Technical staff with the skills needed for adopting AI are in high demand. This brings a range of challenges for HR managers, similar to any sector where suitably qualified staff are in demand:
- There is a global shortage of experienced AI professionals (such as machine learning engineers, data scientists, and AI architects). Competition is intense, with tech giants and startups alike vying for a limited talent pool, leading to bidding wars.
- Salaries and benefits required for AI talent are often much higher than for other roles. Smaller firms or non-tech organisations may struggle to match compensation packages offered by larger, better-funded companies.
- AI professionals often seek dynamic, innovative, and flexible workplaces. Traditional workplaces must adapt cultures, offer flexible working arrangements, and enable access to new tech and learning to be attractive.
- AI specialists want clear opportunities for skill growth, challenging projects, and professional advancement. If organisations can’t provide ongoing training, exposure to real-world AI problems, and a path for advancement, staff may move elsewhere.
- High demand means AI staff are regularly approached by head-hunters and competitors. Even after hiring, retaining talent is difficult; “job-hopping” is common.
- Some firms are not prepared with the infrastructure, data, or vision for effective AI projects. Skilled staff may get frustrated and leave if their expertise isn’t used meaningfully, or if projects seem directionless.
- AI talent is geographically concentrated, and not all firms can relocate or offer remote work. Organisations outside major hubs struggle to attract talent or convince them to move.
- Companies lacking a strong reputation in AI or innovation may be overlooked by top candidates. Building a brand as an “AI employer of choice” takes time but is essential for attracting talent.
- The AI field suffers from under-representation of women and minorities, shrinking the available talent pool. Attracting diverse AI talent and building inclusive teams is both a challenge and a necessity to avoid groupthink and bias.
- For global talent, complex visa rules and immigration policies can hinder recruitment and retention. Hiring international specialists may be slowed or prevented by regulatory hurdles.
Selamat et (2024) published a study exploring how HR managers are adopting AI themselves to deal with these challenges
They argue that in order to address high turnover and talent challenges, HR managers in hospitality should:
- Embrace eHRM and AI to broaden applicant reach, improve efficiency, and enhance decision-making.
- Focus on person-job and person-organisation fit to boost retention.
- Provide a positive candidate experience with clear communication and modern tools.
- Commit to transparency, staff training, and ongoing evaluation of digital HR strategies.
The adoption of electronic HR management (eHRM) and artificial intelligence (AI) offers tools to address these workforce challenges by automating and improving HR processes, especially recruitment and selection. Therefore, investing in eHRM and AI can give HR a strategic advantage in attracting, assessing, and retaining high-quality talent.
They give examples of this investment can deliver tools to improve recruitment and selection. E-recruitment can expand access to more candidates, including passive job seekers, by leveraging job portals, social media, and digital networks. Automated processes such as CV screening, application status updates via chatbots can make recruitment faster and reduce costs. AI-based assessments can help target applicants whose values and abilities align with organisational culture, increasing retention. AI-powered systems can keep candidates informed, improving their experience and perception of the organisation.
Digital platforms and AI tools like chatbots and algorithmic screening can cast a wider recruitment net, improve efficiency, and personalise communication. For example, online and AI-supported job analysis can quickly define role requirements and KSAs, improving job descriptions and person-job fit. E-selection allows for remote testing and interviews, making the process more convenient and accessible. AI can objectively combine applicant data (test results, interviews, profiles) to support unbiased recruitment.
The authors suggest that AI-enabled hiring has demonstrated positive impacts, including up to 35% reductions in turnover. Higher retention is linked to a better match between employee values/skills and organisational needs (person-job and person-organisation fit). EHRM and AI can help both employees and organisations assess this fit early in the process.
They conclude that modern HR leaders should view technology not as a replacement, but as an enabler for smarter, more strategic talent management.
Further Reading:
Selamat, S. M., Baharuddin, F. N., Hayati, A., Musa, P. M., Beta, R. M. D. M., & Ali, A. (2024). Challenges and Opportunities in the Adoption of AI in Talent Acquisition and Retention. International Journal of Academic Research in Business and Social Sciences, 14(9), 100-104.