The ultimate AI glossary for Property Managers 

Article by Kate Sunol Marketing Manager, Industry and Growth 28 January 2026

Everything you need to understand the AI terms reshaping property management in 2026. 

Artificial Intelligence (AI) has rapidly moved from buzzword to daily reality in property management. From automated email replies to insights dashboards, communication tools and workflow automations, today’s platforms are packed with AI that helps teams work faster, smarter and more consistently. 

But as AI becomes more common, so does the terminology, and it can be confusing to know which terms matter, what they mean and how they apply to your role. 

This guide breaks down the most important AI concepts in simple, Property Manager friendly language, with examples grounded in inspections, trust accounting, leasing, arrears and communication. 

Whether you’re new to AI or already using features like Reply with AiMe, this glossary helps you understand the tech behind the tools. 

Why AI matters in property management 

Property Managers juggle some of the most complex workloads in real estate. Every day involves hundreds of micro-tasks: emails, maintenance, inspections, arrears, follow-ups, reporting, updates and customer expectations. 

AI helps lighten that load by: 

• Automating routine work 
• Improving communication quality 
• Reducing manual errors 
• Helping you respond faster 
• Keeping workflows consistent 
• Supporting new staff with on-demand knowledge 

Put simply, AI helps Property Managers deliver great service without burning out. 

The complete AI glossary for Property Managers

Below is an extended glossary designed for practical value, by breaking down technical jargon. 

API (Application Programming Interface) 

Allows different systems to communicate. 

PM example: PropertyMe syncing with inspection tools, partner apps, accounting systems or AI assistants.  

Artificial intelligence (AI) 

Technology that performs tasks typically requiring human thinking such as understanding language, analysing data or making recommendations. 

PM example: Drafting emails, summarising tenant messages or suggesting the next task in a vacate workflow. 

Automation 

A process that runs automatically without manual steps. 

PM example: Automatic arrears reminders or task creation triggered when a tenant gives notice.

Bias 

When AI produces skewed outcomes based on biased data. 

PM example: If historical workflows emphasise maintenance tasks, the AI may over-prioritise these unless corrected.  

Chatbot or virtual assistant 

AI that communicates with users through conversation. 

PM example: A tool that helps tenants troubleshoot basic questions before they reach your team. 

Context window 

The amount of information an AI can consider in one go. 

PM example: Whether the AI can read the entire tenancy history before drafting an owner update. 

Generative AI

AI that creates new content, text, images, or ideas, based on your instructions. 

PM example: AiMe generating clear replies to long owner enquiries or preparing inspection summaries.

Hallucination 

When AI generates answers that sound correct but aren’t. 

PM example: AI creating a policy that doesn’t exist. This is why human oversight remains crucial.  

Large language model (LLM) 

A powerful AI trained on huge volumes of text that can read, write, summarise and understand natural language. 

PM example: When your AI tool accurately interprets a tenant email written in slang or frustration and drafts a calm, professional response. 

Machine learning (ML) 

A type of AI that learns from patterns and improves over time. 

PM example: A system recognising which tasks you prioritise during end-of-month and adjusting suggestions. 

Natural language processing (NLP) 

The part of AI that helps computers understand human language. 

PM example: Categorising tenant messages into maintenance, rent, pets or general enquiries automatically. 

Predictive analytics 

AI that forecasts what might happen next using patterns in data. 

PM example: Identifying tenants at higher risk of arrears based on payment history. 

Prompt

The instruction you give an AI tool. 

PM example: “Draft a friendly reminder email about overdue rent.” 

Prompt engineering 

Writing clearer prompts to get better results. 

PM example: Adding context: “Tenant usually pays on time. Keep the tone warm but firm.”

Reinforcement learning 

AI that improves based on feedback, similar to coaching. 

PM example: A chatbot learning which types of responses customers rate as helpful.  

Supervised learning 

AI trained using labelled examples. 

PM example: Teaching the system what qualifies as “urgent maintenance” by feeding it correct examples. 

Training data 

The data used to “teach” an AI model how to behave. 

PM example: Thousands of historical emails helping the AI learn the tone and structure of professional communication. 

Unsupervised learning 

AI that identifies patterns without human guidance. 

PM example: Spotting trends such as seasonal spikes in maintenance or average time-to-lease. 

Workflow automation 

A sequence of automated steps connected together. 

PM example: Starting a lease renewal automatically triggers tasks for rent review, offer letters, follow-ups and reminders. 

Property management-specific AI terms 

These are terms you’ll hear increasingly as AI features are embedded into tools like PropertyMe. 

AiMe

PropertyMe’s AI assistant

PM example: Reply with AiMe, AiMe Comply and Grow CRM’s AiMe assist.

AI-assisted communication 

Emails or messages generated or suggested by AI. 

PM example: AiMe suggesting responses for maintenance follow-ups, arrears or inspection bookings.

AI-generated summaries 

Shortened versions of long emails, threads or histories. 

PM example: A one-paragraph summary of a 20-message conversation with an owner.  

AI-powered insights 

Analytics enhanced by automated analysis. 

PM example: Insights dashboards showing real-time trends in arrears, maintenance or inspection outcomes. 

Conversational AI 

AI that interacts using natural conversation. 

PM example: Chat tools that understand natural tenant language like “Hey, I think the hot water’s gone again.” 

Entity recognition 

AI identifying key pieces of information within text. 

PM example: Spotting addresses, tenant names or dates within emails to fill in database fields. 

Knowledge base AI 

AI layered on top of a knowledge base to help users quickly find answers. 

PM example: Asking “How do I complete an end-of-month reversal?” and receiving step-by-step instructions instantly. 

Smart checklists 

Checklists powered by automation triggers. 

PM example: Completing “Keys Collected” automatically reveals the next steps in your vacate workflow. 

Text classification 

AI categorising messages or documents into groups. 

PM example: Automatically tagging emails as maintenance, rent, pets, general enquiry or complaint. 

Putting AI into practice: how Property Managers can use this glossary 

Understanding these terms helps you: 

• Communicate more confidently with tech teams 
• Choose AI tools that actually solve workflow problems 
• Understand new features as PropertyMe expands its AI capabilities 
• Improve your prompting and task accuracy 
• Train teams on best practice 
• Future-proof your agency 

The Property Managers who understand AI today will be the leaders shaping the industry tomorrow. 

What’s next? AI at PropertyMe 

PropertyMe is continuing to build AI features designed specifically for the real estate industry, with a strong focus on: 

• Accuracy 
• Trust 
• Transparency 
• User control 
• Compliance 

From Reply with AiMe to smart automations, insights, CRM expansion and more, AI is becoming a core part of the PropertyMe ecosystem.