The foundation paradox: Reframing the AI race for ASEAN’s sustainable future

I. The ASEAN digital mirage: Beyond the AI race narrative

For ASEAN, the "AI Race" is about more than just algorithmic supremacy — it's about economic transformation and regional survival. By 2030, the region's digital economy is estimated to grow to $1 trillion, with AI alone accounting for 10% to 18% of GDP. This "Digital Siren Song"  conceals a harsh truth, though: although Singapore is ranked second in the world for AI  preparedness, other member nations like Laos and Myanmar are ranked as low as 137th and  143rd, respectively. 

High-tech "leapfrogging" projects are frequently started in places without reliable electricity or basic sanitation due to the need to compete on a global scale. Unmanaged AI runs the potential of causing a "New Great Divergence," in which countries' starting points are so dissimilar that the technology actually increases rather than closes gaps in human capabilities and economic performance. 

The illusion of leapfrogging in Southeast Asia 

In ASEAN, technological "leapfrogging" is a common narrative, with the quick transition to mobile banking serving as an example. However, this is a "superficial fix" for the 2.7 billion "unconnected" people in the world, many of whom live in rural Southeast Asia. Only roughly 30% of rural residents in countries like Lao PDR and Cambodia have access to clean water compared to their urban counterparts. 

II. The trap of forced AI adoption: The need for an infrastructure foundation 

The attempt to "force" the AI issue when the majority of ASEAN nations lack the fundamental readiness to support it is a major concern facing the region. Without the required "plumbing,"  forcing high-level AI deployment in delicate digital contexts can result in systemic failure and a  "two-tier" infrastructure that further disadvantages rural areas.

The infrastructure bottleneck 

AI is not plug-and-play; instead, it is mostly dependent on strong digital frameworks, such as fast internet, dependable power, and sophisticated data centres. These resources are either scarce or unequally distributed in many developing ASEAN nations. Blackouts regularly interfere with AI model training and real-time applications without reliable, high-capacity electricity,  making even the most advanced systems inoperable. 

A permanent digital underclass could also result from the rush for cutting-edge technology like 6G while basic 4G access is still lacking in rural Myanmar and Laos. Forcing AI adoption in these situations frequently leads to "stalled pilots," where initiatives appear promising on paper but are unable to grow due to inadequate infrastructure. 

Establishing a sustainable IT practice foundation 

ASEAN must refocus on creating a basis for sustainable IT practices and infrastructure in order to avoid these pitfalls. This includes: 

• Infrastructure Productivity: The "Framework for Improving ASEAN Infrastructure Productivity," which places an emphasis on effective planning and the distribution of limited resources, will replace quick, inefficient expenditures. 

• Resilient Digital Architecture: The region must give top priority to building resilient infrastructure based on AI, IoT, and cloud services that are appropriate for challenging local conditions, as stated in the Hanoi Digital Declaration 2026.  

• Interoperable Data Ecosystems: Since data is the basis for all AI technologies, creating open and safe data ecosystems is crucial. Regional integration is still unattainable without standardised compliance and interoperability. 

III. The ASEAN multiplier: Why AI workflows impact the region more 

AI is a crucial "efficiency multiplier" for the SME backbone in ASEAN, in contrast to industrialised countries, where it frequently replaces manpower. SMEs are the main employers in the area, making up 99% of all businesses. 

AI as an equalizer for SMEs 

For ASEAN SMEs operating on thin margins, AI workflows provide immediate, measurable  gains: 

• Operational Efficiency: Adoption of AI can cut fuel consumption by 11–13% in logistics and energy or material waste by 11–14% in manufacturing. 

• Case Use: Ahamove (Vietnam): helps small eateries handle busy times with fewer employees by using a generative AI virtual assistant. 

• Case employ: Fashion E-commerce (Malaysia): In order to maintain healthy margins versus multinational behemoths, sellers employ AI to manage replenishment and track product performance in real-time. 

However, there is still a "skills gap": 50% of SMEs mention the high cost of integrating AI as the key obstacle, while 75% of ASEAN employers indicate that recent graduates are not prepared for these AI-driven professions.

