25th August 2025

Your AI hiring tools: Compliant or Risky?

The promise of AI-powered hiring tools is compelling: streamlined processes, faster candidate screening, and data-driven decisions that could revolutionise your talent acquisition. Around 78% of organisations had adopted AI technologies by 2024, with recruitment being one of the fastest-growing applications. But before you implement that shiny new AI screening tool, there's a critical question every STEM business needs to ask: Is your AI hiring technology compliant, or could it be exposing you to significant legal and reputational risks?

The Compliance Challenge

In 2024 alone, over 400 AI-related bills were introduced across 41 states in the US, demonstrating unprecedented concern about AI's employment impact. While the UK hasn't seen similar volumes of AI hiring legislation, existing data protection, GDPR, and equality laws still apply, and they're becoming increasingly complex to navigate with AI tools.

Transparency Challenges

Under UK GDPR, individuals have the right not to be subject to automated decision-making, including profiling, which produces legal effects or significantly affects them. This means purely automated hiring decisions could violate data protection law without proper safeguards and human oversight.

Can you clearly explain to candidates why they were rejected? If not, you may be building significant legal risk into your hiring process.

AI and GDPR: A Data Protection Minefield

AI hiring tools process data on a scale far beyond traditional recruitment, often clashing with GDPR’s principles of transparency, purpose limitation, and data minimisation.

Scope of Data Collection

These tools analyse far more than CVs, capturing video micro-expressions, voice patterns, social media activity, typing styles, and even mouse movements, often without candidates fully understanding the extent or purpose of the collection.

Transparency Challenges

GDPR requires clarity on how data is processed, yet many AI systems are “black boxes,” making it difficult for companies to explain their decision-making logic.

Right to Explanation

When candidates seek reasons for automated rejections, AI often offers vague answers, falling short of GDPR’s demand for meaningful insight into decision logic.

Data Retention and Deletion

GDPR grants deletion rights, but removing data embedded in AI training sets can be technically challenging or require retraining entire models.

Cross-Border Transfers

AI hiring platforms often operate internationally, creating extra compliance hurdles, especially for UK businesses post-Brexit, when transferring data to regions with different privacy protections.

AI and discrimination: Beyond obvious bias

Amplification Effect

When algorithms are trained on biased historical data, they not only replicate prejudice but also magnify it, leading to consistent disadvantages for women, minorities, and other groups.

Subtle Discrimination

Bias may emerge in hidden ways: penalising non-native accents, undervaluing certain qualifications, or disadvantaging neurodivergent communication styles.

Intersectionality

AI often fails to detect compounded bias affecting candidates with multiple protected characteristics, such as ethnicity and gender combined.

Proxy Discrimination

Even when direct bias is removed, algorithms may use neutral-seeming factors, like postal codes or extracurriculars that correlate with protected traits.

Feedback Loops

Hiring only certain profiles narrows the training data, making future iterations more discriminatory.

Legal and Regulatory Pressure

The EU’s AI Act and UK equality regulators are targeting AI hiring bias, holding businesses liable for both direct discrimination and failure to monitor it.

Building Compliance Into Your AI Strategy

Audit your current tools: Map all AI-powered tools in your hiring process. Many businesses are surprised by how much AI they're using without proper compliance oversight.

Implement human oversight: Ensure AI recommendations are reviewed by trained hiring managers who can spot bias and make final decisions.

Regular testing: Monitor AI tools for bias and accuracy through regular testing across demographic groups and validation against job performance.

Candidate transparency: Be clear about AI usage, provide plain English explanations, establish consent processes, and offer mechanisms for human review and data deletion.

The Owen Daniels Approach

Having provided STEM talent solutions for over a decade, we've seen how technology transforms hiring when implemented thoughtfully. Our compliance services help businesses navigate this landscape through:

Assessment and Strategy: Evaluating technology stacks against compliance requirements
Implementation Support: Deploying AI tools that enhance capability while maintaining compliance
Ongoing Monitoring: Continuous bias and compliance monitoring, similar to our IR35 compliance services
Training: Educating teams on effective, compliant AI tool usage

AI hiring tools offer genuine benefits, but without proper compliance consideration, they expose businesses to significant risks. The question isn't whether to use AI in hiring, it's how to use it compliantly and effectively.