While some HR jobs are emerging within new workstreams, others are entirely new positions, such as an AI Ethics Leader or HR GPT Designer, who is responsible for creating custom agents.2 These jobs of the future demonstrate that integrating AI into HR is transforming the profession into one that includes a blend of technology and traditional roles to enhance efficiency and strategy.
The Need for Upskilling and Reskilling
As the demand for digital skills continues to surge, businesses now face the unprecedented expectation that every employee, regardless of their role, will soon need a baseline proficiency in AI. This shift is unlike any previous business-wide requirement, and comparable to adopting company values across the board. Investing in workforce development is essential to keep pace with technological changes.
A growing emphasis on continuous learning, upskilling and reskilling programs has enabled companies to better anticipate and manage future skill requirements. Reskilling is gaining more traction than upskilling due to AI-driven role changes, but most organizations aren’t building talent quickly enough to keep pace with these changes. Initiatives for AI-related skills should be targeted and tailored to different roles, such as a C-suite strategy session versus a call center training approach. “Organizations have yet to fully understand the necessary steps for upskilling and reskilling in the context of AI’s impact on specific roles,” adds John McLaughlin, chief commercial officer and partner in Aon’s Health Solutions practice. “A one-size-fits-all approach to interventions in the AI landscape may ultimately be counterproductive.”
Risks and Ethical Considerations
Organizations are currently exercising caution by not solely relying on AI for certain things, such as determining pay ranges and making compensation decisions. Instead, AI serves as a valuable data point that feeds into a primarily human-driven decision-making process, ensuring balanced and fair outcomes. For high-stakes decisions like pay, it is even more important to be transparent about its usage and accuracy, as there is simply less room for error. Documenting its role is especially important when it impacts individual outcomes, as it can help alleviate concerns and justify decisions.
In addition to high-risk use cases, data protection remains a critical concern.3 AI systems require vast amounts of data to function effectively, raising issues around how this data is collected, stored and used. Unregulated use of AI can lead to data breaches and unauthorized access to personal information, necessitating powerful data protection measures. Many employees are also using AI tools independently on their own devices, further complicating the oversight of AI usage.
Internally, AI ethics leaders will lead the charge to ensure that AI is integrated responsibly and ethically. More broadly, governance strategies are also necessary to minimize risks and optimize opportunities. These strategies should be regularly updated to adhere to the evolving regulatory landscape and include clear guidelines and oversight to maintain accountability and fairness.