AI Leaders Prioritise Augmentation Over Replacement
Artificial intelligence (AI) leaders are leveraging technology to enhance the capabilities of skilled employees rather than replace them, according to NTT DATA's '2026 Global AI Report: A Playbook for AI Leaders'. The report identifies 'Expert-first AI' as a defining characteristic of top-performing organisations, stating that these front-runners use AI to amplify the impact of experienced, highly skilled employees rather than to displace them.
Primary Workforce Goal: Augmentation, Not Replacement
The report highlights that AI leaders' primary workforce goal is augmentation. They aim to have skilled, AI-savvy employees with institutional knowledge and a deep understanding of the business focus on higher-value work, with targeted reskilling where needed. This approach contrasts with fears of widespread job displacement, emphasising a collaborative human-AI partnership.
The Rapid Evolution of AI and Agentic AI
The report notes that the rapid evolution of AI is reshaping the nature of work, particularly with the rise of agentic AI. '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,' the report states.
On the changing workplace, the report explains that agentic AI 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.
Workforce of the Future: Collaborative Ecosystems
The report further says, 'As a result, the workforce of the future will comprise collaborative ecosystems where humans define purpose and parameters while agents execute and optimise.' This vision positions AI as a tool for empowerment rather than replacement, enabling employees to focus on strategic and creative tasks.
AI Leaders as AI-Native Enterprises
One of the most striking features identified 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. This structural shift underscores the commitment to augmentation over replacement.
