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Smart Solutions for Real Problems: Exploring Innovations in Southeast Asia’s Cities

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With over 70% of the world’s population predicted to live in cities by 2050, smart cities that use data, technology, and AI to streamline services are key to ensuring a healthy and safe environment for all who live, work, or visit them.

Fueled by rapid urbanisation, Southeast Asia is experiencing a smart city boom with an estimated 100 million people expected to move from rural areas to cities by 2030.

Despite their diverse populations and varying economic stages, ASEAN member countries are increasingly on the same page: they are all united by the belief that smart cities offer a solution to the complex urban and socio-economic challenges they face.

Read on to discover how Southeast Asian countries are using new tools to manage growth and deliver a better quality of life to hundreds of millions of people.

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Click here to download ‘Smart Solutions for Real Problems: Exploring Innovations in Southeast Asia’s Cities’ as a PDF

ASCN: A Network for Smarter Cities

The ASEAN Smart Cities Network (ASCN) is a collaborative platform where cities in the region exchange insights on adopting smart technology, finding solutions, and involving industry and global partners. They work towards the shared objective of fostering sustainable urban development and enhancing livability in their cities.

As of 2024, the ASCN includes 30 members, with new additions from Thailand and Indonesia.

“The ASEAN Smart Cities Network provides the sort of open platform needed to drive the smart city agenda. Different cities are at different levels of developments and “smartness” and ASEAN’s diversity is well suited for such a network that allows for cities to learn from one another.”

Taimur Khilji
UNITED NATIONS DEVELOPMENT PROGRAMME (UNDP)

Singapore’s Tech-Driven Future

The Smart Nation Initiative harnesses technology and data to improve citizens’ lives, boost economic competitiveness, and tackle urban challenges.

Smart mobility solutions, including sensor networks, real-time traffic management, and integrated public transportation with smart cards and mobile apps, have reduced congestion and travel times.

Ranked 5th globally and Asia’s smartest city, Singapore is developing a national digital twin to for better urban management. The 3D maps and subsurface model, created by the Singapore Land Authority, will help in managing infrastructure and assets.

The Smart City Initiative promotes sustainability with innovative systems like automated pneumatic waste collection and investments in water management and energy-efficient solutions.

Malaysia’s Holistic Smart City Approach

With aspirations to become a Smart Nation by 2040 (outlined in their Fourth National Physical Plan – NPP4), Malaysia is making strides.

Five pilot cities, including Kuala Lumpur and Johor Bahru, are testing the waters by integrating advanced technologies to modernise infrastructure.

Pilots embrace sustainability, with projects like Gamuda Cove showcasing smart technologies for intelligent traffic management and centralised security within eco-friendly developments.

Malaysia’s Smart Cities go beyond infrastructure, adopting international standards like the WELL Building Standard to enhance resident health, well-being, and productivity. The Ministry of Housing and Local Government, collaborating with PLANMalaysia and the Department of Standards Malaysia, has established clear indicators for Smart City development.

Indonesia’s Green Smart City Ambitions

Eyeing carbon neutrality by 2060, Indonesia is pushing its Smart City initiatives.

Their National Long-Term Development Plan prioritises economic growth and improved quality of life through digital infrastructure and innovative public services.

The goal is 100 smart cities that integrate green technology and sustainable infrastructure, reflecting their climate commitment.

Leaving behind congested Jakarta, Indonesia is building Nusantara, the world’s first “smart forest city“. Spanning 250,000 hectares, Nusantara will boast high-capacity infrastructure, high-speed internet, and cutting-edge technology to support the archipelago’s activities.

Thailand’s Smart City Boom

Thailand’s national agenda goes big on smart cities.

They aim for 105 smart cities by 2027, with a focus on transportation, environment, and safety.

Key projects include:

  • USD 37 billion smart city in Huai Yai with business centres and housing for 350,000.
  • A 5G-powered smart city in Ban Chang for enhanced environmental and traffic management.
  • USD $40 billion investment to create a smart regional financial centre across Chonburi, Rayong, and Chachoengsao.

