human-centric leadership. However, in the correct architecture, AI enhances our capabilities. It doesn’t replace human decision-making but refines it. The result is a hybrid leadership model where humans and AI work harmoniously, amplifying the other’s strengths. This is not a zero-sum game; it’s an evolutionary step in multifamily leadership.
Of course, safety and ethics are non-negotiable. As AI systems get more powerful, it’s crucial to have robust ethical frameworks, but that’s a topic for another discussion.
In a continuously evolving time, the multifamily industry has to adapt or risk becoming obsolete. It has been said, “If you don’t like change, you will like irrelevance even less.” Embracing AI in leadership roles is not an option; it’s a necessity. It promises to elevate our strategies, systems, and services to the minimum desired levels, redefining what leadership can achieve in the multifamily space.
