As organizations across Asia accelerate their AI ambitions, familiar challenges are emerging. While technology adoption is moving rapidly, cultural readiness often lags behind. Despite tools in place and strategies announced, employees are hesitant, unsure, or inconsistent about how to interact with AI in the workplace.
This tension was at the heart of last week’s Asia HR Leaders Live Series. Culture first – driving AI transformation with habits and momentumSponsored and Sponsored by AsiaHRM HRM Asia. This session brought together Rita Tsui, Founder of AsiaHRM, and Yan Jiejun, Workplace Advisory and Transformation Consultant, Senior Vice President and Asia Pacific Lead at Edelman for a grounded, practical discussion on what it actually takes to incorporate AI into daily work.
Rather than focusing on tools and technical roadmaps, the conversation focused on more human things like habits, mindsets, and culture.
Culture is the root of change
At the beginning of the session, Tsui framed AI transformation through a simple but powerful metaphor. “Culture is like the roots of a tree, people are the branches, and the fruit is the result of business,” she said. “Without strong roots, we cannot expect sustainable results.”
This is a reminder that AI transformation is not just a technology upgrade, but a behavioral change. As Tsui pointed out, in the rush to implement AI, organizations often overlook whether the mindset of their employees is truly ready for change.
Yang agreed, adding that many organizations are still grappling with the basics. She discussed three major stages of AI maturity based on Microsoft’s Work Trends Index.
- Phase 1, When AI acts as a personal assistant.
- Phase 2, Involves more autonomous and agentic AI. and
- Phase 3humans and multiple AI agents work as an integrated team.
“The reality is that most organizations are still in Phase 1, and some have just entered Phase 1,” Yang said. “Even if there is a second stage, it usually happens in pockets rather than at scale.”
This uneven progress creates confusion and anxiety among employees, especially if leaders assume implementation is further along than it actually is, she explained.
Hidden obstacles: Fears, silos, and confidence gaps
Despite the increasing use of AI, Yang emphasized that confidence remains a major barrier. Referring to Edelman Trust Barometer: Using AI She noted that research shows that employees are more likely to be cautious rather than resistant.
“People are getting smarter and smarter about AI,” she said. “They recognize the risks of governance, the illusions, and the consequences of getting it wrong.”
At the same time, fear of job separation remains the “elephant in the room.” Yang emphasized that ignoring this fear does not make it go away.
“There is no silver bullet,” she said. “But it is the ethical responsibility of business, HR, communications and transformation leaders to address this issue openly and consistently, rather than forcing employees to imagine the worst.”
Another common roadblock is siled execution. AI efforts are often driven by innovation teams or IT, with HR, communications, and business leaders working in parallel.
“Speed is important, but so is integration,” says Yang. “Without alignment, you will have fragmented messages and uneven adoption across your organization.”
SHAPE: A culture-first framework for AI adoption
To structure this complexity, Yang introduced SHAPE, a framework developed based on consulting work and Edelman’s own AI journey.
- S – systems thinking
- H- habit
- Answer – (Incorporated into habits and play)
- P- play at scale
- E- large-scale efforts
At the core of SHAPE is the idea that sustainable AI adoption is achieved when organizations intervene at multiple levels: individual, team, and enterprise.
“Interventions are most effective when they are mutually reinforcing throughout the system,” Yang explained. “It’s rarely about doing one big thing perfectly; it’s about continually adjusting as the organization learns.”
Of all the enablers, the one that caused the most discussion was habit. Citing behavioral science research, Yang argued that change fails not because people lack motivation, but because habits are too big, too vague, or too overwhelming.
“Encouraging employees to use AI for 30 seconds once a day may seem trivial, but it makes a difference,” she said. “That small action reduces resistance and creates confidence.”
Usage will naturally grow as employees begin to see tangible benefits such as time savings, idea generation, and improved outcomes. Yang added that celebration and recognition play an important role in reinforcing these actions.
Tsui strongly resonates with this point and connects it with the views of James Clear. Atomic Habits. “Micro-habits create sustainability,” she said. These help people change their behavior without being pressured or overwhelmed. ”
The third enabler, large-scale play, focuses on emotion. Yang emphasized that learning sticks when people feel psychologically safe. “When people feel relaxed, curious and supported, they are much more willing to experiment,” she said.
Read more: One size does not fit all: Decoding the cultural blind spots of psychological safety
Rather than abstract AI training, Yang advocated scenario-based learning, which shows how AI is applied to real-world roles and tasks. Sharing internal success stories, featuring employees as “AI champions,” and encouraging leaders to experiment openly can all help build momentum.
In particular, leadership role modeling sets the tone. “When a leader says, ‘I tried this and it didn’t work, can you help me?’ that normalizes learning and failure,” Yang said. “That vulnerability creates trust.”
Tsui emphasized this point, noting that leaders who actively leverage AI are in a better position to understand the challenges their teams face.
The final enabler, large-scale initiatives, recognizes that AI transformation is a long-term journey. Mr. Yang emphasized the importance of strong collaboration between executives, human resources, communications, change teams, and influential middle management.
“The road to change is bumpy,” she says. “We need a coalition that stays connected, challenges disagreements, and continues to adjust as circumstances change.”
Communication is never “done,” she added. Leaders consistently underestimate the amount of communication needed. “It’s about creating a surround sound effect,” Yang explained. “Strategic messages from the top, followed by meaningful conversations at the team level, supported by live FAQs and an evolving narrative.”
Human challenges to the future of AI
When the session ended, Tsui returned to his central theme. In other words, progress happens when organizations come together and move forward. “You might go faster if you go alone,” she said, “but if you want to go far, you have to go together.”
The takeaway for HR leaders is clear. AI transformation cannot be achieved through technology alone or through one-off training programs. It is built through habits, trust, leadership behaviors, and sustained engagement. Or, as Yang succinctly put it, “There is no strategy for AI. But if you get the culture right, your organization will learn how to move forward.”
