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Creating and Nurturing Trust in Multifamily AI Learning and Training Models

The biggest misconception of artificial intelligence and machine learning solutions is that they automatically solve operational deficiencies negatively impacting your business. Just like your on-site and off-site employees, multifamily technology needs to be trained to follow your company’s standards. These standards include operations, leasing, and the property’s brand voice to nurture your defined audience through their desired user experience and digital channel. 

Three considerations that AI and machine learning models must learn to create trust in their ability to automate steps of the customer journey and become an accurate self learning AI platform (Hint: It’s a human thing):

1. Customers need a Digital Human to be able to replicate the talent of onsite and overworked leasing consultants, and other office team members, to facilitate a seamless leasing operation, digitally. 

2. Providing a 5-star customer service experience is key to improving online reputation scores and resident satisfaction surveys in a fast paced leasing environment. A Digital Human must nurture the needed bedside manner delivered by onsite team members to solve complex customer problems.

3. Learning from each user and customer experience insight provides the refinement needed to improve business processes so that you can deliver incremental customer and business value.

Understanding the Power of Conversational AI in Property Management

AI learning is best facilitated when there is a set of defined standards, rules, instructions, and tasks to follow up and evaluate the outcomes in customer conversations. Conversation designers interpret perceived customer value from conversations across different modes of communication (chat, SMS, email, voice assistant, and cell phone calls) via different customer input types (voice, click or text). 

Conversational AI reporting and analytics tools give insights to customer conversations via different modes of communication and different customer input types to help you better understand how to provide transparency to your stakeholders on your AI data training standards and code of ethics driving your customer and business outcomes.  

A resident interacting with an AI assistant on a laptop.

AI and Machine Learning: The Future of Resident Interaction

It all starts with evaluating what your team is actually doing compared to what your team is telling you they’re doing. I know it may sound bad, but I mean this with the best intention. Using technology like CRMs and other experience builders is one of the main reasons you might not be getting a clear picture of what’s happening in customer interactions.

Understanding what customers are saying in property management reports and comparing it to the leasing activity notes is part of the journey to understand your audience. Digital behavior across your third party applications and SEO performance data is the contextual information national leaders need to understand in one quick glance.

To present that picture to your senior leadership, you have to start from the problem and work yourself backwards, step by step, so that you can start back from the beginning and achieve a different outcome at the end. AI & machine learning take what instructions or feedback of these steps you provide, run with it automatically, and then give you a status update once it's done. What you learn from the outcome is how to train the AI so that your customer interactions are automated with the trust you put into your AI training.

How AI and Machine Learning Improve Customer Interactions

Natural language processing is the heart and soul of conversational AI which transforms a chatbot to communicate with users in a way that it has 1) human-like conversations, 2) personalized experiences, and 3) effortless accessibility, allowing users to interact with the chatbot using their own words.

In your journey to bridge the physical and digital experiences, NLP plays a pivotal role in making these interactions not just functional but also enjoyable and natural in the virtual apartment leasing experience vs. in-person tours.

The Role of Natural Language Processing in Conversational AI

To deliver a five star customer experience, AI training has to easily translate the complexity of your business operations and chat with your customers as if it were a real person. People are more at ease using technology that they understand and technology that understands them. As technologists, you can build trust in conversational AI solutions when you know each step that is needed to achieve a prosperous and seamless customer operation. That’s when you can evaluate an outcome-based business model powered by a conversational AI proptech chatbot, like Digital Human

Building Trust in AI Systems: A Crucial Aspect

Building trust in AI is not just a technological challenge; it's a critical aspect of creating exceptional user experiences and propelling the widespread adoption of AI-driven solutions

Trust is the cornerstone of any successful AI implementation. When users trust the technology, they're more likely to engage with it. In the quest for a five-star customer experience, AI should effortlessly simplify the complexity of business operations. This ensures that interactions with AI feel natural and user-friendly, ultimately leading to higher satisfaction levels.

Users are most comfortable when AI can mimic human conversations. When AI can chat with customers as if it were a real person, it eliminates friction in communication. This comfort factor leads to more meaningful and productive interactions, contributing to a superior user experience.

Trust is closely tied to users' comprehension of the technology. People are more at ease with technology they understand. They feel comfortable when they can predict how AI will respond or assist them. This understanding is crucial in encouraging users to adopt and embrace AI solutions

Why Trust in AI Learning and Training is Essential

The number one way to overcome challenges in establishing trust in a technology that is making recommendations on what it is taught is to learn to understand how to best use the technology to  fit your business model. Once you have that defined, mapped out, and translated into standard procedures for each of your employees, you gain team unity to deliver a greater focus on customer and business needs. Once you have an AI training and learning operation in place, you have to be able to create a feedback system that allows your process to evolve over time based on the changes in the business. 

Overcoming Challenges in Establishing Trust in AI Solutions

Holding the team accountable to these changes is one of the biggest challenges and it’s not because technologists don’t care. There are factors like new technology to the market, changes in product development roadmaps, and the need to adapt to business needs. Today, more than ever, there is a need for faith in your third party vendors and your own team members to work together to achieve the right outcomes. 

Implementing Trustworthy AI Training Programs in Multifamily Management

Principles for Effective AI Data Training

AI development is not a one-person show. Collaboration between data scientists, domain experts, ethicists, and legal professionals is essential for addressing complex data and ethical challenges. 
On a property management team, you may not have all the resources you need to create the perfect AI language model, but building best practices that meet your objectives and operate ethically, accurately, and effectively is key to overcoming your challenges. That’s how you unlock the full potential of your AI, one best practice at a time, so that you can bridge between the business and your customers, providing human-like interactions and invaluable insights. 

Nurturing Trust through Continuous Learning and Improvements

Understanding who your audience is at each of your properties is the first step to nurture trust in Online Leasing for Apartments in the Digital Age. From all the conversations your renters are having before they sign a lease, after they move in, and right before renewal, you can create pivotal conversational experiences guided by your AI solution in the renter’s journey.

Sometimes, the bad reviews and the negative experiences that you and your teams encounter can be painful. What you learn from those customer interactions and how you provide feedback to your organization to update their processes is the self-reflection you take to better understand how to select, train and implement the right AI solution for your business. Nothing in this business is steady and having transparency in your dynamic operation is what will drive the right outcomes for your organization.

AI in Property Management: The Evolution of Resident Communication

It's essential to work with your teams and technology partners to articulate customer problems so that these AI & machine learning technologies can learn to understand how to solve your customer needs. AI chatbots require careful training to align with your specific standards. 

Within this context, Natural Language Processing (NLP) takes center stage, enabling human-like interactions in virtual settings. Trust in AI is a must for superior user experiences and widespread adoption, supported by a foundation that understands the technology, nurtures collaboration, and follows ethical practices. Trust acts as the bridge connecting your business with customers in the digital age, ensuring the success of conversational AI solutions and AI data training.