We Started with a Question...
The Data Gave Us A Mission
How WAV Institute Began
In early 2023, Joy Morales began noticing something troubling. She was asking AI platforms to recommend attorneys, and the names coming back skewed heavily male. Not because women attorneys were less qualified. Not because they had weaker practices. But because the systems doing the recommending had never been built with them in mind.
She started testing systematically. Then more systematically. By early 2025, what had started as professional curiosity had become a full research methodology, a proprietary AI Visibility Framework built specifically to measure how women attorneys appear across ChatGPT, Gemini, and Perplexity.
In January 2026, WAV Institute launched publicly with the Colorado Women Attorneys AI Visibility Report, the first study of its kind. 209 attorneys. 19 scoring criteria. Two AI Platforms. The findings were stark: 69.4% of Colorado women attorneys scored below the AI visibility threshold on ChatGPT. The Texas report followed. Then on to Florida. The pattern doesn't change by state. But the solutions do, and WAV Institute is building both.
​
Our Mission
What We're Here to Do
WAV Institute's mission is to close the AI visibility gap for women attorneys through research that measures the problem, education that explains it, and services that fix it.
We Operate from Three Core Beliefs:
#1 What Gets Measured Gets Changed - Awareness isn't enough. WAV Institute produces rigorous, empirical, state-by-state research so the disparity isn't just felt, it's documented, scored, and traceable to specific technical causes.
#2 The Window is NOW - AI-powered search is already mainstream, but most attorneys haven't optimized for it yet. The attorneys who act in 2026 establish structural advantages that compound over time. Those who wait face an increasingly steep climb
#3 This is a Structural Problem with Structural Solutions - The AI Visibility gap isn't a branding problem. It isn't a confidence problem. It's a technical and systemic problem rooted in how AI was trained and how the web is coded. Those problems have real, implementable fixes.
​
The Research
The Nation's most rigorous research on AI Bias in the Legal Profession. WAV Institute's state studies are not surveys or opinion polls. They are scored, empirical analyses of real attorneys across live AI platforms, using a proprietary framework developed and refined over two years of methodology work. Every attorney in our studies receives a visibility score built from documented criteria, digital footprint, schema markup quality, crawler accessibility, citation source presence, platform-specific signals, and credential verification. Scores are mathematically verified. Data is anonymized in public reports. The framework details are proprietary.
​
What We've Published:
Colorado Women Attorneys AI Visibility Report - January 2026, 209 attorneys. ChatGPT and Gemini. 19-point framework. Maximum score 95 points. Key Finding: 69.4% below visibility threshold. 94% lacking proper schema markup.
​
Texas Women Attorneys AI Visibility Report - April 2026, 336 attorneys. ChatGPT, Gemini, and Perplexity. Expanded 100-point framework. Key finding: 51.8% below visibility threshold. 84% have schema markup only 28% have the right kind.
​
Florida Women Attorneys AI Visibility Report - Coming May 2026
​
The Double Bias Problem
Why This Doesn't Fix Itself
​
WAV Institute's research led to the identification of what we call the Double Bias Problem, the compounding structural disadvantage women professionals face in AI recommendation systems.
​
It works like this:
Layer 1 - Historical Training Data Bias - AI systems were trained on decades of web content that underrepresented women professionals. The models learned, at a foundational level, to associate professional authority with male names and credentials.
​
Layer 2 - Live Web Bias - Today's web still skews toward men in positions of professional visibility, more citations, more directory prominence, more schema-optimized profiles. AI systems continue to learn from this environment in real time.
​
Layer 3 - The Compounding Feedback Loop - Attorneys who are cited by AI gain more visibility, which generates more citations, increasing their score. Attorneys who aren't cited fall further behind, not because their credentials have changed, but because the gap compounds. The Result: passive inaction doesn't hold your position. It accelerates your invisibility. That's why 2026 is the critical window and why WAV Institute's work is urgent.
​
OUR TEAM
Our diverse team combines research expertise with technical skills to address AI visibility bias.
Joy Morales, MA
Founder/CEO
Tim Hallam,
AI Visibility Specialist
Candace Conley,
Sales Director
Kristen Kramer,
Schema Mark up
Specialist
Mark Vallecera,
AI Visibility
Technician
​
Joy Morales, MA
CEO/Founder
Joy brings together two decades of digital marketing experience and a rigorous research background to a problem most of the legal industry hasn't named yet. In 2023, she began studying AI visibility patterns, two years before WAVI's public launch. She holds a Master's degree in Education Research, which shapes WAVI's methodology at every level: statistical rigor, framework validation, mathematical verification of published findings, and a commitment to reproducibility. She is a Texas MCLE-accredited CLS sponsor (Sponsor No. A18496) and the architect of WAVI's proprietary AI Visibility Framework. Joy is based in Colorado Springs, CO
Tim Hallam
AI Visibility Specialist
Tim leads WAVI's technical auditing infrastructure, the layer of the research that goes beyond scoring into the structural causes of invisibility. He conducts Sitebulb-based schema audits across every state study, identifying not just whether schema markup exists but whether it's the correct type and whether AI crawlers can actually reach it. His analysis of Texas attorney websites produced one of the WAVI's most important findings: 84% of attorneys have schema markup, but only 28% use the correct LegalService designation. The rest carry what WAVI calls a "false signal", code that looks right but tells AI the wrong information.
Candace Conley
Sales Director
Candace leads client outreach and enrollment for WAVI's courses and services. She works directly with women attorneys, bar associations, and legal organizations to connect them with WAVI's research and solutions, translating the data into conversations that help attorneys understand what's at stake and what they can do about it.
Kristen Kramer
Schema Markup
Specialist
Kristen handles schema implementation for WAVI's service clients, translating audit findings into correctly coded, AI -readable structured data on attorney websites. She specializes in LegalService schema, GPS coordinate markup, credential verification schema, and the crawler accessibility configurations that ensure AI can reach and read what's been built.
Mark Vallecera
AI Visibility Technician
Mark leads WAVI's AI visibility scanning operations, executing standardized scans across ChatGPT, Gemini, and Perplexity for every attorney in our state studies. His work produces the clean, consistent data that powers every finding in our published research.