Philippines Fights Urban Challenges with Smart Solutions

By 2050, population in cities is expected to soar to nearly 102 million – twice the current figure.

A glimmer of optimism emerges with the rise of smart city solutions championed by local governments (LGUs).

Rapid urbanisation burdens the Philippines with escalating waste. By 2025, daily waste production could reach a staggering 28,000 tonnes. Smart waste management solutions are being implemented to optimise collection and reduce fuel consumption.

Smart city developer Iveda is injecting innovation. Their ambitious USD 5 million project brings AI-powered technology to cities like Cebu, Bacolod, Iloilo, and Davao. The focus: leverage technology to modernise airports, roads, and sidewalks, paving the way for a more sustainable and efficient urban future.

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Coding Evolved: How AI Tools Boost Efficiency and Quality

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AI tools have become a game-changer for the technology industry, enhancing developer productivity and software quality. Leveraging advanced machine learning models and natural language processing, these tools offer a wide range of capabilities, from code completion to generating entire blocks of code, significantly reducing the cognitive load on developers. AI-powered tools not only accelerate the coding process but also ensure higher code quality and consistency, aligning seamlessly with modern development practices. Organisations are reaping the benefits of these tools, which have transformed the software development lifecycle. 

Ecosystm research indicates that close to half (nearly 50%) of Asia Pacific organisations are already leveraging AI tools for code generation, with an additional 32% actively evaluating similar GenAI tools

Impact on Developer Productivity 

AI tools are becoming an indispensable part of software development owing to their: 

  • Speed and Efficiency. AI-powered tools provide real-time code suggestions, which dramatically reduces the time developers spend writing boilerplate code and debugging. For example, Tabnine can suggest complete blocks of code based on the comments or a partial code snippet, which accelerates the development process. 
  • Quality and Accuracy. By analysing vast datasets of code, AI tools can offer not only syntactically correct but also contextually appropriate code suggestions. This capability reduces bugs and improves the overall quality of the software. 
  • Learning and Collaboration. AI tools also serve as learning aids for developers by exposing them to new or better coding practices and patterns. Novice developers, in particular, can benefit from real-time feedback and examples, accelerating their professional growth. These tools can also help maintain consistency in coding standards across teams, fostering better collaboration. 

Advantages of Using AI Tools in Development 

  • Reduced Time to Market. Faster coding and debugging directly contribute to shorter development cycles, enabling organisations to launch products faster. This reduction in time to market is crucial in today’s competitive business environment where speed often translates to a significant market advantage. 
  • Cost Efficiency. While there is an upfront cost in integrating these AI tools, the overall return on investment (ROI) is enhanced through the reduced need for extensive manual code reviews, decreased dependency on large development teams, and lower maintenance costs due to improved code quality. 
  • Scalability and Adaptability. AI tools learn and adapt over time, becoming more efficient and aligned with specific team or project needs. This adaptability ensures that the tools remain effective as the complexity of projects increases or as new technologies emerge. 

Deployment Models 

The choice between SaaS and on-premises deployment models involves a trade-off between control, cost, and flexibility. Organisations need to consider their specific requirements, including the level of control desired over the infrastructure, sensitivity of the data, compliance needs, and available IT resources. A thorough assessment will guide the decision, ensuring that the deployment model chosen aligns with the organisation’s operational objectives and strategic goals. 

SAAS Vs. On-Premises: A guide to choosing the right deployment model

Technology teams must consider challenges such as the reliability of generated code, the potential for generating biased or insecure code, and the dependency on external APIs or services. Proper oversight, regular evaluations, and a balanced integration of AI tools with human oversight are recommended to mitigate these risks. 

A Roadmap for AI Integration 

The strategic integration of AI tools in software development offers a significant opportunity for companies to achieve a competitive edge. By starting with pilot projects, organisations can assess the impact and utility of AI within specific teams. Encouraging continuous training in AI advancements empowers developers to leverage these tools effectively.  Regular audits ensure that AI-generated code adheres to security standards and company policies, while feedback mechanisms facilitate the refinement of tool usage and address any emerging issues. 

