The prevailing narrative surrounding artificial intelligence in the workplace often posits a future where enhanced AI capabilities diminish the need for human judgment. However, this perspective is increasingly being challenged by industry leaders who argue for a fundamental shift in understanding. Tan Toi Chia, Chief of People, Organization, and Communications at Singaporean telecommunications giant StarHub, is a prominent voice in this counter-narrative, asserting that as AI streamlines execution, human judgment becomes not less, but more, critical.
"As AI makes execution easier, the real differentiator becomes judgment—knowing when to trust AI, when to challenge it, and how to apply context," Tan articulated in a recent discussion on the evolving nature of work. This assertion stems from a logical progression: when the cost of producing an output plummets due to AI automation, the scarcity shifts to the discerning decisions about what to do with that output. While AI excels at drafting, summarizing, and generating content at an unprecedented scale, it lacks the nuanced understanding required to determine if a particular result is appropriate for a specific situation, customer, or moment in time. "AI can generate outputs, but judgment, context, and accountability remain fundamentally human," Tan emphasized.
This paradigm shift has led StarHub to sharpen its focus on two core human attributes: curiosity and agency. Curiosity, as defined by Tan, is the engine that drives individuals to question existing assumptions, explore novel possibilities, and engage in continuous learning. Agency, on the other hand, represents the proactive willingness of individuals to take ownership and actively shape outcomes, rather than passively awaiting directives. These qualities are not merely aspirational; they are becoming foundational to navigating an AI-augmented professional landscape.
The Global Landscape of Evolving Skills
StarHub’s emphasis on these human-centric attributes is echoed globally. The World Economic Forum’s "Future of Jobs Report 2025," a comprehensive analysis drawing on insights from over 1,000 employers worldwide, corroborates this trend. The report identifies curiosity and lifelong learning as skills projected to experience the most significant rise in importance by 2030, alongside creative thinking, resilience, flexibility, and agility. Crucially, the report forecasts that approximately 39% of employees’ core skills will undergo transformation within the same timeframe, underscoring the imperative for continuous adaptation.
For Tan, the elevation of these traits carries a significant corollary for organizational reward systems. As AI empowers every employee with enhanced capabilities, a corresponding growth in responsibility becomes inevitable. An individual who can now accomplish in hours what once took days is also the person ultimately accountable for the strategic deployment and ethical implications of that output. This necessitates a recalibration of how performance is measured and recognized.
The challenge of quantifying attributes like judgment, which do not always manifest neatly in traditional output metrics, is a recognized hurdle. StarHub’s response has been to broaden its evaluation framework. "We’re placing greater emphasis not just on what people deliver, but how they think, collaborate, exercise judgment, and create value," Tan explained. This holistic approach acknowledges that true value creation in an AI-enabled future lies beyond mere task completion.
Redefining Roles: From Tasks to Outcomes
A fundamental transformation underway at StarHub, and increasingly across forward-thinking organizations, is a redefinition of how work itself is conceptualized. Instead of defining roles by the specific tasks an individual performs, the focus is shifting towards the outcomes they are accountable for. This distinction is critical because tasks are precisely the elements AI is most adept at absorbing, while outcomes remain the domain where human ingenuity and decision-making are indispensable.
While functional expertise continues to be valued, StarHub is actively cultivating capabilities that are transferable across diverse roles, teams, and business challenges. This approach moves away from preparing individuals for narrowly defined, static jobs towards building a more agile and adaptable workforce.
Customer-facing roles provide a clear illustration of this evolution. Employees in these positions are spending less time on routine information retrieval and more time engaged in resolving complex customer issues, fostering deeper relationships, and exercising discretionary judgment. "The opportunity isn’t simply to make work more efficient," Tan stated. "It’s to free people to solve more complex problems, build stronger relationships, and contribute in higher-value ways." This perspective reframes AI not as a replacement for human effort, but as a catalyst for elevating human contribution.
However, Tan is careful to temper overly optimistic visions of employees effortlessly "gliding up the value chain." He acknowledges that the transition to higher-judgment work is not an automatic consequence of AI access. "Moving up the value chain doesn’t happen simply because people have access to AI," he cautioned. "It happens when organizations redesign how work happens and intentionally build new capabilities." This emphasizes the organizational responsibility in facilitating employee development and career progression in the age of AI.
StarHub’s strategy is anchored in capability building rather than mere tool adoption. This philosophy is encapsulated in "The StarHub Way," a set of behaviors that encourage curiosity, ownership, responsible experimentation, and continuous learning. Tan argues that these behaviors are even more critical in an AI-enabled environment, where technology can provide answers, but humans remain ultimately accountable for the decisions made based on those answers.
The ultimate objective, as articulated by Tan, is not to transform every employee into an AI expert. Instead, the goal is to cultivate a workforce adept at critically evaluating AI-generated outputs, applying relevant context, and exercising sound judgment responsibly. This reframes the traditional upskilling agenda, shifting the priority from technical AI proficiency to what can be termed "critical AI literacy"—the ability to discern the reliability, accuracy, and appropriateness of AI-generated information.
The Long View: Work Design as the Strategic Imperative
Looking beyond the immediate hype surrounding AI, towards a three-to-five-year horizon, Tan envisions a future where AI seamlessly integrates into the fabric of daily work, becoming as ubiquitous and invisible as email or search engines. In this mature state of augmentation, routine administrative tasks, preliminary content generation, and initial research will be fully automated. The work that remains, and indeed the work that will drive enterprise performance, will be centered on distinctly human capabilities: empathy, strategic creativity, sophisticated relationship management, and nuanced decision-making.
"What many organizations underestimate is that this isn’t primarily a technology transformation. It’s a work design transformation," Tan concluded. "Technology scales quickly. People and capability don’t." He further highlighted that many of the most valuable organizational assets, such as judgment, trust, and collaboration, are not easily quantifiable on a balance sheet. However, their absence has a palpable and immediate negative impact on customer satisfaction and overall business performance.
When enterprise systems falter or output errors erode client trust, the root cause is seldom the underlying algorithm itself. More often, it is a failure in human oversight, a breakdown in the application of context, or a deficiency in critical judgment. As organizations navigate this evolving professional landscape, those that solely focus on procuring the latest AI software risk plateauing. The organizations poised for sustained success will be those that approach AI integration as a fundamental work design transformation, investing deeply in the judgment, agency, and accountability of their human capital. This strategic focus on human capabilities, rather than solely on technological adoption, will be the true differentiator in the AI-powered workplace of tomorrow.
