AI GOVERNANCE • RESPONSIBLE IMPLEMENTATION
Creating a practical AI governance framework for real estate data and marketing
How I helped translate emerging AI risks into clear standards for disclosure, accuracy, data protection, education, and compliance across an MLS organization serving more than 3,700 users.
3,700+
users supported
5
core governance
priorities
2026
policy implementation
Generative AI created new opportunities for efficiency and marketing while introducing risks involving inaccurate content, altered property images, undisclosed modifications, consumer confusion, and exposure of confidential data. The organization needed standards that protected data integrity without preventing responsible use.
The challenge
Coordinated operational preparation with internal teams and platform partners.
Built member communications, training, and support resources for adoption.
Identified workflow impacts and helped turn them into repeatable processes.
What I led
The governance framework
The five priorities are explained here, below the three-number results band.
01
True representation
AI-altered imagery cannot misrepresent
the condition of a property.
02
Disclosure of AI-altered content
Altered and synthetic images require
clear identification.
Case Studies / AI Governance & Responsible Implementation
03
Protection of material property information
AI cannot conceal defects or
misrepresent condition.
04
Data privacy and approved tools
Confidential information must be
protected in AI systems.
05
Human oversight & accountability
AI supports professional judgment but does not replace responsibility for accuracy, compliance, or final decisions.
My role
Monica Decker
Director of MLS &
Platform Operations
• Product Operations
• Platform Strategy
• Program Management
• Vendor Management
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