Technology teams have the opportunity to not only boost operational efficiency but also cultivate a culture of innovation and continuous improvement in their software development practices. As AI technology matures, even more sophisticated tools are expected to emerge, further propelling developer capabilities and software development to new heights. 

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Upskilling for the Future: Building AI Capabilities in Southeast Asia

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Southeast Asia’s massive workforce – 3rd largest globally – faces a critical upskilling gap, especially with the rise of AI. While AI adoption promises a USD 1 trillion GDP boost by 2030, unlocking this potential requires a future-proof workforce equipped with AI expertise.

Governments and technology providers are joining forces to build strong AI ecosystems, accelerating R&D and nurturing homegrown talent. It’s a tight race, but with focused investments, Southeast Asia can bridge the digital gap and turn its AI aspirations into reality.

Read on to find out how countries like Singapore, Thailand, Vietnam, and The Philippines are implementing comprehensive strategies to build AI literacy and expertise among their populations.

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Download ‘Upskilling for the Future: Building AI Capabilities in Southeast Asia’ as a PDF

Big Tech Invests in AI Workforce

Southeast Asia’s tech scene heats up as Big Tech giants scramble for dominance in emerging tech adoption.

Microsoft is partnering with governments, nonprofits, and corporations across Indonesia, Malaysia, the Philippines, Thailand, and Vietnam to equip 2.5M people with AI skills by 2025. Additionally, the organisation will also train 100,000 Filipino women in AI and cybersecurity.

Singapore sets ambitious goal to triple its AI workforce by 2028. To achieve this, AWS will train 5,000 individuals annually in AI skills over the next three years.

NVIDIA has partnered with FPT Software to build an AI factory, while also championing AI education through Vietnamese schools and universities. In Malaysia, they have launched an AI sandbox to nurture 100 AI companies targeting USD 209M by 2030.

Singapore Aims to be a Global AI Hub

Singapore is doubling down on upskilling, global leadership, and building an AI-ready nation.

Singapore has launched its second National AI Strategy (NAIS 2.0)  to solidify its global AI leadership. The aim is to triple the AI talent pool to 15,000, establish AI Centres of Excellence, and accelerate public sector AI adoption. The strategy focuses on developing AI “peaks of excellence” and empowering people and businesses to use AI confidently.

In keeping with this vision, the country’s 2024 budget is set to train workers who are over 40 on in-demand skills to prepare the workforce for AI. The country will also invest USD 27M to build AI expertise, by offering 100 AI scholarships for students and attracting experts from all over the globe to collaborate with the country.

Thailand Aims for AI Independence

Thailand’s ‘Ignite Thailand’ 2030 vision focuses on  boosting innovation, R&D, and the tech workforce.

Thailand is launching the second phase of its National AI Strategy, with a USD 42M budget to develop an AI workforce and create a Thai Large Language Model (ThaiLLM). The plan aims to train 30,000 workers in sectors like tourism and finance, reducing reliance on foreign AI.

The Thai government is partnering with Microsoft to build a new data centre in Thailand, offering AI training for over 100,000 individuals and supporting the growing developer community.

Building a Digital Vietnam

Vietnam focuses on AI education, policy, and empowering women in tech.

Vietnam’s National Digital Transformation Programme aims to create a digital society by 2030, focusing on integrating AI into education and workforce training. It supports AI research through universities and looks to address challenges like addressing skill gaps, building digital infrastructure, and establishing comprehensive policies.

The Vietnamese government and UNDP launched Empower Her Tech, a digital skills initiative for female entrepreneurs, offering 10 online sessions on GenAI and no-code website creation tools.

The Philippines Gears Up for AI

The country focuses on investment, public-private partnerships, and building a tech-ready workforce.

