In business, as on the racetrack, winning teams don’t tweak last year’s engines. They build for an all-new race, designing lighter, more powerful systems and putting every resource in place for performance. Now, that new growth engine is AI.
Across Southeast Asia, the tension between ambition and influence is becoming increasingly evident. According to Accenture’s report, Sovereign AI: Driving Competitive Advantage in APAC, organizations in the region are developing their AI infrastructure, with more than 64% planning to increase investment in sovereignty-related AI technologies, and markets such as Singapore and Indonesia are emerging as early testbeds for advanced AI adoption.
However, adoption remains uneven and much of the focus in the region remains on compliance, governance and risk management rather than unlocking new growth.
This gap is significant and costly. According to Accenture’s report, “The Great Value Migration,” $27 trillion in enterprise value has migrated to the world’s 3,000 largest companies over the past decade, with one-third of that migration occurring in the past two years. The report also reveals that these companies are losing nearly $5 trillion in revenue due to disruption, indicating that new value pools are forming faster than companies can rewire.
As the rules of growth, competitiveness, and leadership are rewritten, companies need to design AI-native business models where AI shapes not only their operations but their economics.
Asia Pacific is poised for AI-driven growth
Organizations in APAC are increasingly recognizing the role of AI in their growth, reflected in both leadership priorities and increased investment. According to Accenture’s Pulse of Change study, more than three in four C-suite leaders (76%) believe the primary benefit of AI is increased revenue rather than cost reduction, and 86% of organizations plan to increase their investment in AI over the next year.
This shift from AI ambition to execution is increasingly being strengthened at the national level across Southeast Asian countries. Singapore has positioned AI as core economic infrastructure in its 2026 National Budget, established a National AI Council, and launched sector-specific AI missions to accelerate adoption, talent development, and enterprise-level impact. Similarly, Malaysia is accelerating its goal of becoming an AI nation by 2030, backed by government-led investments to accelerate the adoption of technologies such as AI.
So what separates companies that are capturing real value from those that are still exploring?
- Data must drive growth, not just operations
Many organizations treat data as an operational input rather than a growth engine. Incomplete, inconsistent, or disconnected data will produce low-quality output. High-performing companies do things differently, using proprietary data to develop new products, explore new channels, and build commercial models that their competitors can’t imitate. According to Accenture’s report, Making reinvention real with gen AI, one-third (34%) of companies have already scaled at least one industry-specific solution, making them three times more likely to achieve enterprise-level benefits. As racing teams constantly analyze telemetry to improve performance, leaders must ask themselves: Is our data capturing growth, and what data are we missing to redefine the productivity frontier?
- Agentic AI is new capital, not just automation
AI agents that can interpret context, act autonomously, and adjust workflows in ways that change the way companies think about labor, assets, and resource allocation are reshaping competition. This is not just a matter of efficiency. It’s about doubling capacity and generating new revenue. Agenttic AI requires a fundamentally different operating model that integrates AI into decision-making, workflows, and business architecture. This is the essence of becoming an AI-native company.
- Growth requires orchestration of the entire ecosystem, not isolation
AI doesn’t work alone. It relies on computing, cloud, and data infrastructure that no company can build alone. Once leaders identify agent AI priorities, they can evaluate where to build on their own advantages and leverage partners who already have relevant capabilities. This means knowing when to co-create solutions with partners, when to rely on platforms, and when to invest in in-house capabilities. Organizations that use AI effectively treat their ecosystems, partners, customers, data, and platforms as strategic assets rather than suppliers.
- Investing in technology equals investing in people
AI, like racing, is a team sport. Investments in technology are only as good as the people who utilize them. According to Accenture’s banking blog, “Scaling AI for Business Transformation,” companies that invest in technology and talent are four times more likely to achieve long-term profitable growth. However, Accenture’s Pulse of Change study found that only 27% of C-suite leaders are prioritizing adapting their employees to the new environment, and less than one in five employees (21%) believe they have a say in how AI is introduced and used in the workplace. Closing the gap will require redesigning workflows, redefining roles, and incorporating continuous learning to help employees use AI effectively.
Leadership imperatives: Scaling, reinventing, and letting go.
Confusion is not a signal to retreat. It is the starting point for building resilience. Success with AI requires redirecting investments, creating new business models, and redefining how value is measured when pilots fail.
Successful organizations pivot quickly, expand rapidly, and abandon what is no longer useful. This gives CEOs a new mandate. It’s about building AI-native business models, building on differentiated data advantages, deploying agent systems at scale, investing deeply in talent, and mobilizing the ecosystem to accelerate reinvention.
