The Use of Artificial Intelligence in Job Recruiting and its Legal Risks

Elizabeth Edinger*

The use of artificial intelligence (AI) is inevitable, especially for those in the legal profession. It has been stated that AI has the potential to automate routine tasks and boost productivity for lawyers, saving lawyers up to four hours per week and generating $100,000 in new billable time per lawyer each year.¹ Recently, not only in the legal profession, but throughout employers generally, AI is being utilized to recruit and hire new employees.² Industry estimates predict that 70 percent of companies are using AI-powered hiring platforms to hire their new employees.³

Some notable ways employers have implemented AI into their recruiting processes include resume screening, streamlining the interview process, and predictive analytics.⁴ AI-powered hiring platforms can scan resumes and cover letters to indicate whether an applicant’s qualifications match the company’s desired job description and criteria.⁵ AI-powered hiring platforms streamline the interview process by analyzing an applicant’s speech patterns and non-verbal cues resulting in a more comprehensive analysis of each candidate than a traditional human interview.⁶ Predictive analytics uses prior candidate data to analyze patterns and trends to determine a candidate’s likelihood of success in future positions.⁷ These AI-powered recruitment processes often lead to more efficient recruiting and decision-making by companies and their recruiters.⁸ Thus, the use of AI-powered hiring platforms can create more efficient hiring processes which have many benefits, but there are also legal risks that employers should be made aware of.

Benefits

As a benefit, some individuals argue that the use of AI in recruiting can lead to a more objective view of an applicant, eliminating subjective biases.⁹ Arguably, under this objective approach, an applicant’s “suitability” for a role is based solely on data regarding their expertise, past experience, and potential for growth rather than human tendencies.¹⁰ Accordingly, these systems have the potential to reduce unconscious biases by reducing intentional or unintentional human prejudice from the hiring processes.¹¹

Risks

However, others may argue that AI-powered hiring platforms can increase the risk of discrimination in hiring processes because AI-powered hiring platforms can be trained on “historical hiring data often reflect[ing] existing biases.”¹² For example, in 2015, a company’s recruiting engine was determined to have discriminated against certain applicants based on gender.¹³ The system was discovered to be assigning “lower ratings to resumes that included the word ‘women.’”¹⁴ This recruiting engine was later understood to be trained using primarily male resumes over a period of ten years.¹⁵ Moreover, women applicants were underrepresented and, accordingly, an algorithmic bias developed.¹⁶ Additionally, “[p]oorly worded job descriptions can lead to the exclusion of qualified job candidates, and applicants’ own language can contain cultural biases.”¹⁷

As a result, employers may face the legal risk of discrimination or a violation of federal law including Title VII of the Civil Rights Act when implementing AI-powered recruitment systems.¹⁸ The language of Title VII of the Civil Rights Act states that it shall be unlawful for an employer to “fail or refuse to hire . . . or otherwise discriminate against any individual with respect to his compensation, terms, conditions, or privileges of employment, because of such individual’s race, color, religion, sex, or national origin.”¹⁹ Although employers may not use AI-powered hiring platforms to discriminate intentionally, disparate impact discrimination cases do not have an intent element.²⁰ Thus, as stated in Griggs v. Duke Power Co., where a company required employees to obtain a high school diploma and receive scores on two different aptitude tests to transfer into a higher paying position, “good intent or absence of discriminatory intent” does not negate seemingly neutral employment practices that result in discriminatory consequences.²¹ Thus, employers need to consistently monitor the AI-powered hiring platforms used throughout their employment practices because lack of intent is not a defense.²²

What Can Employers Do?

Moreover, employers must be proactive, vigilant, and cautious when monitoring the outcomes of their AI hiring processes.²³ This may be difficult, however, because often AI-powered hiring platforms are analogous to “black boxes,” “making it difficult or even impossible for recruiters to understand how decisions are made.”²⁴ To avoid unintentional discrimination in hiring practices and excess litigation expenses, employers should be proactive in their approach to using AI-powered recruitment systems.

To start, employers should ensure that their AI-powered recruitment system is trained to be unbiased, transparent, and compliant with all relevant laws, including privacy laws.²⁵ Employers should monitor their systems frequently for any bias, maintain oversight on the system’s outcomes, and intervene when necessary.²⁶ Also, employers should consider implementing training programs for their HR and recruiting professionals to make sure their employees are properly versed on how to use the AI-powered hiring platforms they have implemented effectively and ethically.²⁷

To conclude, the use of AI is inevitable, especially in recruiting where its use can extensively eliminate resources and time to find the best candidate. However, employers have a responsibility to ensure that their systems are being used appropriately and in accordance with employment laws.