With its strong STEM education and programming skills, the Philippines is well-positioned for an AI-driven market, allocating USD 30M for AI research and development.

The Philippine government is partnering with entities like IBPAP, Google, AWS, and Microsoft to train thousands in AI skills by 2025, offering both training and hands-on experience with cutting-edge technologies.

The strategy also funds AI research projects and partners with universities to expand AI education. Companies like KMC Teams will help establish and manage offshore AI teams, providing infrastructure and support.

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The Future of Thailand Tech: A Roadmap for CIOs & Technology Leaders

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The technology market in Thailand continues to evolve at an unprecedented pace, creating both exciting opportunities and significant challenges for tech leaders in the country. Real-world AI applications and cloud expansion define the future of IT strategies in 2024, as organisations push digital transformation forward. Understanding these trends is crucial for navigating today’s market complexities and achieving exponential growth. Here are the opportunities in the Thailand technology landscape and insights on how to address them effectively.

Tech Modernisation: Breaking Free from Vendor Lock-in

Data centre consolidation and infrastructure modernisation remain top priorities for organisations in Thailand. These processes catalyse the ‘de-requisitioning’ removing outdated or unnecessary technology from an organisation’s infrastructure. But vendor lock-ins pose challenges for organisations, mainly stifling organisational flexibility, hindering innovation, and exposing them to business disruption risks.

44% of organisations in Thailand are focused on consolidating data centres and modernising tech stacks to mitigate vendor lock-ins and enhance operational efficiency.

Modernising infrastructure reduces reliance on single vendors and improves scalability and resilience. Despite the widespread adoption of hybrid and multi-cloud environments, effectively managing these systems remains challenging and requires additional strategic investments.

Over-reliance on a single provider can expose organisations to new risks. This is why CIOs in Thailand are taking decisive steps to combat technology vendor lock-in. They are centralising and modernising their data centres and enhancing cross-platform tools to reduce vendor dependency.

This approach is key to their long-term growth and innovation, allowing them to remain at the forefront of the digital transformation landscape, ready to leverage emerging technologies and adapt to expanding business challenges.

The Hybrid Cloud Labyrinth: Managing Complexity for Success

Nearly 60% of Thailand organisations have embraced hybrid and multi-cloud environments, but the challenges of managing the complexity are often underestimated.

Hybrid strategies offer numerous benefits, such as increased flexibility, optimised performance, and enhanced disaster recovery capabilities. However, managing different cloud providers, each with its unique interface and operational management tools can be challenging.

The challenges of managing a hybrid IT environment are indeed multifaceted. Integration requires harmonising various technology services to work together seamlessly, which can be complex due to differing architectures and protocols. Security is another primary concern, as managing security across on-premises and multiple cloud providers necessitates consistent policies and vigilant monitoring to prevent breaches and ensure compliance. Additionally, efficiently utilising resources across hybrid clouds involves sophisticated monitoring and automation tools to optimise performance and cost-effectiveness. These challenges are real and pressing, and they demand attention and action.

Alarmingly, only 1% of organisations in Thailand plan to increase their investments in hybrid cloud management in 2024.

Organisations can ensure seamless integration, consistent security readiness, and efficient resource utilisation across diverse cloud platforms by investing in robust tools and practices for effective hybrid cloud management. This mitigates operational risks and security vulnerabilities and leads to cost savings due to well-managed cloud environments.

It’s crucial for CIOs in Thailand to urgently prioritise investing in new comprehensive management solutions and developing the necessary skills within their IT teams. This involves training staff on the latest hybrid cloud management technologies and best practices and adopting advanced tools that provide visibility and control over multi-cloud operations. Cracking the hybrid/multi-cloud code empowers CIOs to not only navigate these environments, but also unlock the potential of advanced technologies like AI, ultimately driving superior IT services and expanded business growth. The urgency of this task cannot be overstated, and the sooner you act, the better prepared your organisation will be for the future.

