AI in Talent Acquisition: Applications, Risks & Strategy

Question 1

Analyse the current applications of AI in talent acquisition (e.g., résumé screening, chatbots, video interview analysis, candidate matching, predictive analytics). Select 4 applications to analyse. (300-350 words)

(20 marks)

Question 2

Evaluate the benefits and risks of using AI in talent acquisition. (750 – 800 words)

(20 marks)

Question 3

Research two case studies of a real, existing company using AI in talent acquisition. Analyse its implementation, effectiveness, and challenges. In your answer, do also appraise how the use of AI fulfils or does not fulfil the needs of the organisation. (15 marks for each company) (950-1100 words)

(30 marks)

Question 4

Create a Talent Management System guide that integrates the use of AI across the employee lifecycle, with a specific focus on Talent Acquisition.

Your guide should address the following:

1. Talent Acquisition

• How AI can be used to source, screen, and select candidates.
• Ethical issues and risks associated with AI in hiring (e.g., bias, transparency, data privacy).
• Strategies to ensure fairness, accountability, and candidate experience.

2. Integration Across the Talent Lifecycle

• Briefly outline how the talent acquisition process links to other HR functions such as onboarding, learning and development, performance management, and succession planning.
• Where appropriate, highlight how AI tools can support these processes and what challenges or limitations may arise.

3. System Design Considerations

• Design principles (e.g., inclusivity, transparency, data governance)
• Human-AI collaboration: What decisions should remain human-led?
• Change management: How would you engage employees and leaders in adopting AI tools responsibly?

4. Your Recommendations

• Summarise key recommendations for HR teams looking to implement AI in their talent management system.
• Consider ethical, strategic, and operational aspects.

You will be assessed on:

1. Depth of analysis and critical thinking
2. Practicality & relevance to HR practice
3. Design principles & implementation considerations

(Max 1200 words) (15 marks)

Question 5

Construct a competencies framework for a talent acquisition manager who needs to use AI for talent acquisition. The competencies/qualities should be relevant for a talent acquisition manager who needs to utilise AI for talent acquisition. Please list 3 competencies. For each competency, list 3 behavioural indicators that go with the competency. (500 words).

(15 marks)

HRM Assignment Answers: Expert Answer on Talent Acquisition Case Study

Current application of AI in talent acquisition

AI is highly used in performing all business activities including the HRM roles like talent acquisition. The four important AI applications in performing talent acquisition are identified in the areas including resume screening, chatbots to answer candidate queries, video interview analysis, and performing predictive analytics and candidate matching.
The benefits of using AI in talent acquisition includes reduction in time to hire new candidates and it also improves efficiency. However the limitations include overreliance on technology and lack of human touch may affect decisions.

Benefits and risks of using AI

In terms of benefit, AI enhances efficiency and data driven decisions are always good in making the best possible decision. AI also benefits in terms of scalability as it can handle large volumes of data and it also enhances the experience of candidates through personalised interaction. In terms of risks, it includes biases in the form of algorithm bias, issues with transparency and data privacy, and since it makes the entire process easier, it leads to over reliance on AI.
The effective mitigation can be possible through including human elements along with AI implementation, and regular audit of AI tools.

Case studies of real companies using AI in talent acquisition

The two companies selected are Unilever and IBM. Both these companies have utilised AI in performing the Talent acquisition, as Unilever used AI for resume screening and predictive hiring whereas IBM utilised it for talent matching and predictive analytics. Unilever benefited from it in terms of reduction in hiring time, and IBM benefited in terms of optimised sourcing and improved employee retention. The challenge faced by Unilever is in terms of addressing the concerns of candidates with respect to AI evaluation whereas IBM faced challenges in integrating AI with Legacy HR system.

Talent management system guide

In performing the management of talent using AI, it is important to make adequate consideration for ethical issues and mitigation through human oversight. The integration should be performed across the life cycle including on boarding, learning and development, performance management and succession planning. It is also important to make system design considerations such as proper compatibility with the existing systems, and adequate training to deal with issues of employee resistance.

Competency framework for AI talent acquisition manager

The three important competencies required on the part of hR manager in using AI for talent acquisition are data driven decision making, ethical and inclusive hiring, and technology adoption and management.

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