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AI job disruption forecasting — Issue 3

As artificial intelligence continues advancing, the role of Executive, Quality Service Management is expected to undergo significant transformation.

Figure 1 shows the automation potential and timeline for key tasks. Data-centric activities like “Analyze data patterns” and “Prepare operational reviews” show high automation potential (up to 80%) with major changes likely between 2025 and 2035. Meanwhile, human-intensive tasks such as “Supervise fieldwork” and “Develop outreach strategies” exhibit much lower potential (5–35%), suggesting these areas will remain more resistant to automation in the near term.

Figure 2 models an Artificial General Intelligence (AGI) disruption scenario, where automation potential rises dramatically across all tasks. Even functions previously considered human-dependent, such as “Manage complaints” and “Coordinate survey logistics”, could see automation rates of 75–90%. In this scenario, the role of the Executive would shift significantly towards oversight, ethical decision-making, and managing AI systems rather than performing traditional operational tasks.

These insights underscore the importance of proactive workforce planning. By recognising the importance of human capabilities like strategic thinking, empathy, and complex stakeholder management, professionals in Quality Service Management can better future-proof their careers against the rapid development of AI.