The Future of Work: AI Adoption for Enhanced Productivity

AI is a powerful tool for improving employee productivity and transforming internal operations.

However, only 12% of Thailand’s organisations invest in AI to enhance the employee experience.

This represents a missed opportunity for organisations to utilise AI’s potential to streamline processes, automate repetitive tasks, and provide personalised support to employees.

AI can significantly enhance operational efficiency by automating routine tasks, enabling staff to focus on strategic initiatives. For instance, AI-driven analytics platforms can process vast amounts of data in real time, providing actionable insights that help businesses make informed decisions quickly. AI frees employees to focus on higher-level tasks like developing innovative solutions and strategies. This empowers them to take on more strategic roles, fostering personal growth and career advancement.

The early adopters of AI in Thailand are already reaping the benefits, gaining significant competitive edge by enhancing employee productivity and satisfaction.

In Thailand AI adoption is gaining momentum within tech teams – 44% are exploring its potential for various use cases.

However, its capabilities extend far beyond. AI encompasses a wide range of technologies that can generate content, such as text, images, and code, based on input data. These versatile capabilities are not limited to tech teams, but can also be used for content creation, process automation, and product design in various industries. The success of these early adopters should inspire other Thailand organisations to consider AI adoption as a means to stay ahead in the market. 

The enthusiasm for AI has yet to extend beyond tech teams, with only 19% of business units considering its adoption.

This difference highlights an opportunity for CIOs in the country to play a crucial role in advocating for broader AI adoption across the organisation. By demonstrating the tangible benefits, such as increased efficiency, reduced costs, and enhanced innovation, CIOs can drive more widespread acceptance and use. Encouraging cross-departmental collaboration and training on AI applications can further support its integration across business operations. CIO leadership is crucial for successful AI adoption.

The Importance of a Collaborative Ecosystem

Together, we can navigate the intricacies of advanced technologies and foster innovation in Thailand organisation. These market trends should guide you on how to establish a resilient and adaptable IT infrastructure that facilitate long-term growth and innovation. Emphasising modernisation and the strategic use of AI will enhance operational efficiency and position your organisation to harness emerging technologies effectively, all while being part of a supportive and collaborative community. 

Stay tuned for more Ecosystm insights and guidance on navigating the Thailand technology landscape, ensuring your organisation remains at the forefront of digital transformation.

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Hyperscalers Ramp Up GenAI Capabilities

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When OpenAI released ChatGPT, it became obvious – and very fast – that we were entering a new era of AI. Every tech company scrambled to release a comparable service or to infuse their products with some form of GenAI. Microsoft, piggybacking on its investment in OpenAI was the fastest to market with impressive text and image generation for the mainstream. Copilot is now embedded across its software, including Microsoft 365, Teams, GitHub, and Dynamics to supercharge the productivity of developers and knowledge workers. However, the race is on – AWS and Google are actively developing their own GenAI capabilities. 

AWS Catches Up as Enterprise Gains Importance 

Without a consumer-facing AI assistant, AWS was less visible during the early stages of the GenAI boom. They have since rectified this with a USD 4B investment into Anthropic, the makers of Claude. This partnership will benefit both Amazon and Anthropic, bringing the Claude 3 family of models to enterprise customers, hosted on AWS infrastructure. 

As GenAI quickly emerges from shadow IT to an enterprise-grade tool, AWS is catching up by capitalising on their position as cloud leader. Many organisations view AWS as a strategic partner, already housing their data, powering critical applications, and providing an environment that developers are accustomed to. The ability to augment models with private data already residing in AWS data repositories will make it an attractive GenAI partner. 

AWS has announced the general availability of Amazon Q, their suite of GenAI tools aimed at developers and businesses. Amazon Q Developer expands on what was launched as Code Whisperer last year. It helps developers accelerate the process of building, testing, and troubleshooting code, allowing them to focus on higher-value work. The tool, which can directly integrate with a developer’s chosen IDE, uses NLP to develop new functions, modernise legacy code, write security tests, and explain code. 

