Executive Summary
In Southeast Asia’s dynamic markets, digital and AI transformation often revolves around an overt focus on technology. We believe the first step in any successful transformation is to ensure that stakeholders are aligned on a clear business strategy. However, strategy and technology alone are not enough to deliver sustainable impact. Strategy can be developed, technology can be bought, but culture must be built. Without cultural readiness—shaped deliberately by leaders—AI projects stall, adoption falters, and trust erodes.
Culture dictates how decisions are made, how risks are taken, and how innovation is embraced or resisted. While technology provides the tools, culture determines whether those tools are adopted, scaled, and embedded into the fabric of the organization. Executives must act not just as sponsors but as cultural architects, deliberately shaping behaviors, rituals, and systems to ensure transformation succeeds.
What Do We Mean by “Culture”?
“Culture” is one of the most frequently used but often misunderstood terms in business. Leaders talk about culture when they mean values, behaviours, incentives, or sometimes just employee morale. In truth, culture is the shared system of beliefs, behaviors, and norms that guide how work actually gets done in an organization. It is not what is written on posters, but what is reinforced day to day in decisions, rituals, and leadership examples.
- Beliefs & Mindsets – What people assume to be true about customers, risk, technology, and performance.
- Behaviors & Rituals – The daily practices, meeting cadences, and ways of working that reinforce those beliefs.
- Structures & Systems – Incentives, KPIs, governance, and organizational design that either support or block the right behaviors.
- Symbols & Stories – The narratives, role models, and symbols that embody the culture (e.g., a CEO experimenting openly with AI tools, or celebrating “fast failures”).
Culture becomes visible when these dimensions align. If not, employees receive mixed signals—leading to confusion, cynicism, or resistance.
Introduction to the Three Cultural Battlegrounds
To operationalize culture for digital and AI transformation, we focus on three critical battlegrounds:
- Mindset Reboot — Leadership as Cultural Signal: Transformation begins with what leaders say and do. Leaders set the tone for curiosity, humility, and experimentation. Without visible role modelling, cultural change will stall.
- Norms & Operating Rituals — Embedding Culture in Everyday Work: Culture lives in the mechanics of how work gets done. Embedding new rituals—cross-functional squads, agile governance, and transparent decision flows—ensures AI becomes part of business-as-usual, not a bolt-on.
- Safe to Fail, Fast to Learn — Institutionalising Experimentation: AI thrives in environments where teams feel safe to test, learn, and iterate. Psychological safety, learning reviews, and reward mechanisms create the conditions for scalable innovation.
Together, these three parts create a flywheel of cultural acceleration: leadership sets the tone, rituals embed new norms, and safe experimentation reinforces continuous learning.
Part I: Mindset Reboot — Leadership as Cultural Signal
Key Point
Culture change starts at the top. Employees follow what they see leaders do, not what leaders say. Executives must demonstrate curiosity, humility, and willingness to experiment with AI tools themselves. Leaders must acknowledge their own learning journey, signalling permission for teams to do the same.
Why This Matters
If leaders cling to legacy ways of working, employees will conclude that transformation is optional. Conversely, when executives model digital-first behaviors—using AI dashboards in meetings, celebrating small experiments—they create visible proof points of change.
Southeast Asia Example
DBS Bank (Singapore): CEO Piyush Gupta drove digital transformation by positioning DBS as a “26,000-person start-up” and personally role-modelling agile practices.
Part II: Norms & Operating Rituals — Embedding Culture in Everyday Work
Key Point
Culture sticks when embedded in rituals: team formation, decision protocols, and meeting rhythms. Without re-designed norms, AI remains a bolt-on tool. Culture becomes durable only when it is translated into the routines and structures of daily work.
Why This Matters
Operating rituals act as the cultural operating system. If AI adoption is not built into team rituals—such as retrospectives, performance dialogues, or data-driven decision cycles—employees quickly revert to legacy behaviors. Embedding AI into rituals ensures that new ways of working endure.
Southeast Asia Example
Grab (Regional): Grab institutionalized agile pods across the business, giving teams autonomy and embedding rituals like retrospectives to normalise rapid experimentation.
Part III: Safe to Fail, Fast to Learn — Institutionalising Experimentation
Key Point
AI adoption is inherently experimental. Projects will pivot, stall, or fail—but failure can be fuel if teams are empowered to learn. A culture of psychological safety ensures employees take bold bets without fear of punishment.
Why This Matters
If failure is punished, teams will avoid risk and innovation stagnates. By institutionalising a culture of experimentation, organizations accelerate collective learning and innovation. Mechanisms such as “fail-safe budgets,” structured learning reviews, and recognition of both successes and well-documented failures are essential.
Southeast Asia Example
Petronas (Malaysia): In its push toward becoming a “data-driven energy company,” Petronas deliberately set up small-scale AI pilots in refining and trading operations, framing them as learning labs. Leadership encouraged teams to document not just successes but failures, sharing lessons group-wide. By creating safe environments for experimentation, Petronas avoided “big bang” failures while building internal confidence in scaling AI.
The Culture Acceleration Framework
Lead → Embed → Reinforce
- Leadership Mindset & Role Modelling: Executives experiment openly, use AI in decisions, admit failures, signal curiosity.
- Operating Norms & Rituals: Agile squads, cross-functional decision rights, meeting rituals, transparent data use.
- Safety & Learning Culture: Safe-to-fail pilots, psychological safety, rapid iteration, shared learning reviews.
- Reinforcing Mechanisms: KPIs aligned with learning, recognition for collaboration, incentives for experimentation, culture metrics tracked.
Conclusion
In Southeast Asia’s fast-changing markets, culture is the ultimate differentiator. Technology is accessible to all; culture is unique. The Influence Model reminds us: people change when they see new behaviours modelled, understand the “why,” build the skills, and are reinforced through systems.
Executives who embrace this role as cultural architects create transformations that endure. Those who ignore it risk investing millions in technology, only to see it collapse under old habits.
Culture isn’t a by-product of transformation—it is the transformation.