IV. Sustainability practices: A survival mechanism for Southeast Asia 

In ASEAN, operational resilience requires sustainability. By 2035, 25% of the world's energy demand is expected to come from Southeast Asia, and by 2030, 75% of its cities will frequently experience flooding. 

The Water-Energy-AI nexus 

Infrastructure for AI is "resource-ravenous." A single AI-focused hyperscale data centre can use up to 5 million gallons of water every day, which is equivalent to a city of 50,000 people, and it uses as much electricity as 100,000 houses.  

• Singapore's Green DC Roadmap: Targets a Power Usage Effectiveness (PUE) of ≤ 1.3 and a  Water Usage Effectiveness (WUE) of ≤ 2.0 m3/MWh over the next decade.

• Regenerative Manufacturing: This model leverages AI to optimize product life cycles - from material choice to disposal - to create Profit-Sustainability parity.

V. The social fabric: Addressing wealth chasms in a digital age 

One "policy choice" in ASEAN is inequality. Nowadays, 75% of all personal wealth is held by the richest 10% of people worldwide, while only 2% is held by the poorest half. The top 1% wealth criterion in ASEAN varies from $5.23 million in Singapore to $60,000 in the Philippines. 

The Stiglitz-Sen framework for ASEAN 

A "dual economy" nightmare, according to Joseph Stiglitz, is one in which the wealthy reside in gated communities while the remainder experience instability in healthcare and education. Development is about "capability expansion" - the freedom to live the lives people value,  according to Amartya Sen's Capability Approach. 

• The Conversion Problem: Even if a farmer has access to an AI chatbot, it won't help them if they lack literacy, steady energy, or trust - all of which are conversion variables.

VI. Existential essentials: The infrastructure crisis 

The "SDG investment gap," which is $4 trillion annually in developing nations, must not be overshadowed by the rush to AI. It would take a six-fold increase in current progress rates to provide universal coverage for securely managed drinking water by 2030. 

The opportunity cost: Data centres vs. human life 

Building a single AI-optimized data centre can cost more than $20 million per megawatt. This amounts to a $1.2 billion investment for a mid-size 60MW project. On the other hand, it costs about $114 billion a year to provide 140 low- and middle-income nations with universal access to clean water and sanitary facilities. Diverting infrastructure budgets to "win" a technology race when 2.1 billion people lack safe water is a high-stakes gamble with human capital.

VII. New insights: The hidden costs of the AI supply chain 

1. The Invisible Labours: Digital Sweatshops in ASEAN 

The "invisible labour" of 150–430 million data workers is what powers the algorithms. Data workers earn less than $2 per hour in "digital sweatshops" in nations like the Philippines and  Vietnam, where they are frequently exposed to upsetting material with little assistance. 

2. The E-Waste Fallout: Hardware's Toxic Legacy 

The amount of electronic waste is increasing five times more quickly than recorded recycling.  Malaysia produces 12.2 kg of e-waste per person yearly, which is significantly more than the global average of 7.8 kg, placing it third in ASEAN. 

VIII. A hierarchy of national needs: The HE-AI framework mapping 

Inspired by Maslow's hierarchy, the Hierarchy of Engagement with AI (HE-AI) model offers countries a diagnostic and strategic road map for understanding AI adoption as a progression through eight distinct levels. It acknowledges that AI maturity is a multifaceted process that integrates organisational resilience, ethical integrity, and technological capabilities in addition to technical proficiency. 

The levels of engagement and their ASEAN significance 

• Level 0: First Exposure & Curiosity: Motivated by fundamental accessibility and building trust. This is the most crucial stage in rural Cambodia or Myanmar, where outreach and basic literacy are needed before any tools are used. 

• Level 1: Awareness & Orientation: This level emphasises efficiency, safety, and responsible use rules for basic tasks. Maslow's "safety needs" are in line with this.  

• Level 2: Guided Application: Using third-party infrastructure and departmental training to shift to departmental or SME use. At the moment, the majority of ASEAN economies are trying to reach this level.  

• Level 3: Competence & Autonomous Utilisation: Creating national AI commons (HPC clusters) and safe internal data pipelines. A step toward this maturity is Malaysia's $43.6 billion investment in data centres. 

