3 ways generative AI will transform your people strategy in 2024
As we navigate this pivotal time, we explore three transformations on the horizon that we believe HR and talent leaders should be mindful of in the coming year.
By the end of 2024, AI will be table stakes when it comes to HR technology. Already, almost every human capital management (HCM) vendor is talking about their AI strategy and touting its benefits. HR and talent leaders are on board with this shift but, like many of us, they are still learning how AI can truly benefit us and our work. We predict that in 2024, the use of generative AI in recruitment and retention will hit a tipping point. It’ll be a time when AI is no longer thought of as a novelty tool but rather a critical part of the broader people strategy. As we navigate this pivotal time, we explore three transformations on the horizon that we believe HR and talent leaders should be mindful of in the coming year.
AI will go from automation tool to hiring partner
AI can process a lot more information than the human brain. While we may misremember things, AI doesn’t. It can also find patterns that are difficult for us to pick up. Research shows that nearly 50% of hiring decisions are wrong. It’s not surprising considering that interviews are not always the best predictor of on-the-job success and resumes and references can often feature embellishments. Moreover, employers are also relying on people managers to make the final call on hiring when assessing talent isn’t their full-time job. This means that they’re often not always knowledgeable on what kind of talent the business truly needs.
C-Suite leaders including CHROs have long recognized the pitfalls of the old ways of hiring. With the increasing use of generative AI, we believe many will be looking for more holistic ways of integrating AI into their overall people strategy. This means partnering with AI and thinking of it as an expert consultant who can do a lot more beyond automating resume screens. It can think about hiring for you 24/7, and more importantly, it can help you implement data-driven methods to maximize the chance of hiring candidates who will be successful on the job.
Human decision-making will be valued more, not less
Will the increasing use of generative AI threaten the jobs of internal recruiting teams? This is a common concern from HR and talent leaders, and rightfully so. While there are still many questions around how AI will impact the future of work, when it comes to recruiting and retaining talent, we’ve seen the benefits of how it can replace mundane work and free up human power for more creative, strategic endeavors.
For example, we recently heard from one of our customers that using AI gave their in-house recruiters valuable time back to be able to engage with candidates organically and create a more personalized, better candidate experience. Recruiters were able to jump on more candidate calls to better understand what candidates were looking for, leading to an increase in offer-acceptance rates.
In the new year, we believe more business leaders will see that the rise of AI is about human and technology partnership. More leaders will invest in generative AI with the mindset that it helps their people work better and build more effective and efficient teams. For HR and talent leaders, that means finding AI technology that can integrate seamlessly into their existing workflows to help them deduce massive quantities of data and find patterns that they may otherwise miss.
More HR and talent leaders will leverage AI to demonstrate impact
During the economic downturn of 2023, many businesses made the tough decision to cut back on their internal recruiting teams as hiring slowed. In the new year, recruiting teams will likely turn to AI to demonstrate the impact that they have on the bottom line of a business, thereby future-proofing themselves from tough economic times. For example, AI can predict which talent profiles and skills drive business outcomes like quota attainment, retention, and quality of hire. Recruiters and talent leaders can then become stewards of this data and the most well-equipped to attract, engage, and bring these skills into the business.
Related: The truth about AI’s impact on the global workforce
Ultimately, AI used for talent intelligence can help HR and talent leaders quantify the value they bring to an organization and make data-driven recommendations for hiring. By doing so, the value of talent acquisition skyrockets within an organization and smaller recruiting teams are able to do more with less.
In 2024, as AI evolves from an automation tool to a strategic hiring partner, organizations are poised for a paradigm shift in talent acquisition and retention. This integration not only enhances traditional processes but also empowers decision-makers with data-driven insights, significantly improving the accuracy of hiring choices. Contrary to fears of job displacement, generative AI amplifies human decision-making, freeing internal recruiting teams to focus on creative and strategic endeavors. Amidst economic uncertainties, HR and talent leaders are also turning to AI to showcase the impact of their efforts on the bottom line, leveraging talent intelligence to make compelling, data-driven hiring recommendations and positioning recruiting teams for success in resource-constrained environments. This AI-driven era not only redefines people strategies but equips organizations to navigate the future with resilience and foresight.
Anna Wang is the co-founder and CTO of Searchlight, which brings together AI and behavioral science to help companies hire the right person in every role. Anna leads product, software engineering, and AI initiatives to help companies reliably predict quality of hire. Anna received her undergraduate and master’s degrees from Stanford in computer science and artificial intelligence. While at Stanford, Anna was a co-lecturer in Artificial Intelligence and Ethics.
Kerry Wang is the cofounder and CEO of Searchlight. Kerry is a Forbes 30 Under 30 honoree, member of the Future of Talent Acquisition Advisory Council, and Stanford graduate in Org Behavior and Computer Science.