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* Elizabeth Edinger, J.D. Candidate, University of St. Thomas School of Law Class of 2026 (Associate Editor).

1. Thomson Reuters, How AI is Transforming the Legal Profession (2025), Thomson Reuters L. Blog (Jan. 16, 2025), https://legal.thomsonreuters.com/blog/how-ai-is-transforming-the-legal-profession/ [https://perma.cc/5ZYE-U67S]. This time is saved through the use of AI-powered tools that perform document reviews, legal research, and contract analysis. Id. ↩︎
2. Travis Whitsitt, The AI Revolution in Legal Recruiting: Using Technology to Identify Top Talent, Vault L. Blog (Feb. 10, 2025), https://vault.com/blogs/vaults-law-blog-legal-careers-and-industry-news/the-ai-revolution-in-legal-recruiting-how-firms-are-using-technology-to-identify-top-talent [https://perma.cc/D64N-Y3AD]. ↩︎
3. How Can Bias Be Removed from Artificial Intelligence-Powered Hiring Platforms?, Harv. Sch. of Eng’g (June 12, 2023), https://seas.harvard.edu/news/2023/06/how-can-bias-be-removed-artificial-intelligence-powered-hiring-platforms [https://perma.cc/8S9D-6UAS]. ↩︎
4. Whitsitt, supra note 2. ↩︎
5. Abby Knowles, The Future of Hiring: The Role of AI in Modern Recruitment Strategies, SHRM (July 28, 2024), https://www.shrm.org/topics-tools/news/technology/the-future-of-hiring–the-role-of-ai-in-modern-recruitment-strat [https://perma.cc/8U6J-TCPQ]. ↩︎
6. Neil Sahota, Hiring Best-Fit Lawyers: Why AI Has Changed the Game on Firm Recruiting, JD Supra Persps. 2025 (Feb. 23, 2024), https://www.jdsupra.com/legalnews/hiring-best-fit-lawyers-why-ai-has-4335131/ [https://perma.cc/2A73-U98Z]. ↩︎
7. Impress AI, How Can Predictive Analysis Transform Your Recruitment Process, Impress AI Blog (Aug. 15, 2024), https://impress.ai/blogs/how-can-predictive-analytics-transform-your-recruitment-process/ [https://perma.cc/KB86-73RF]. ↩︎
8. Sahota, supra note 6. ↩︎
9. Sahota, supra note 6. ↩︎
10. Sahota, supra note 6. ↩︎
11. Sahota, supra note 6. ↩︎
12. Eric H. Rumbaugh & Malin A. Ehrsam, The Legal Risk of Using AI in the Hiring Process, Staffing Indus. Analysts (Oct. 29, 2024), https://www.staffingindustry.com/editorial/cws-30-contingent-workforce-strategies/the-legal-risk-of-using-ai-in-the-hiring-process [https://perma.cc/UAK9-HS72]. ↩︎
13. Allen Garcia, The Continuity of Barriers: How AI Job Recruiters Discriminate,Harv. Tech. Rev. (Sept. 15, 2024), https://harvardtechnologyreview.com/2024/09/15/the-continuity-of-barriers-how-ai-job-recruiters-discriminate/ [https://perma.cc/RR8Q-PF3E]. ↩︎
14. Id. ↩︎
15. Id. ↩︎
16. Id. ↩︎
17. How Can Bias Be Removed from Artificial Intelligence-Powered Hiring Platforms?, supra note 3. ↩︎
18. Rumbaugh & Ehrsam, supra note 12.   ↩︎
19. 42 U.S.C. § 2000e-2(a).   ↩︎
20. Rumbaugh & Ehrsam, supra note 12.  ↩︎
21. Griggs v. Duke Power Co., 401 U.S. 424, 432 (Minn. 1971); Rumbaugh & Ehrsam, supra note 12. ↩︎
22. Griggs v. Duke Power Co., 401 U.S. 424, 432 (Minn. 1971);Rumbaugh & Ehrsam, supra note 12. ↩︎
23. Rumbaugh & Ehrsam, supra note 12. ↩︎
24. Rumbaugh & Ehrsam, supra note 12. ↩︎
25. Sahota, supra note 6.  ↩︎
26. Sahota, supra note 6.  ↩︎
27. Sahota, supra note 6.  ↩︎