• Level 4: Strategic Alignment & Innovation: Developing new solutions and incorporating AI into fundamental national strategies. An early entry into this stage can be seen in the rise of AI start-ups in Vietnam.  

• Level 5: The "Ethics Gate" is the most important intersection for developing countries. Before implementing AI in mission-critical fields like health and finance, bias audits, transparency, and independent monitoring are necessary. Ignoring this barrier results in public rejection and algorithmic prejudice.  

• Level 6: Human-AI Co-Evolution: Deep, extensive integration with strong governance. As of right now, Singapore is the only ASEAN nation getting close to this stage. 

• Level 7: Societal & Global Impact: The pinnacle of maturity (equivalent to Maslow's "transcendence"), where a country establishes international norms and advances interoperable, morally sound AI for the benefit of society.  

Table 1: ASEAN Mapping of AI Engagement Maturity (2025-2026)

Source: Derived from Global AI Adoption 2025, Government AI Readiness Index, and regional infrastructure reports. 

At the moment, the majority of ASEAN members are in Levels 0 through 2. Project rejection and "robot policing" resistance result from rushing to "Mastery" (Level 5) without the digital infrastructure or trust of Level 0. 

XI. Regional resilience: The road to 2045 

Adopted during the 46th ASEAN Summit in 2025, the ASEAN Community Vision 2045 places  "Regional Resilience" as the cornerstone for the ensuing twenty years. In this perspective, the concept of regional power is redefined from technological supremacy to Comprehensive  Security, which is the capacity to endure shocks related to geopolitics, biology, and climate change through mutual cooperation. 

Strategic goals for the road to 2045 

1. Protect Human Security First: The ASCC 2045 Strategic Plan's implementation prioritises poverty alleviation and social protection as a precondition for digital transformation. 

2. Bridging the Urban-Rural Continuum: In order to avoid the "Dual Economy," achieving universal access to safe water and electricity in rural Cambodia, Laos, and Vietnam has taken precedence over the deployment of 6G in urban areas.  

3. Green Finance and Carbon Neutrality: Expanding regional clean energy projects, such as the ASEAN Power Grid, to help meet the 2030 target of 45% renewable capacity.  

4. Inclusive Digital Transformation: Encouraging "Effective Digital Transformation," which puts 5.5 million people' upskilling ahead of software deployment.  

5. Data Sovereignty through Strategic Interdependence: Rethinking sovereignty from individual rivalry for foreign hyperscale nodes to regional cooperation on AI testing and benchmarking (the "ASEAN Safety Test"). 

Actionable roadmap for ASEAN leadership 

• Mandate GREEN Infrastructure: Follow Singapore’s lead in setting strict PUE(≤1.3) and WUE(≤2.0) standards to protect local water basins. 

• Institutionalize 4Ps: Encourage "Public-Private-People Partnerships" so that marginalised communities and young people can co-create the digital landscape. 

• Narrow the Development Gap (NDG): To close the $210 billion yearly investment gap for sustainable projects throughout the entire bloc, capacity-building must extend beyond the  CLMV nations. 

Final commentary 

The AI Race is a marathon on sinking ground for ASEAN. Building on sand are nations that prioritise computational supremacy over their social structure and physical underpinnings. The  region must move from "Connectivity to Connected Intelligence," as the Hanoi Digital  Declaration 2026 highlights; nevertheless, this intelligence is useless if it is not connected to the  life of the "informal majority." 

By 2045, the depth of the social compact, the stability of the electrical grid, and the  dependability of the water tap will be the real indicators of development rather than the  quantity of LLMs installed. "Compassionate Connectivity" - making sure that every community,  from metropolitan innovators to rural enterprises, shares in the benefits—will decide success in the AI future. By focusing on the "Existential Essentials," ASEAN creates the only environment in which it can succeed rather than losing the race. Being the most equipped to withstand the future together, rather than being the first to arrive, is the ultimate competitive advantage in the twenty-first century.

illuminem Voices is a democratic space presenting the thoughts and opinions of leading Sustainability & Energy writers, their opinions do not necessarily represent those of illuminem.

Track the real‑world impact behind the sustainability headlines. illuminem’s Data Hub™ offers transparent performance data and climate targets of companies driving the transition.