AI Driven
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.
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Adaptive AI
Photo by DeepMind on Unsplash
The advent of adaptive AI is set to revolutionize the way we approach multifamily property management. With the ability to adapt and improve performance over time, these systems can help property managers to streamline processes, increase efficiency, and make more informed decisions.
One of the key areas where adaptive AI can have a significant impact is the area of tenant screening. Traditional tenant screening methods can be time-consuming and involve manual work, such as checking references and credit reports. Adaptive AI systems, on the other hand, can use machine learning algorithms to analyze data from various sources, such as social media profiles and online behavior, to create a more comprehensive profile of a potential resident – a renter’s resume. This can help property managers make more informed decisions while considering fair housing laws about who to rent to and can also help reduce the risk of rent defaults.
Another area where adaptive AI can have a big impact is in the area of maintenance and repairs. Traditional property management systems often rely on manual processes, such as phone calls and emails, to schedule and track maintenance and repairs. Adaptive AI systems, however, can use machine learning algorithms informed by IoT sensors to predict when equipment is likely to fail and can automatically schedule maintenance and repairs based on this prediction. This can help to reduce downtime and save money on repairs in the long run.
Using adaptive AI in multifamily can significantly improve property management systems and labor efficiency and effectiveness. With the ability to adapt and improve over time, these systems can help property managers to make more informed decisions, reduce costs, and provide a better experience for team members and residents.
However, it’s also important to note that with the increasing use of adaptive AI, there is a need to be thoughtful and mindful and have proper data privacy and security measures in place to protect the data of prospects, residents, and property managers.