Artificial Intelligence (AI) is up ending the recruitment business model, automating everything from sourcing and screening to candidate engagement and assessment. However, as we saw in Part 1 organisations embracing these tools must also navigate an increasingly complex web of regulations and ethical standards. The use of AI in recruitment significantly impacts compliance with laws and standards, introducing both opportunities and additional risks and complexities.
So how is AI being used in recruitment and what are the benefits?
Perhaps unsurprisingly AI is automating and enhancing nearly every stage of the hiring process. Key use cases include:
- Sourcing and Outreach: AI tools can scan vast numbers of social profiles and job boards to identify both passive and active candidates based on criteria like job title, location, and experience. They also enable personalised outreach by tailoring messages and employee value propositions to individual candidates, increasing engagement and expanding the talent pool.
- Screening and Matching: AI-powered software can automate the screening of CVs and applications, ranking and shortlisting candidates by matching their skills and experience to job requirements. This speeds up the process and can revisit previous applicants for new roles, providing more opportunities for candidates and reducing manual workload for recruiters.
- Candidate Engagement: AI-driven chatbots handle initial candidate interactions, answer FAQs, schedule interviews, and conduct pre-screening assessments. This improves the candidate experience by providing instant responses and keeps recruiters focused on higher-value tasks.
- Interview and Assessment: AI-based video interview platforms can analyse candidates’ word choices, speech patterns, and even facial expressions to help assess suitability for the role and fit to company culture.
- Job Description and Content Creation: Generative AI (GenAI) can write inclusive, bias-free job descriptions and generate personalised outreach messages used in search and selection, ensuring clarity and alignment with company values and goals.
- Predictive Analytics: AI can analyse historical hiring data to predict which candidates are most likely to succeed, assess cultural fit, and suggest areas for upskilling, supporting more informed hiring decisions.
- Reducing Bias: By focusing on objective skills and experience rather than demographic factors, AI can help to reduce unconscious bias in candidate selection, promoting fairer and more diverse hiring.
- Promoting Internal Recruitment: AI can facilitate promotions and transfers by analysing internal data, such as employee assessments, to identify current staff who fit open roles. Many organisations prefer to fill roles internally first reducing the cost of external recruitment and retaining talent.
Industry leading giants like Unilever and L’Oréal have successfully implemented AI in recruitment, achieving faster hiring, increased diversity, and improved candidate engagement.
So what’s the catch?
The use of AI in recruitment can significantly impact your ability to comply with existing regulations and standards as well as introducing new and unexpected risks. When using AI in recruitment organisations must navigate a complex legal landscape that includes data protection, anti-discrimination, and emerging AI-specific regulations.
Key compliance considerations when using AI in recruitment include:
- Data Protection: Regulations like the GDPR (EU/UK) and CCPA (US) require lawful collection and processing of candidate data. This means organisations must identify an appropriate legal basis for processing, minimise data collection, and ensure candidates can exercise their rights (such as access, rectification, and deletion). This is less visible and more difficult to control when the AI is gathering and processing the data.
- Transparency: Employers must clearly inform candidates about how AI is used in the recruitment process, what data is collected, and how decisions are made. Many current AI tools lack sufficient transparency, which can lead to non-compliance and erode candidate trust.
- Fairness and Anti-Discrimination: AI systems must be designed and monitored to prevent bias and discrimination. Laws such as the UK Equality Act 2010, US Civil Rights Act 1964, and EU directives require fairness in automated decision-making. Audits have found that some AI tools can inadvertently filter out candidates based on protected characteristics, highlighting the need for careful oversight and regular bias testing.
- Human Oversight: Many regulations require that candidates have the right to human intervention in automated decisions, the ability to contest outcomes, or express their viewpoint. This ensures that AI does not make unchecked, potentially unfair decisions.
- Audit and Accountability: Regular audits and impact assessments (such as Data Protection Impact Assessments under GDPR) are essential to identify and mitigate risks. New laws, like the EU AI Act and even local regulations (e.g., New York City’s Local Law 144), are introducing mandatory audits and stricter oversight for AI in recruitment.
- Emerging AI Regulations: The regulatory landscape is evolving, with new frameworks like the EU AI Act and the US AI Bill of Rights introducing additional compliance requirements, especially for higher-risk AI systems used in recruitment.
Practical steps for keeping your AI compliant:
So how can you respond to these additional challenges ensuring you retain the benefits of AI in recruitment without falling foul of any new traps. Here are some simple practical principles to adopt and associated key questions to ask:
- Conduct regular audits and impact assessments – how are the AI tools performing? What results are they generating? Are they delivering the benefits we hoped for?
- Ensure transparency and clear communication with candidates – where AI driven decisions are being made how do we ensure the reasoning is available, understandable and suitable to be shared externally?
- Monitor and test AI tools for bias and accuracy – Where have issues arisen and why? Can we benchmark the AI tool against a human recruitment expert?
- Limit data collection and retention – What data is the AI tool accessing and where is it coming from? What new data is it actually creating? Where is data being stored and processed and for how long?
- Provide mechanisms for human review of automated decisions – How to ensure that your recruitment process still has humans in the loop at critical points to provide regular checks and balances before things go external and beyond your control?
Compliance Control – using the right tools?
We’ve considered how AI in recruitment can improve efficiency in the search, sift and selection process. We’ve also seen how use of AI tools also introduces significant compliance challenges for recruiters.
Organisations must proactively address data protection, fairness, transparency, and human oversight to comply with current and emerging regulations.
It’s a lot to stay on top of in such a rapidly evolving space. This is where process management and compliance tools like Maly’s Okuda platform can play a role again.
By putting in place a structured, consistent, digital approach across the organisation, one that helps you ask the right questions at the right time to the right people (and to capture their answers for audit purposes) you can minimise the risk of AI behaving in unexpected and undesirable ways.
This approach will certainly help you to maximise the benefits of AI in terms of speed, efficiency, and reach to find the very best candidates and to avoid pitfalls.