Defining a new era of leadership for HR as AI trust guardians

As organisations across Asia-Pacific accelerate their adoption of AI, the conversation is rapidly shifting from capability to accountability. This transition took centre stage in the final session of the Asia HR Leaders Live Series, organised by AsiaHRM and supported by HRM Asia, where Nguyen Thuy Ha, Former HR Director and Back-Office Director at VinBigdata, unpacked what it truly means to move beyond technology towards trust and governance in AI-driven human resources.

Opening the session, Rita Tsui, Founder of AsiaHRM, set the tone by highlighting the growing urgency for organisations to not only embrace AI, but to do so responsibly. While AI has become a defining force in reshaping HR functions—from recruitment to performance management—the real challenge, she noted, lies in ensuring that its implementation strengthens, rather than erodes, organisational trust.

Ha’s insights drew heavily from her experience at the intersection of AI, leadership, and organisational transformation. She pointed out that in markets like Vietnam, AI adoption in HR is no longer experimental. Organisations are already deploying AI tools across a wide range of functions, including CV screening, automated interviews, employee chatbots, performance analytics, and workforce predictions. Yet despite this widespread adoption, meaningful integration into daily workflows remains limited.

This disconnect, Ha explained, reflects a broader “reality gap”: while access to AI is expanding rapidly, its depth of use—and impact—remains shallow. Citing internal observations, she noted that although a significant proportion of organisations have experimented with AI, only a small fraction use it consistently in HR operations. The implication is clear: adoption alone does not equate to transformation.

One of the most striking dynamics shaping AI adoption in South-East Asia is what Ha described as a “high trust, low understanding” environment. Employees and organisations are generally open to AI and willing to trust its outputs, yet lack a clear understanding of how these systems work. This imbalance creates significant risk, particularly when AI is used to inform high-stakes decisions such as hiring, promotions, or terminations.

At the core of these risks are three critical areas: ethics, data, and people.

From an ethical standpoint, AI systems are susceptible to bias, often reflecting historical patterns embedded in training data. Ha illustrated this with recruitment scenarios, where AI models trained on past hiring decisions may inadvertently favour candidates from certain backgrounds or institutions, limiting diversity and fairness. Compounding this is the issue of transparency. Many AI systems operate as “black boxes”, leaving employees and candidates uncertain about how decisions are made, which can undermine confidence in HR processes.

Data governance presents another layer of complexity. HR functions inherently manage large volumes of sensitive personal data, and the introduction of AI amplifies concerns around data privacy, security, and compliance. Ha emphasised that organisations often fall into the trap of over-collecting data without a clear purpose, increasing exposure to regulatory and reputational risks—particularly in multi-country operations where data protection laws may vary significantly.

However, the most profound challenges, she argued, stem from people. The fear of job displacement remains a dominant concern as AI automates routine and administrative tasks. At the same time, a more subtle but equally damaging phenomenon is emerging: “silent resistance.” In many workplace cultures in Asia, employees may hesitate to voice concerns or admit a lack of understanding, leading to passive disengagement. This can manifest in minimal system usage, poor data input, or superficial compliance—ultimately undermining the effectiveness of AI initiatives.

Against this backdrop, Ha underscored a critical reframing: AI failures are rarely technological issues. Instead, it is a failure of governance, design, and leadership.

To address this, she outlined the need for a robust AI governance framework that precedes implementation, rather than follows it. Central to this framework is the principle of “human in the loop”, ensuring that critical decisions remain under human oversight, with AI serving as a decision-support tool rather than a decision-maker. Clear accountability structures must also be established to define who is responsible for AI-driven outcomes.

Transparency, she added, should be embedded by design. Employees need a basic understanding of how AI systems function and how decisions are derived. This not only builds trust but also empowers users to engage more meaningfully with the technology.

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Importantly, Ha repositioned HR’s role in the AI era. Rather than being passive adopters, HR leaders must act as data trustees and trust guardians. This means safeguarding employee data, ensuring ethical use, and bridging the gap between technical capabilities and business needs. HR must also take ownership of decision governance, ensuring fairness and consistency in AI-assisted processes.

Equally critical is the need for continuous monitoring and audit. AI systems are not static; they evolve with new data inputs, which means new risks can emerge over time. Regular reviews are essential for identifying biases, ensuring compliance, and maintaining system integrity.

Beyond governance structures, leadership plays a defining role in driving successful AI adoption. Ha stressed the importance of actively listening to employee concerns, even when they are not explicitly voiced. Organisations must create safe channels for feedback, involve employees early in the design and deployment process, and communicate clearly about the purpose and boundaries of AI usage.

Measuring success, she added, requires a shift in perspective. Traditional metrics, such as adoption rates, are insufficient. Instead, organisations should focus on trust-based indicators, including employee sentiment, behavioural patterns, levels of feedback, and the extent to which managers rely on—or override—AI recommendations.

Ultimately, the session reinforced a clear takeaway: the future of HR is not just AI-powered, but trust-powered.

As organisations continue to integrate AI into their people strategies, the true differentiator will not be the sophistication of the technology, but the strength of the governance frameworks and leadership principles that underpin it. In this sense, AI becomes less a test of technical capability and more a test of organisational integrity.

Closing the session, Ha encapsulated this sentiment succinctly: organisations must remain the masters of AI, not the other way around. By designing AI systems with trust at their core, HR leaders have an opportunity not only to enhance efficiency but also to build more transparent, ethical, and human-centric workplaces.

This marks the end of the Asia HR Leaders Live Series, which has provided invaluable insights into the evolving landscape of workforce management. Looking ahead, AsiaHRM will launch a new series titled Sustainability for Business, focusing on how organisations can balance profitability with environmental and social responsibility.

The Sustainability for Business Series will commence on 1 April 2026, featuring Tan Swee Heng, Head Shared Leadership Team Coaching Academy, Leadership in Motion. Participants will explore the four-stage journey of organisational sustainability, learn to identify the hidden risks of a “business as usual” mindset, and discover how to leverage sustainability as a competitive differentiator to create long-term value for their brands.

To register, click here.