AI leaders are using technology to strengthen skilled employees rather than replace them, says NTT DATA’s 2026 Global AI Report. This “augmentation, not replacement” approach, termed “Expert-first AI”, aims to amplify the impact of experts.
Artificial intelligence (AI) leaders are using the technology to strengthen the capabilities of skilled employees rather than replace them, according to NTT DATA’s “2026 Global AI Report: A Playbook for AI Leaders”, which says the primary workforce goal among top-performing organisations is “augmentation, not replacement”.
Expert-First AI: Augmentation Over Replacement
The report identifies “Expert-first AI” as one of the defining characteristics of AI leaders, saying, “these front-runners use AI to amplify the impact of experienced, highly skilled employees rather than to replace them.”
According to the global AI report, “AI leaders’ primary workforce goal is augmentation, not replacement. They want skilled, AI-savvy employees with institutional knowledge and a deep understanding of the business to focus on higher-value work, with targeted reskilling where needed.”
The report added that the rapid evolution of AI is reshaping the nature of work, particularly with the rise of agentic AI. It said, “Every technology revolution is also a human one. AI is no different in this regard, but it’s progressing a lot faster. Where previous transformations have advanced over decades, this one is unfolding in years.”
Agentic AI and the Future Workplace
On the changing workplace, the report said, “Agentic AI, in particular, is redefining human work. Instead of job descriptions, organisations will define roles in terms of decision loops: data intake, interpretation, action and evaluation. Some loops will be fully automated; others will remain hybrid, with human oversight.”
It further said, “As a result, the workforce of the future will comprise collaborative ecosystems where humans define purpose and parameters while agents execute and optimise.”
The Structure of AI-Native Enterprises
The report further said, “One of the most striking features is how AI leaders are structured. They increasingly operate as AI-native enterprises where workflows are redesigned, governance is centralised, infrastructure is secure and scalable, and expert talent is empowered, not displaced.” (ANI)
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