One year ago, we hosted a roundtable and heard how leaders were leveraging AI in their workflows. There were all sorts of applications that feel second-nature today: Automating notetaking, generating job descriptions, and using AI to personalize outreach.

But the most interesting takeaway was how resistant organizations were to allowing their employees to leverage AI. This creates tension between the risk of unintentionally feeding an AI model with privileged, proprietary data and the potential reward of major efficiency gains, which still weighs heavily on the executive talent space.

While companies have come a long way in the last year, sorting out acceptable use policies and more, talent teams, too, have clear actions to confidently leverage AI throughout their workflow.

1. Ensure AI Use Meets Legal and Regulatory Mandates

GDPR, CCPA, and more recent legislation, such as New York City’s Law 144, present legal challenges for executive search organizations that leverage AI. Companies need to ensure compliance with audit rules, notice requirements, and consent from applicants when using AI in hiring, especially when automated employment decision tools (AEDTs) are leveraged to score, rank, or profile candidates.

  • Action: Complete Checklists for Existing Laws
    Review existing legislation and leverage checklist tools for GDPR, CCPA, NYC144 to ensure compliance.
  • Action: Set Up Alerts
    Monitor for any legislative changes related to AI and executive talent by setting up a news alert with specific keyword strings like “executive search” AND (“AI” OR “artificial intelligence”) AND (“law” OR “regulation” OR “compliance” OR “legislation”).

2. Avoid AI Bias and Discrimination

For candidate scoring, if algorithms are trained on historical data that may reflect past human biases related to hiring or promotion decisions, AI models may perpetuate those biases in a candidate’s score. Certain demographics may receive lower scores even if their qualifications are equivalent to higher-scoring groups, and they may be omitted from searches without much transparency as to why.

  • Action: Implement a Human Oversight Mandate
    Decide which activities, such as shortlisting, ranking, or rejecting candidates, are better handled by humans versus AI. Then, ensure that trained recruiters are involved to review and approve any AI-generated recommendations.
  • Action: Conduct Regular Bias Audits
    Periodically test your AI hiring tools with an audit checklist like this to ensure they are not having a disparate impact on protected demographic groups. You take it one step further and hire a firm to conduct the audit to ensure legal compliance.

3. Establish AI Vendor Trust

While there’s been an explosion in experimentation and early adoption of AI tools in executive search, there is also a high degree of skepticism around how vendors source, process, and store data. Talent leaders are trying to figure out the best way forward to audit existing and new AI technology, the right cadence to do so continuously, and how to adapt processes moving forward.

  • Action: Create a Vendor Questionnaire
    Before even testing a tool, send vendors a detailed questionnaire that covers their data handling policies. Ask whether your data is used to train their models, how it is stored, how data deletion requests are handled, whether the tool has bias mitigation, and if the tool complies with particular legal and regulatory practices. 
  • Action: Request Security Certifications
    Ask for security certifications (e.g., SOC 2 Type II, ISO 27001).

4. Maintain Search Confidentiality

The concern among search professionals is that disclosures about AI and AEDTs will impact confidential searches. Recruiters often do research behind the scenes to gather data on the state of the market and available talent. If you are leveraging AI for any of this research and need to disclose activity to the candidates involved, this undermines the ability to conduct searches confidentially.

  • Action: Develop Recruiter-Specific Training
    Provide in-depth training for the executive talent team on the approved AI tools, the nuances of disclosure requirements under various laws, and how to spot potential AI bias in outputs.
  • Action: Provide Confidentiality Scenarios
    Train recruiters on how to leverage AI for market research without triggering disclosure requirements, such as using aggregated, anonymized data queries.

Conclusion

For executive talent leaders looking to adopt more AI tools into existing workflows, being proactive in addressing key concerns related to legal compliance, bias, vendor security, and confidentiality can greatly increase your confidence in wielding AI responsibly.