TL;DR

• Scale: 70 M+ AI‑scored video interviews completed on HireVue alone by 2024 and climbing.
• Trust gap: 65 % of job seekers feel uneasy with AI screening, and 90% want full disclosure before recording (Economic Times).
• Reg‑tech squeeze: Only 38% of enterprises disclose algorithmic grading up front while fines now reach €35 M / 7% of global revenue (EU AI Act).
• Business upside: Companies with clear consent flows fill roles faster and see a lift in candidate NPS (LinkedIn Talent Trends).
• Grab the six‑step playbook below to transform compliance into brand advantage.

Table of Contents

1. Introduction
2. Why Candidate Consent Matters
3. The Landscape of AI‑Driven Hiring
4. Countdown to Compliance
5. Business Case for Transparency
6. Six‑Step Consent & Transparency Playbook
7. Human + Machine: The Hybrid Sweet Spot
8. Quick Consent Audit Checklist
9. In Summary
10. Get Help From Talivity
11. FAQs

Introduction

A promising candidate completes what looked like a standard one‑way video interview, then learns facial‑analysis software graded every micro‑expression and vocal inflection. Feeling deceived, they post the story on LinkedIn. Within hours, your employer brand is trending for the wrong reasons.

This isn’t hypothetical. As AI hiring scales, the tension between efficiency and candidate trust has reached a tipping point. The solution: explicit, end‑to‑end AI interview consent.

Why Candidate Consent Matters in AI Video Interviews

More than 70 million HireVue video interviews had been completed by 2024, and that number continues to climb as we head further into 2025.

Yet, without transparency, this efficiency can undermine trust. More than 65% of job seekers say they are uncomfortable with AI screening. And those feelings grow when there’s a failure to disclose. Nearly 90% of job seekers want companies to be upfront about their use of AI in recruitment.

Still, many organizations treat algorithmic decision-making as a black box. When candidates discover AI involvement after the fact, negative stories can spread quickly across social channels, damaging the brand you took years to build.

The stakes are clear. 73% of people say a fully automated hiring process would give them a negative perception of a company and its brand. Transparency is critical.

The Current Landscape of AI-Driven Hiring

Today’s platforms, such as HireVue, Modern Hire, Sapia.ai, and Paradox Olivia, offer sophisticated one-way video interviews and conversational AI that can assess everything from communication skills to cultural fit.

Enterprises are adopting automated employment decision tools in a big way. Spending on video interviewing software hit $410 million in 2024 and is forecast to more than double by 2033. 

Emerging trends include:

• Multimodal emotion analysis
• Large language model (LLM) interview scoring
• Mobile-first candidate flows

Countdown to Compliance: The Regulatory Landscape

Companies are facing a complex set of regulations, which vary by jurisdiction. Here are just a few of the emerging laws employers must navigate.

Illinois AI Video Interview Act

Active since 2020 and amended in 2024, the Illinois AI Video Interview Act requires written notice to candidates, disclosure of evaluation factors, and 30-day deletion rights. It’s the most established framework, offering a template for other states.

NYC Local Law 144

New York City Local Law 144 focuses on bias prevention through mandatory annual independent audits, public summary reports, 10-day advance notice to candidates, and opt-out paths.

EEOC Technical Guidance

Under Title VII, the U.S. Equal Employment Opportunity Commission requires adverse-impact testing on automated employment-decision tools (AEDTs). This pushes companies to prove their AI systems don’t discriminate against protected classes.

EU AI Act — High-Risk Hiring Systems

The most comprehensive framework arrives in phases through 2026-27 with the EU AI Act, requiring pre-deployment risk assessments, human oversight, and explicit transparency for high-risk hiring systems.

The Business Case for Consent & Transparency

Beyond compliance, AI hiring transparency drives measurable business outcomes. Only about a quarter of job applicants say they trust AI in hiring, creating a significant opportunity for employers that are fully transparent.

There are also significant financial risks for non-compliance. NYC fines reach up to $1,500 per infraction with no cap on civil penalties. EU penalties can hit €35 million or 7% of global revenue.

Maintaining compliance is obviously important, but there’s also an upside to expanding use. Higher consent rates expand training datasets, improving model accuracy and reducing false negatives that might cause you to miss potentially great employees.

Transparency drives both risk mitigation and competitive advantage.

A Six-Step Consent & Transparency Playbook

So, how do you ensure your AI video interviewing process is transparent and compliant? Here’s a six-step playbook:

1. Pre-Interview Disclosure

Create plain-language notices supported by FAQ microsites and brief explainer videos. Avoid legalese to make sure candidates understand when AI is used, how it’s used, and why it matters.

2. Affirmative Opt-In & Alternative Path

Implement consent with logged timestamps. For candidates who opt out, you’ll need to decide whether you will offer alternatives or live interviews. This may be necessary to ensure your talent pipeline remains inclusive, attract top candidates, and help avoid legal claims.

3. Explainability Layer

Provide post-interview score breakdowns with links to bias-audit summaries. Candidates deserve to understand how they were evaluated.

4. Independent Bias Audits & Public Reporting

Conduct annual third-party audits and publish summaries on your careers site.

5. Data Retention & Deletion

Establish retention schedules that align with regulations such as GDPR and offer self-serve deletion where possible.

6. Accessibility & Accommodation

Ensure captioning, screen-reader compatibility, and disability-specific adjustments to avoid discrimination in your hiring process.

Human and Machine: Finding the Hiring Sweet Spot

You shouldn’t be choosing between human judgment and machine efficiency. Combining both strategically is key. AI can detect patterns and surface insights, but you need humans to preserve empathy, context, and final decision-making authority.

Ownership of candidate experience remains shared, but accountability must stay human. This hybrid approach satisfies both efficiency goals and ethical obligations.

Quick Consent Audit Checklist

• Plain-language AI notice sent and acknowledged?
• Explicit opt-in captured and logged with timestamps?
• Bias-audit results publicly available and current?
• Data deletion request workflow functional and tested?
• Human interview alternative offered and staffed?
• Is algorithm drift monitoring active and documented?
• Are disability accommodations verified and accessible?

In Summary

Ethical AI interviewing is not a compliance tax; it’s a brand moat. Lead with transparency, follow the six‑step playbook, and turn AI interview consent into a magnet for top talent.

Get Help From Talivity

AI interview ethics is sometimes viewed as a “compliance tax.” In reality, AI hiring transparency is a competitive advantage. Companies that embrace transparency early will differentiate their brand, attract top talent, and build sustainable hiring practices that scale with regulatory requirements.

Use our HR Tech ROI Calculator to quantify the cost of AI-interview compliance.

Ready to embed consent into every click? Talivity’s Employer Brand & Compliance team delivers bias-audit roadmaps, policy kits, and candidate-experience design. Book a free assessment today.

FAQs

What happens if candidates opt out of AI analysis?

Consider providing alternative pathways, such as live interviews with human recruiters. This ensures your hiring process remains inclusive and helps you avoid missing top talent who prefer human interaction.

What if our current vendor doesn’t support transparency features?

Evaluate vendors based on their compliance capabilities, bias audit support, explainability features, and consent management tools. Many leading platforms now offer these features as standard.

How do we handle data requests and deletions?

Implement self-serve deletion workflows where possible, establish clear retention schedules, and ensure your systems can quickly locate and remove candidate data upon request.

Leighann Emo

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With a rich background in content development, Leighann creates engaging, educational articles that resonate with growing businesses. Her commitment to delivering informative and compelling content underscores her dedication to keeping Talivity at the forefront of thought leadership in the talent acquisition and recruitment marketing industry.