Enterprise AEDT Auditing: Managing Compliance at Scale

The Enterprise Compliance Challenge

Enterprise organizations face a fundamentally different compliance challenge than SMBs. Where a startup might use one AI hiring tool across one jurisdiction, an enterprise may deploy dozens of tools across multiple business units, geographies, and regulatory regimes.

This scale creates complexity that requires a systematic approach. Ad hoc auditing — reviewing one tool at a time as questions arise — does not work at enterprise scale. This guide outlines a framework for managing AEDT compliance across a large organization.

Step 1: Build a Complete AEDT Inventory

Scope the Inventory

Enterprise AEDT inventories must cover:

• All business units: Each division may use different tools independently
• All geographies: Different offices may have different hiring technology stacks
• All hiring stages: From sourcing and screening through assessment, interviewing, and offer decisions
• All tool types: ATS features, standalone screening tools, assessment platforms, interview analysis, background check tools, and any custom-built solutions
• All vendor relationships: Including tools embedded in larger platforms that may not be marketed as "AI"

Categorize by Risk

Not all AEDTs present equal compliance risk. Categorize each tool:

• High risk: Tools that make or substantially influence selection decisions (resume screeners, automated assessments, ranking algorithms)
• Medium risk: Tools that inform but do not drive decisions (analytics dashboards, candidate insights)
• Low risk: Tools that automate administrative tasks without influencing selection (interview scheduling, communication management)

Focus audit resources on high-risk tools first.

Maintain the Inventory

The AEDT inventory must be a living document:

• Assign ownership to a specific role (typically in HR technology or compliance)
• Require procurement to flag any new tool with AI capabilities before deployment
• Review and update quarterly
• Include contract renewal dates to trigger re-audit planning

Step 2: Map Regulatory Requirements

Multi-Jurisdictional Compliance Matrix

Build a matrix mapping each AEDT to the regulations that apply based on where it is deployed:

| Tool | NYC LL144 | CA AB 331 | CO AI Act | EU AI Act | EEOC/Title VII | |---|---|---|---|---|---| | ATS AI Screener | Yes (NYC office) | Yes (CA office) | Yes (CO office) | Yes (EU offices) | Yes (all US) | | Video Interview AI | Yes | Yes | Yes | Yes | Yes | | Skills Assessment | No (not used in NYC) | Yes | No | Yes | Yes |

This matrix determines audit scope and requirements for each tool.

Harmonize Requirements

Where possible, design audit processes that satisfy the strictest applicable requirements. An audit that meets EU AI Act standards will generally satisfy NYC LL144 requirements as well. This reduces duplication.

Step 3: Establish Governance

Roles and Responsibilities

• CISO/DPO: Overall accountability for AI governance
• HR Technology: AEDT inventory maintenance and vendor management
• Legal/Compliance: Regulatory monitoring and interpretation
• Data Science/Analytics: Technical audit execution and methodology oversight
• Business Unit HR: Data provision and remediation implementation
• Procurement: Pre-deployment AI screening and vendor due diligence

Policies and Procedures

Document and maintain:

• AEDT acceptable use policy
• Bias audit methodology standards
• Remediation procedures when bias is detected
• Vendor AI due diligence requirements
• Candidate notification standards
• Data retention and privacy requirements for audit data
• Escalation procedures for critical findings

Reporting Structure

• Quarterly compliance dashboard to executive leadership
• Annual comprehensive report to the board
• Immediate escalation for critical findings (impact ratios below 0.70 or statistically significant adverse impact)

Step 4: Execute Audits at Scale

Audit Scheduling

For enterprises with many AEDTs, stagger audits throughout the year:

• Q1: Audit tools deployed in the previous year
• Q2: Re-audit high-risk tools from Q1 of the prior year
• Q3: Audit tools with significant model updates
• Q4: Comprehensive annual review and planning for next year

Data Pipeline

The largest bottleneck in enterprise auditing is data preparation. Build a systematic pipeline:

1. Define a standard data schema for audit input (demographics, outcomes, stages, dates)
2. Create automated exports from each ATS and HRIS system
3. Validate data quality before each audit (completeness, accuracy, format)
4. Maintain historical data for trend analysis

Batch Processing

Use platforms that support batch auditing — uploading data for multiple tools or business units simultaneously rather than processing each one manually. OnHirely supports batch processing for enterprise clients.

Intersectional Analysis at Scale

Enterprise data volumes typically support robust intersectional analysis. Ensure your audit process includes cross-tabulation across all protected categories, not just the minimum required by specific regulations.

Step 5: Remediate Systematically

Remediation Workflow

When an audit identifies adverse impact:

1. Triage: Assess severity (how far below 0.80 is the impact ratio?) and scope (how many candidates affected?)
2. Root cause analysis: Work with the vendor or internal data science team to identify the source of bias
3. Develop remediation plan: Define specific actions, owners, and timelines
4. Implement fixes: Make changes to the tool, data, or process
5. Verify: Re-audit after remediation to confirm the fix worked
6. Document: Maintain records of the entire remediation lifecycle

Common Enterprise Remediation Patterns

• Model retraining: Vendor retrains the model on more representative data
• Feature engineering: Remove or adjust features that serve as proxy variables
• Threshold adjustment: Modify cutoff scores to reduce adverse impact while maintaining quality
• Process change: Add human review stages for borderline candidates
• Tool replacement: If remediation is not feasible, switch to a less biased alternative

Step 6: Monitor Continuously

Dashboards and Alerts

Enterprise compliance requires real-time visibility:

• Impact ratio dashboards updated weekly or monthly
• Automated alerts when impact ratios approach the 0.80 threshold
• Trend tracking to identify gradual drift toward adverse impact
• Comparative views across business units and geographies

Integration with GRC

AI hiring compliance should integrate with your existing governance, risk, and compliance (GRC) infrastructure. Audit results, remediation actions, and compliance status should be trackable alongside other enterprise risk metrics.

How OnHirely Serves Enterprise Clients

OnHirely's enterprise tier is built for scale. The platform supports multiple tools and business units, batch data processing, custom reporting templates aligned with internal governance requirements, API integration with ATS and HRIS systems, role-based access for distributed compliance teams, and audit trails that satisfy the strictest regulatory requirements. Enterprise clients work with a dedicated compliance advisor who helps design and execute their audit program.