It is no surprise, Artificial Intelligence has been a huge topic of attention in the multifamily sector. AI has swept its way through many forms and fashions, providing unique ways to increase income, reduce expenses and enhance the resident experience. The AI experience in Multifamily is not a new form of technology to help the business, it has been around for many years and continues to provide benefits in numerous ways to all industries.
Although AI is making mass headlines, it is extremely important to keep human experience within its launches. It is vital to ensure ethical, unbiased, user-friendly, and context-aware AI systems that align with human values and contribute positively to society’s well-being is being launched. Computers cannot and should not replace the value and importance of technical empathy and human interaction.
Within this blog, I will share the importance of why we should keep a heavy balance of human experience within our businesses, especially Multifamily. I will also share how we can use AI to help reduce overhead in our operations and provide elevated experiences for our investors and residents.
Keeping human experience within AI is crucial for several reasons:
- Ethical considerations: AI systems are becoming increasingly integrated into various aspects of our lives, from decision-making processes to autonomous vehicles. By infusing AI with human experience, we ensure that these systems align with our ethical and moral values. This prevents AI from making decisions that could harm individuals or society as a whole.
- Bias mitigation: AI algorithms learn from data, and if the training data contains biases, the AI system can perpetuate and even amplify those biases. By incorporating human experience, we can provide more nuanced and context-aware decision-making that helps counteract harmful biases.
- User-centric design: AI systems are ultimately designed to interact with humans. By incorporating human experience, we can create more user-friendly and intuitive AI interfaces that understand human needs, preferences, and emotions, leading to better user experiences.
- Interpretability and transparency: The “black-box” nature of some AI models can make it challenging to understand how they arrive at specific conclusions. By incorporating human experience, we can improve interpretability, making AI systems more transparent and understandable to users and developers.
- Contextual understanding: Human experience includes an understanding of context, culture, and social dynamics. By integrating these elements into AI systems, we can improve their ability to comprehend and respond appropriately to diverse situations.
- Safety and control: By incorporating human experience into AI, we can design systems that prioritize safety and control. This is especially important in critical applications like healthcare, finance, and autonomous systems, where errors could have severe consequences.
- Creativity and innovation: Human experience encompasses creativity, imagination, and innovation. By infusing AI with these qualities, we can unlock the potential for AI to assist in problem-solving, artistic endeavors, and scientific discoveries.
- Adaptability and learning: Human experience includes the ability to adapt, learn from mistakes, and improve over time. By incorporating these aspects, AI systems can become more flexible, resilient, and efficient in their tasks.
- Empathy and emotional intelligence: Human experience involves emotions, empathy, and understanding. By integrating these elements into AI, we can create systems that can respond more compassionately to human needs and emotions, particularly in applications like healthcare, mental health support, and customer service. It is important to refrain from removing human experience and oversight, as it will diminish trust and negate the sense of community and retention.
AI’s potential to streamline operations, enhance resident experiences, and increase efficiency will likely continue to have a significant impact on the multifamily real estate sector. Keeping human experience within AI is vital to society’s well-being. There are many ways we can utilize AI to source adequate deals, identify tertiary markets and CRM management. However, I will now explain some ways we can integrate AI into our asset acquisitions, post close.
- Smart Home Technology: AI-driven smart home devices have become more prevalent in multifamily properties. These devices can optimize energy usage, enhance security, and improve overall resident experience. AI-enabled thermostats, lighting systems, and smart locks can learn from residents’ habits to adjust settings automatically, leading to energy savings and increased comfort. It can also reduce owner expenses by being able to control vacant unit lights, thermostats, etc.in bulk.
- Predictive Maintenance: AI is being used to predict and prevent equipment failures within multifamily buildings. By analyzing data from sensors and historical maintenance records, AI algorithms can identify potential issues before they become significant problems, reducing downtime, and saving costs. This becomes significantly important in high-rise, mid-rise buildings that use MAU, circulation and TEAL systems.
- Resident Experience: AI-powered chatbots and virtual assistants are transforming resident interactions with property management. These tools can handle routine inquiries, schedule maintenance requests, and provide helpful information, improving response times and overall customer satisfaction. AI-enabled property management software could offer personalized experiences to residents. From customizing amenity recommendations to tailoring communication preferences, AI helped property managers engage and retain tenants better.
- Automated Marketing and Leasing: AI is assisting property managers in optimizing marketing efforts by analyzing data to target potential residents more effectively. AI-driven algorithms can help identify the best advertising channels, determine pricing strategies, and even predict lease renewal probabilities.
- Tenant Screening and Risk Assessment: AI is being utilized to assess tenant applications and determine the risk associated with potential renters. Machine learning algorithms can analyze various data points to predict the likelihood of lease defaults and help property managers make more informed decisions. AI-driven tenant screening tools were used to process rental applications faster and more accurately. These tools analyzed applicant data and credit histories, providing property managers with insights to make better-informed decisions.
- Energy Efficiency and Sustainability: AI-driven systems can monitor and optimize energy usage in multifamily properties. By analyzing consumption patterns, AI can identify areas for improvement and suggest energy-saving measures, contributing to more sustainable and eco-friendly operations.
- Data Analytics for Decision Making: AI and machine learning are enabling property managers to make data-driven decisions. By processing vast amounts of data from various sources, AI can provide valuable insights on occupancy trends, rent levels, and maintenance costs, aiding in better decision-making and strategic planning.
- Security and Surveillance: AI-powered surveillance systems can enhance the security of multifamily properties. These systems can detect unusual behavior, recognize faces, and send real-time alerts, improving overall safety and security for residents.
- Rent Prediction: AI algorithms can analyze market trends, economic indicators, and historical data to predict rent fluctuations and demand patterns. Property managers can leverage this information to set optimal rental rates and maximize revenue. AI-powered systems like rent optimization supply and demand tools analyze real-time market data to help property owners and managers optimize rental prices and identify competitive advantages.
- Facility Management: AI can assist in efficiently managing multifamily property facilities by optimizing maintenance schedules, monitoring equipment performance, and suggesting cost-saving measures.
- Occupancy Prediction: Machine learning models were employed to predict occupancy rates accurately, assisting property managers in making strategic decisions related to lease renewals, marketing efforts, and budgeting.
Without a doubt, AI’s potential to streamline operations, enhance resident experiences, and increase efficiency has and will continue to greatly benefit asset owners. There are many IOT platforms that have been launched over the years. It is important to strategically partner with the companies that have already worked through hiccups within algorithms and communication.