AI Roles Expand for HR Leaders as Companies Redefine Work
Three major companies have merged HR leadership with AI transformation responsibilities. This shift reflects a broader trend to redefine job roles and workforce capabilities in response to technological advancements.
The rapid advancement of artificial intelligence (AI) is prompting significant shifts in the roles of Human Resources (HR) leaders. In the past year, companies like Atlassian, Moderna, and Lumen Technologies have integrated AI transformation oversight into their HR leadership structures. This move signals a recognition that the most challenging aspect of AI adoption is not the technology itself, but the necessary reimagining of work and the workforce.
Atlassian appointed Avani Prabhakar as its Chief People and AI Enablement Officer in April 2026, expanding her previous HR team leadership to encompass AI transformation across its 14,000 employees. Similarly, biotech firm Moderna merged its HR and IT departments under its chief people officer, now focusing on digital technology, while Lumen Technologies broadened its chief people officer role to include AI enablement.
Traditionally, jobs have served as the fundamental unit of organization. However, AI is disrupting this model by automating or altering specific tasks within job bundles. The World Economic Forum projects that up to 39% of current worker skills could be transformed or obsolete by 2030 due to AI. This uncertainty necessitates a focus on adaptability and learning potential in new hires, rather than solely on traditional credentials or experience.
This evolving landscape requires a strategic shift from merely reducing headcount to redesigning work. Instead of using technology primarily for job cuts, organizations are advised to first identify necessary work, required capabilities, and the optimal combination of human and AI resources. Citigroup, for instance, initiated its restructuring by analyzing processes for automation and redesign before making staffing decisions.
Consequently, performance management practices must also adapt. While speed and output volume have been traditional metrics, AI's capacity for high-volume production diminishes their singular value. Human contributions, such as judgment, direction-setting, and error detection, are becoming increasingly critical. Companies that reward these evolving skills are better positioned for future success.