How can Generative AI transform HR?
Imagine HR professionals with an AI-powered assistant that streamlines recruitment, maximises employee potential, and fosters a personalised, inclusive workplace. Picture HR managers no longer needing to draft job requirements manually, and an AI assistant acting as a career mentor, guiding employees through their professional journey with questions like: "What jobs align with my aspirations?" and "Who are three role models with similar strengths and weaknesses, and what have they achieved?"
It may sound like something out of a sci-fi movie, but thanks to generative AI.
In an episode of the McKinsey Talks Talent podcast, HR leaders, Bryan Hancock and Bill Schaninger, engage in a thought-provoking conversation with McKinsey’s Lareina Yee and Lucia Rahilly. They delve into the promise and potential pitfalls of harnessing generative AI in HR, which sheds light on how this technology can reshape the future of talent management and how we can prepare for the inevitable.
The impact of generative AI on recruiters
Generative AI can change how hiring works in two important ways, as Bryan explains. It can assist managers in creating clearer job requirements and offer personalised details about candidates. The technology identifies the necessary skills for success in a role, but managers still need to review the final output. It also provides personalised insights on individuals, their fit for a job, and other career options.
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But that's just the tip of the iceberg. Gen AI can transform the very foundation of recruitment by shifting the focus from mere credentials to the measure of an individual's skills. Lareina says, "One thing this technology does extremely well is tagging – the ability to tag unstructured data for words. While many businesses explore its application in e-commerce and diverse retail experiences, the potential extends to talent acquisition and capability search”. Rather than focusing solely on credentials or degrees, organisations can now seek specific keywords that indicate desired capabilities and skills. With gen AI, recruiters can focus on the actual abilities and experiences that make each candidate unique.
Empowering professional growth
Gen AI can empower skill-based transitions, benefiting employers and candidates alike. Individuals with skills but uncertain career prospects rely heavily on managers or mentors to guide them towards nontraditional paths. Individuals can engage with an intelligent chatbot to explore career opportunities, argues Bryan. The chatbot can provide insights like, "Based on your skill profile, most individuals pursue these paths, but some explore A, B, C," with "C" referring to coding. With further inquiry, the chatbot can present a comprehensible job description tailored for non-IT professionals.
Streamlining performance reviews
"I don't want generative AI to generate performance reviews. It requires human involvement, judgement, and empathy," Bryan emphasised. Drawing from his experience as a McKinsey evaluator, he explained the current process of gathering feedback, which involves receiving written feedback through a digital system from 15 to 20 individuals. This feedback encompasses long-form comments, upward feedback scores with commentary and ratings, deployment frequency, and compliance-related measures. But what if there was a way to streamline this process? “I’m excited about that use case because it eliminates a lot of work,” Bryan said.
Transparency is another critical aspect that generative AI can enhance. Employees gain a clearer understanding of their progress, potential career paths, and the factors that contribute to their success. They can explore their potential by finding success models who share similar strengths and weaknesses.
The essential role of human judgement
While the possibilities seem endless, it is essential to address the potential risks and challenges associated with the adoption of generative AI in HR. One crucial consideration is the need for human involvement in decision-making processes, especially in areas where regulations demand it. Generative AI learns from the data it is trained on, and if not carefully managed, this can introduce biases and other risks into the HR process. As Lareina emphasises, “while AI can provide valuable options and suggestions, human judgement and empathy are crucial for making final decisions and ensuring fairness and ethical standards are upheld”.
The true power lies in the fusion of generative AI with human expertise and judgement. Bill Schaninger highlights the importance of consistent data capture and sharing for the successful implementation of generative AI in HR. He emphasises that for the technology to deliver its full potential, organisations must commit to maintaining accurate and comprehensive data.
HR professionals must approach this technology as a productivity aid, a companion that complements their skills and augments their decision-making, according to Bryan. Striking the balance between technology and human touch is crucial. It is important to acknowledge that this tech can be exploited for malicious purposes. “This is where government regulation, policy, and international standards come into play,” says Lareina. Complete reliance on self-regulation within the private sector may not be adequate for addressing these concerns.
Preparing for the future (job displacement)
Lucia Rahilly acknowledges concerns about job displacement and the impact of generative AI assuming managerial roles. Bill suggests promoting learning and experimentation to prepare for these changes. To ensure the human element is not overshadowed, leaders must take proactive steps. Lucia stresses the need for leaders to modernise talent capabilities and guide employees through workforce transformations.
Generative AI stands as a powerful tool that can shape the future of HR and unlock the true potential of every individual. With its capacity to augment human potential, we stand at the precipice of a transformative journey. How we put it to use is the question.