AI in Recruitment: Transforming the Future of Hiring in Aged Care

Given the growing demand for staff in the aged care sector, finding the right candidates to fulfil care requirements is an ongoing challenge. Aged care providers are often competing for staff with other sectors, and may need to rely on agencies to fill gaps in their workforce. In addition to these challenges, the recruitment landscape is changing and technology has had a huge impact on the way we can identify and onboard talent. This article explores some of the opportunities (and challenges) created by Artificial Intelligence in recruitment, and what this means for the aged care sector. 

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The Current AI Revolution in Recruitment

Artificial intelligence is fundamentally transforming recruitment practices, with 87% of organisations now using AI at some point in the hiring process (Bartram, 2025). This represents a massive shift from traditional recruitment methods, with 67% of hiring leaders citing time savings as AI’s primary benefit (Bartram, 2025). According to research by BCG, 70% of companies experimenting with AI or GenAI are doing so within HR, with talent acquisition being the top use case (Boston Consulting Group, 2025).

The impact is already measurable: 92% of firms report seeing benefits from AI in recruitment, with more than 10% reporting productivity gains of over 30% (Boston Consulting Group, 2025). AI adoption saves recruiters and hiring teams up to 17 hours weekly, with one-quarter of that time saved on candidate matching alone (Bullhorn, 2025). 

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Most Common Use Cases for AI in Recruitment

Content Creation and Administrative Tasks

WIth AI’s ability to automate repeatable tasks, the most popular applications of this technology in recruitment include content creation (writing job descriptions, marketing emails, assessments) and administrative tasks (scheduling interviews), with 70% of companies surveyed already using AI in some way for these purposes (Boston Consulting Group, 2025).

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Efficiency and Speed Improvements

By automating these activities, AI can dramatically accelerate hiring timelines. Companies report Time-to-Fill improvements of 8-10%, with some organisations seeing 4-day reductions in Time-to-Fill (The Access Group, 2025).

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Enhanced Candidate Experience

AI-assisted messaging, which aims to keep candidates engaged through the recruitment lifecycle by automating regular communication, has been found to increase the likelihood of a quality hire by 9% compared to traditional methods (Tracker RMS, 2023). However, maintaining a positive candidate experience remains pivotal, as candidates can be put off by a process that lacks human involvement.

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Challenges Specific to Implementing AI Technology

Change Management and Acceptance

A recent study from Melbourne Business School and KPMG found that Australia is one of the most hesitant countries globally in trust towards AI. The study found Australia has the lowest score of any country surveyed in believing that the benefits of AI outweigh the risks and among the lowest on measures such as acceptance, excitement and optimism towards AI (Gillespie et al, 2025). This creates a barrier to implementing AI as employees and companies are reluctant to adopt this new technology.

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A major challenge in implementing AI for recruitment is overcoming this resistance and unfamiliarity. Given the previously referenced sentiment in Australia, recruitment teams may lack the knowledge and resources to evaluate and integrate AI tools effectively, resulting in slow adoption and limited benefit realisation.

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Established professionals may be hesitant, concerned about job security or sceptical of AI’s ability to match their intuitive candidate assessment skills. Without clear change management—including staff training, open communication, and gradual rollout—organisations risk internal friction and underperformance of the tools implemented. This challenge is heightened by the rapid pace of AI developments, demanding ongoing learning in addition to regular workloads.

 

Discrimination Concerns in AI Recruitment

Recent Australian research found that 62% of organisations used AI tools in their recruitment processes, yet these systems may inadvertently discriminate against candidates, particularly those from marginalised communities (Charity, 2025). A University of Melbourne study found that the way AI hiring systems are used in practice creates serious risks of discrimination (Sheard, 2025).

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This is particularly concerning for industries such as aged care, where many workers identify as having English as a second language. AI systems have demonstrated concerning bias patterns, often struggling to fairly assess candidates from diverse linguistic backgrounds (Serra, 2023). This is in part due to the data on which they are trained consisting of predominantly English language resumes/candidates.

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Determining Cultural Fit: The Need for Human Involvement

Identifying the right fit between an organisation’s culture and a new employee is a critical component in staff retention. Currently, AI lacks the nuanced understanding required to assess interpersonal skills or determine cultural fit effectively (Faraj, 2024).

