09 Mar AI and Talent Management
Competition for attracting top talent is growing fiercer, and between the Great Resignation and more recent trends such as Quiet Quitting, traditional recruitment approaches are falling short in a fiercely competitive market.
With digital transformation and innovation initiatives shaping a post-pandemic modern workplace, traditional recruitment approaches are not quite cutting it and hiring managers are turning to artificial intelligence (AI) to improve recruitment practices.
Applying AI to assess human competencies and characteristics, however, doesn’t come without its fair share of controversy.
How can AI help Talent Management?
AI tools and insights can help hiring managers and recruiters to sift through larger volumes of resumes quicker, review cover letters, and even conduct virtual interviews*.
If the criteria against which an AI tool is measuring candidates is diverse, demographically unbiased and if the algorithms are specifically set up to reduce bias, predictions of candidate performance potential can be improved. Unlike traditional recruitment practices, such as referrals, CV screening, and in-person interviews, AI can find patterns which might be missed by the human eye.
Considering the above, the potential for AI to mitigate prejudice and increase diversity and socio-economic inclusion could be better than if done by its counterpart human recruiters.
* We strongly recommend that the human-element isn’t completely excluded from the interview process. It’s important to consider what the perceived experience of the candidate might be and to not compromise on providing the best possible experience.
Where does AI fall short?
While AI has the potential to mitigate and reduce bias, it can also bring new complexities into the hiring process if the criteria it uses to assess candidates against has not been properly vetted.
If the criteria is biased (e.g. a dataset is modelled after a similar high performing group of people with similar genders, cultural backgrounds and competencies) AI could exacerbate the problem of biased hiring and homogeneity in organisations.
Also for consideration are candidates who meet most of the criteria but are not a 100% match. These candidates will likely be rejected or excluded from the AI tool’s pool of candidates. For this reason, data ranges as opposed to set data should be considered.
Another shortfall of how AI can be applied is in conducting candidate interviews. Here, candidates are invited to have a conversation with a chatbot programmed to ask questions to assess values and behaviours. While these are crucial components to consider when making hiring decisions, other factors such as personality traits, attitude and nonverbal cues cannot be gauged in the same way as in a person-to-person interview.
Should AI be integrated into Talent Management practices?
There are definite benefits of integrating AI into talent management practices, as long as debiased algorithms and diverse datasets are never compromised on, and the principles and practices which favour quality, always over quantity are prescribed.
Removing bias from AI might not be an easy feat, but perhaps it is more viable than removing it from humans themselves. As for the question of the role of the recruiter and if this is at risk of being replaced by AI, only time will tell, but for the most part we believe there is great potential for a synergetic leveraging from where the other might fall short.
- Research Roundup: How Technology Is Transforming Work (hbr.org)
- Where AI Can — and Can’t — Help Talent Management (hbr.org)
- How AI Can Support Talent Acquisition Efforts (reworked.co)
- Smart HR: How AI is Transforming Talent Acquisition (techopedia.com)
- AI in recruitment: How technology will change the recruiter role | ROCK