InteracTech Asia 2026: What HR Leaders Must Know About AI in the Workplace
HR and technology leaders gathered on 20 May 2026 at InteracTech Asia to discuss how artificial intelligence is reshaping talent management, leadership, and organisational design. The conference surfaced six core lessons for HR professionals navigating an AI-enabled workplace.
Deployment is Not the Same as Adoption
Rolling out AI tools is only the first step. Organisations must build genuine adoption, change behaviour, and absorb AI into how teams work, make decisions, and collaborate.
Josh Skorupa, Head of Digital Transformation at GovTech, described the gap between deployment pressure and organisational readiness. Most organisations are "very good at generating AI activity," he said, but "not consistently good at generating organisational adoption."
Skorupa outlined three requirements for real adoption: understanding how AI reshapes conversations around specific tasks; recognising how AI participation influences wider operational decisions; and acknowledging that organisational challenges stem from interconnected systems, not isolated task improvements.
Focus on Judgment, Not Just Tasks
As AI automates routine work, the critical skill becomes decision-making. HR leaders must pay closer attention to how employees apply context, exercise accountability, and make judgments in AI-supported environments.
Sujay Bhat, Senior Director of HR Strategy Advisory at SAP SuccessFactors, framed this as a choice between two paths: a "default" approach focused on productivity gains, and a "transformational" approach that uses AI to solve previously unsolved problems and redesign how work happens.
In the transformational view, AI acts as a catalyst for human agency-enabling people to become better versions of themselves rather than replacing their judgment. In the default view, AI becomes a "negative multiplier, because people stop thinking."
AI Should Drive Transformation, Not Just Efficiency
Many organisations begin with efficiency gains. The greater opportunity lies in redesigning work, solving complex problems, and creating value that was not previously possible.
Bhat cautioned that treating AI as an "AI buddy" integrated into workflows as a peer can backfire if it reduces human thinking. The transformational approach positions AI as enabling human capability, not replacing it.
Human Judgment Remains Essential in Key Decisions
AI can support screening, scoring, analysis, and recommendations. Final decisions-especially in hiring, talent development, and workforce planning-require human judgment, business context, and ethical accountability.
A panel on decision-making across the employee lifecycle reinforced that AI should augment, not replace, human judgment. While AI can rank candidates, final hiring decisions must account for culture fit, business context, and industry-specific nuances that algorithms cannot capture.
The panel also stressed that leadership-not just HR-must drive conversations about AI readiness and literacy. Organisations need a shared language grounded in human-centricity, technology, and domain expertise.
HR Must Become Product-Led and Data-Driven
The traditional HR service desk model is becoming unsustainable. As automation and conversational AI handle routine queries, HR must evolve into a product organisation.
Centres of Expertise should function as product teams. HR business partners should become talent portfolio managers. HR technology must be treated as a core business capability, not a support function.
The goal is to make HR scalable, data-driven, and outcome-focused. Without this shift, HR risks "designing its own obsolescence" by remaining transactional. Differentiation comes from institutional knowledge, how AI is embedded into processes, and how organisations integrate capabilities across knowledge, skills, tools, and workflows.
Culture Determines Whether AI Creates Value
Psychological safety, trust, continuous learning, manager enablement, and open experimentation are critical. Employees must embrace AI meaningfully rather than simply comply with new tools.
A final panel on building resilience into culture reinforced that transformation is now constant, not episodic. Change management must become a core leadership capability. Innovation does not always require new technology-incremental improvements from frontline employees can create meaningful impact when organisations actively support those ideas.
The panel stressed that agility and future-readiness are built through cultures grounded in trust, collaboration, continuous learning, and open communication-not through technology adoption alone.
Practical Challenges HR Leaders Face
Conference attendees identified six real-world problems requiring solutions:
- Scaling AI learning: How to ensure every employee-not just digitally fluent workers-can use AI effectively.
- Role redesign: What's the fastest way to remap tasks between people and AI without disrupting operations.
- Building trust in AI: How to teach teams to trust, question, and calibrate AI recommendations responsibly.
- Change management: How to make adoption stick when employees resist new tools.
- Unlocking value: How to foster experimentation, reskill talent, and adapt ways of working to realise AI benefits.
- Manager capability: What managers need to lead effectively in an augmented workplace.
The Judgment Muscle
As AI removes execution-based and apprenticeship-style work, organisations risk removing the experiences that traditionally built employee depth, accountability, and decision-making capability.
Maurice Ky, Director of Data and Analytics at Ubisoft Singapore, questioned what development pathways would look like for younger generations if AI absorbs foundational tasks. He emphasised that employees must learn to take accountability, understand consequences, and develop awareness through repeated exposure to real-world challenges.
Experienced leaders play an increasingly important role in helping younger talent balance AI-enabled work with human judgment. At the same time, senior employees must remain open to learning from younger generations who may adapt to AI-native ways of working more quickly.
Ky described the value of building teams with both "cautious thinkers" and "fast innovators." Cautious thinkers ground ideas and stress-test assumptions. Innovators push the organisation forward. Both are necessary for balanced decision-making.
Organisations should measure whether judgment itself develops over time-reflected not only in outcomes, but also in the evolution of questions employees ask and how teams respond to unfamiliar situations.
What HR Leaders Should Do Now
Ramya Balakrishnan, VP Global Talent and Development at Coty, framed the challenge as a "judgment problem," not a "tools problem."
She encouraged HR leaders to:
- Strengthen their ability to make judgment calls about what should remain human and where AI should be deployed.
- Develop "sense making" skills-translating AI into language that resonates with different stakeholders.
- Begin work redesign by identifying actual organisational problems, not by deploying technology because it exists.
- Avoid creating "dangerous dependence" on AI systems that could become single points of failure.
Balakrishnan's closing advice was direct: use AI on your own work this week, have one honest conversation with a peer leader, and kill one HR ritual that AI just made obsolete.
For HR leaders seeking to develop AI fluency at the strategic level, AI for CHROs (Chief Human Resources Officers) provides frameworks for navigating workforce transformation and talent management strategy. For those implementing AI across HR operations, AI for HR Managers covers practical applications in recruitment automation, workforce analytics, and talent management.
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