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The most successful recruitment processes combine AI efficiency with human insight, ensuring that while administrative tasks are streamlined, the crucial elements of relationship building and cultural assessment remain in human hands. This is particularly important in the context of aged care given the underlying importance of finding staff to deliver quality care to residents. 

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Recommendations for Implementation​

For aged care providers looking to implement AI in their recruitment process, we recommend:

• Maintain Human Oversight: Ensure that AI tools augment rather than replace human decision-making, particularly in final candidate selection and cultural fit assessment.

• Monitor for Bias: Regularly audit AI systems for discriminatory patterns, especially when recruiting candidates from diverse backgrounds or those with English as a second language.

• Prioritise Candidate Experience: Use AI to improve efficiency whilst maintaining personal touch points that help candidates understand your organisation's culture and values.

• Start Small: Begin with administrative tasks and gradually expand AI usage as your team becomes comfortable with the technology and its limitations. Small use cases will also breed familiarity, which will in turn help teams identify new or additional use cases. 

• Stay Compliant: Ensure all AI recruitment tools comply with Australian anti-discrimination laws and provide transparency about how AI is used in your hiring process.

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Conclusion

AI in recruitment offers significant opportunities for improved efficiency and better candidate matching. However, successful implementation requires careful attention to change management, bias mitigation, human oversight, and maintaining the human elements that are crucial for cultural fit assessment.

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The future of recruitment lies not in replacing human judgement with AI, but in creating powerful partnerships between human expertise and artificial intelligence that enhance both candidate experience and hiring outcomes whilst preserving the relationship-building and cultural assessment that remain uniquely human strengths. Harnessing the benefits of AI in talent identification and hiring can be advantageous for aged care providers who are constantly grappling with workforce shortages.

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References 

• Bartram, Finn, “Recruitment Process Automation: 15 Methods + Best Practices”, (People Managing People, 30 January 2025), <https://peoplemanagingpeople.com/recruitment/recruiting-process-automation/> 

• Boston Consulting Group, “How AI Tools Are Changing Recruitment”, (15 January 2025), <www.bcg.com/publications/2025/ai-changing-recruitment> 

• Bullhorn AU, “Recruitment Agencies Using AI Are Twice as Likely to Have Increased Revenue”, (26 February 2025), <www.bullhorn.com/au/news-and-press/press-releases/recruitment-agencies-using-ai-are-twice-as-likely-to-have-increased-revenue/> 

• Charity, Kelly, “AI Hiring And Bias Reviews in Australia: What You Must Know”, (The Recruitment People, 27 May 2025), <https://therecruitmentpeople.com.au/ai-hiring-bias-australia-recruitment-2025/> 

• Faraj, AJ, “Understanding the Limits of AI for Recruiting”, (Staffing Industry Analysts, 6 December 2024), <www.staffingindustry.com/editorial/staffing-stream/understanding-the-limits-of-ai-for-recruiting> 

• Gillespie, Nicole, Lockey, Steven, Ward, Tabi, Macdade, Alexandria, & Hassed, Gerard, “Trust, attitudes and use of artificial intelligence: A global study 2025” (2025) The University of Melbourne and KPMG <https://figshare.unimelb.edu.au/articles/report/Trust_attitudes_and_use_of_artificial_intelligence_A_global_study_2025/28822919?file=54013232> 

• Serra, Barbara, “Artificial Intelligence’s Second Language”, <https://barbaraserra.substack.com/p/artificial-intelligences-second-language> 

• Sheard, Natalie, "Discrimination by Recruitment Algorithms Is a Real Problem", (University of Melbourne - Pursuit, 15 May 2025), <https://pursuit.unimelb.edu.au/articles/discrimination-by-recruitment-algorithms-is-a-real-problem> 

• The Access Group, "The Future of Recruitment: How AI Is Transforming Recruitment Agencies in Australia", (13 June 2025), <www.theaccessgroup.com/en-au/blog/rec-the-future-of-recruitment-how-ai-is-transforming-recruitment-agencies-in-australia/> 

• Tracker RMS, "The Challenges Recruiters Must Know When Implementing Automation", (3 September 2023), <www.tracker-rms.com/blog/the-challenges-recruiters-must-know-when-implementing-automation/>