Amazon Q Business is an AI assistant that can safely ingest an organisation’s internal data and connect with popular applications, such as Amazon S3, Salesforce, Microsoft Exchange, Slack, ServiceNow, and Jira. Access controls can be implemented to ensure data is only shared with authorised users. It leverages AWS’s visualisation tool, QuickSight, to summarise findings. It also integrates directly with applications like Slack, allowing users to query it directly.  

Going a step further, Amazon Q Apps (in preview) allows employees to build their own lightweight GenAI apps using natural language. These employee-created apps can then be published to an enterprise’s app library for broader use. This no-code approach to development and deployment is part of a drive to use AI to increase productivity across lines of business. 

AWS continues to expand on Bedrock, their managed service providing access to foundational models from companies like Mistral AI, Stability AI, Meta, and Anthropic. The service also allows customers to bring their own model in cases where they have already pre-trained their own LLM. Once a model is selected, organisations can extend its knowledge base using Retrieval-Augmented Generation (RAG) to privately access proprietary data. Models can also be refined over time to improve results and offer personalised experiences for users. Another feature, Agents for Amazon Bedrock, allows multi-step tasks to be performed by invoking APIs or searching knowledge bases. 

To address AI safety concerns, Guardrails for Amazon Bedrock is now available to minimise harmful content generation and avoid negative outcomes for users and brands. Contentious topics can be filtered by varying thresholds, and Personally Identifiable Information (PII) can be masked. Enterprise-wide policies can be defined centrally and enforced across multiple Bedrock models. 

Google Targeting Creators 

Due to the potential impact on their core search business, Google took a measured approach to entering the GenAI field, compared to newer players like OpenAI and Perplexity. The useability of Google’s chatbot, Gemini, has improved significantly since its initial launch under the moniker Bard. Its image generator, however, was pulled earlier this year while it works out how to carefully tread the line between creativity and sensitivity. Based on recent demos though, it plans to target content creators with images (Imagen 3), video generation (Veo), and music (Lyria). 

Like Microsoft, Google has seen that GenAI is a natural fit for collaboration and office productivity. Gemini can now assist the sidebar of Workspace apps, like Docs, Sheets, Slides, Drive, Gmail, and Meet. With Google Search already a critical productivity tool for most knowledge workers, it is determined to remain a leader in the GenAI era. 

At their recent Cloud Next event, Google announced the Gemini Code Assist, a GenAI-powered development tool that is more robust than its previous offering. Using RAG, it can customise suggestions for developers by accessing an organisation’s private codebase. With a one-million-token large context window, it also has full codebase awareness making it possible to make extensive changes at once. 

The Hardware Problem of AI 

The demands that GenAI places on compute and memory have created a shortage of AI chips, causing the valuation of GPU giant, NVIDIA, to skyrocket into the trillions of dollars. Though the initial training is most hardware-intensive, its importance will only rise as organisations leverage proprietary data for custom model development. Inferencing is less compute-heavy for early use cases, such as text generation and coding, but will be dwarfed by the needs of image, video, and audio creation. 

Realising compute and memory will be a bottleneck, the hyperscalers are looking to solve this constraint by innovating with new chip designs of their own. AWS has custom-built specialised chips – Trainium2 and Inferentia2 – to bring down costs compared to traditional compute instances. Similarly, Microsoft announced the Maia 100, which it developed in conjunction with OpenAI. Google also revealed its 6th-generation tensor processing unit (TPU), Trillium, with significant increase in power efficiency, high bandwidth memory capacity, and peak compute performance. 

The Future of the GenAI Landscape 

As enterprises gain experience with GenAI, they will look to partner with providers that they can trust. Challenges around data security, governance, lineage, model transparency, and hallucination management will all need to be resolved. Additionally, controlling compute costs will begin to matter as GenAI initiatives start to scale. Enterprises should explore a multi-provider approach and leverage specialised data management vendors to ensure a successful GenAI journey.

