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Amazon Web Services (AWS) recently released its Global Generative AI Adoption Index, based on a survey of 3,739 senior IT decision-makers across nine countries and multiple industries. While the 19-page report includes a range of insights—from AI deployment trends to evolving talent strategies—one point that stood out to me was around change management. Nearly half of the respondent organizations have moved beyond proof-of-concept and are transitioning to production or fully integrating generative AI into workflows. Yet only 14% currently have a change management strategy in place to support adoption—a figure expected to rise to 76% by 2026. As organizations face multiple overlapping changes—not just those related to AI—I believe HR leaders and their teams will need to play an increasingly critical role in addressing change fatigue: when the pace and volume of change exceed employees’ capacity to adapt, leading to performance risks. One suggestion I’d offer is to map all active and proposed change initiatives, identify the most disruptive ones, and assess employees’ ability to absorb the cumulative “change load.” These insights can guide leadership in adjusting the timing, sequencing, or scope of change efforts. Not looking at all changes collectively is like trying to manage a personal financial budget by focusing on just one or two expenses without seeing the full picture; this approach doesn’t reveal whether overall spending is sustainable. The same applies to change—taking a holistic view helps manage the total impact more effectively and increases the likelihood of achieving desired outcomes.
