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AI Bias Audit

Is Your AI a Legal Liability?

If your organization uses AI to screen applicants, assess loan eligibility, score candidates, or make any automated recommendation — you may already be subject to federal anti-discrimination law and state-level AI bias regulations. Most organizations don't know until they're facing a complaint, a lawsuit, or a regulator.

70%

of companies let AI reject candidates with no human review

$613M

AI Bias Audit market in 2025, growing 6.7% CAGR

5+ States

active or pending AI bias laws as of 2026

Aug 2026

EU AI Act high-risk rules take effect

The Problem

Your Vendor's Audit Doesn't Protect You

The trap most organizations fall into: assuming your AI vendor has already handled compliance. They haven't — at least not for you. Vendor bias audits protect the vendor. You are still liable for the outcomes their tool produces in your workflow.

AI-influenced scores and rankings can be treated as “decision-making” under employment law, fair lending law, and other regulations — even when a human makes the final call.

Real Exposure

Employers in CA-based litigation against Eightfold AI are learning this the hard way. Lenders using AI scoring models face CFPB scrutiny under the Equal Credit Opportunity Act.

Industries & Use Cases We Cover

HR & Recruiting

ATS algorithms, video interview scoring, pre-employment assessments, chatbot screening

Title VII, ADEA, ADA, NYC LL144, CO, CA

Financial Services & Lending

Credit scoring models, loan underwriting AI, fraud detection, customer risk scoring

ECOA, Fair Housing Act, CFPB guidance

Insurance

Underwriting AI, claims routing, risk scoring models

State insurance regulations, disparate impact doctrine

Healthcare

Patient triage algorithms, care management tools, prior authorization AI

ACA Section 1557, CMS non-discrimination rules

Any Regulated Industry

Any AI or algorithm used in consequential decisions about people

EU AI Act (Aug 2026), emerging U.S. federal guidance

Our Methodology

6-Phase AI Bias Audit Process

A structured, repeatable process with measurable, defensible outcomes — built on 15+ years of Fortune 500 product and operations leadership.

01

Discovery & Inventory

  • Map all AI touchpoints in your workflow
  • Identify vendor tools vs. internal systems
  • Collect training data documentation
  • Define in-scope roles and jurisdictions
02

Vendor Audit Review

  • Evaluate vendor-provided bias audits
  • Assess gaps in vendor documentation
  • Identify what's NOT covered by vendor compliance
  • Flag tools without published audit results
03

Adverse Impact Analysis

  • Statistical testing across demographic groups
  • Apply EEOC four-fifths / 80% rule
  • Counterfactual scenario testing
  • Proxy variable identification
04

Regulatory Mapping

  • Map findings to NYC LL144 requirements
  • Assess Colorado, California, CFPB obligations
  • EU AI Act high-risk classification check
  • Multi-jurisdictional compliance summary
05

Audit Report & Findings

  • Written audit report with supporting data
  • Risk scoring by tool and process
  • Bias sources identified and documented
  • Executive summary for leadership
06

Remediation Roadmap

  • Prioritized remediation action plan
  • Human oversight policy template
  • Vendor negotiation guidance
  • Monitoring and governance framework

Coverage

Protected Classes & Bias Vectors

Federally Protected Classes

  • Race and national origin (Title VII)
  • Gender and sex (Title VII)
  • Age, 40+ (ADEA)
  • Disability status (ADA)
  • Pregnancy and family status
  • Religion

Emerging & High-Risk Bias Vectors

  • Neurodiversity (autism, ADHD — video/voice AI)
  • Resume gaps (caregiver and parental bias)
  • School / credential pedigree filtering
  • Geographic and zip code proxies
  • Communication style and accent detection
  • Intersectional bias (race × gender × age)

Deliverables

What You Receive

Every engagement produces documentation you can use internally, with legal counsel, or in front of a regulator.

01

AI Tool Inventory Report

A complete register of every AI system, algorithm, or vendor tool touching your applicant or decision funnel.

02

Vendor Gap Analysis

Identifies what your vendors' existing audits do and don't cover — and where you remain exposed.

03

Adverse Impact Analysis

Statistical testing across protected classes with EEOC-aligned metrics and methodology documentation.

04

Regulatory Compliance Map

A jurisdiction-by-jurisdiction breakdown of your obligations under current and pending laws.

05

Written Audit Report

Fully documented findings suitable for internal review, legal counsel, or regulatory disclosure.

06

Remediation Action Plan

Prioritized, practical steps to reduce bias exposure — including vendor negotiation guidance.

07

Human Oversight Policy Template

A ready-to-adopt policy governing how AI recommendations are reviewed and overridden.

08

Governance Framework

Ongoing monitoring cadence, documentation protocols, and 4-year record-keeping guidance.

Why Us

Why Technovative AI

Fortune 100 Leadership Experience

25+ years of product, operations and engineering leadership experience at McKinsey and Fortune 100 companies. Enterprise-grade rigor brought to every engagement.

SMB-First Approach

Enterprise-grade AI compliance made accessible and affordable for growing businesses. We scope work to your actual risk profile — not a one-size-fits-all checklist.

6-Phase Proven Methodology

Structured, repeatable process with measurable, defensible outcomes. Our methodology was purpose-built for AI bias work and adapts to any regulated industry.

Start with a Free Consultation

Not sure where your exposure is? Our free 30-minute session is the right first step. We'll review your AI tech stack, identify your highest-risk touchpoints, and scope a bias audit engagement — at no cost to you.