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The Next Frontier: Southeast Asia’s Data Centre Evolution

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ASEAN, poised to become the world’s 4th largest economy by 2030, is experiencing a digital boom. With an estimated 125,000 new internet users joining daily, it is the fastest-growing digital market globally. These users are not just browsing, but are actively engaged in data-intensive activities like gaming, eCommerce, and mobile business. As a result, monthly data usage is projected to soar from 9.2 GB per user in 2020 to 28.9 GB per user by 2025, according to the World Economic Forum. Businesses and governments are further fuelling this transformation by embracing Cloud, AI, and digitisation.

Investments in data centre capacity across Southeast Asia are estimated to grow at a staggering pace to meet this growing demand for data. While large hyperscale facilities are currently handling much of the data needs, edge computing – a distributed model placing data centres closer to users – is fast becoming crucial in supporting tomorrow’s low-latency applications and services.

The Big & the Small: The Evolving Data Centre Landscape

As technology pushes boundaries with applications like augmented reality, telesurgery, and autonomous vehicles, the demand for ultra-low latency response times is skyrocketing. Consider driverless cars, which generate a staggering 5 TB of data per hour and rely heavily on real-time processing for split-second decisions. This is where edge data centres come in. Unlike hyperscale data centres, edge data centres are strategically positioned closer to users and devices, minimising data travel distances and enabling near-instantaneous responses; and are typically smaller with a capacity ranging from 500 KW to 2 MW. In comparison, large data centres have a capacity of more than 80MW.

While edge data centres are gaining traction, cloud-based hyperscalers such as AWS, Microsoft Azure, and Google Cloud remain a dominant force in the Southeast Asian data centre landscape. These facilities require substantial capital investment – for instance, it took almost USD 1 billion to build Meta’s 150 MW hyperscale facility in Singapore – but offer immense processing power and scalability. While hyperscalers have the resources to build their own data centres in edge locations or emerging markets, they often opt for colocation facilities to familiarise themselves with local markets, build out operations, and take a “wait and see” approach before committing significant investments in the new market.

The growth of data centres in Southeast Asia – whether edge, cloud, hyperscale, or colocation – can be attributed to a range of factors. The region’s rapidly expanding digital economy and increasing internet penetration are the prime reasons behind the demand for data storage and processing capabilities. Additionally, stringent data sovereignty regulations in many Southeast Asian countries require the presence of local data centres to ensure compliance with data protection laws. Indonesia’s Personal Data Protection Law, for instance, allows personal data to be transferred outside of the country only where certain stringent security measures are fulfilled. Finally, the rising adoption of cloud services is also fuelling the need for onshore data centres to support cloud infrastructure and services.

Notable Regional Data Centre Hubs

Singapore. Singapore imposed a moratorium on new data centre developments between 2019 to 2022 due to concerns over energy consumption and sustainability. However, the city-state has recently relaxed this ban and announced a pilot scheme allowing companies to bid for permission to develop new facilities.

In 2023, the Singapore Economic Development Board (EDB) and the Infocomm Media Development Authority (IMDA) provisionally awarded around 80 MW of new capacity to four data centre operators: Equinix, GDS, Microsoft, and a consortium of AirTrunk and ByteDance (TikTok’s parent company). Singapore boasts a formidable digital infrastructure with 100 data centres, 1,195 cloud service providers, and 22 network fabrics. Its robust network, supported by 24 submarine cables, has made it a global cloud connectivity leader, hosting major players like AWS, Azure, IBM Softlayer, and Google Cloud.

Aware of the high energy consumption of data centres, Singapore has taken a proactive stance towards green data centre practices.  A collaborative effort between the IMDA, government agencies, and industries led to the development of a “Green Data Centre Standard“. This framework guides organisations in improving data centre energy efficiency, leveraging the established ISO 50001 standard with customisations for Singapore’s context. The standard defines key performance metrics for tracking progress and includes best practices for design and operation. By prioritising green data centres, Singapore strives to reconcile its digital ambitions with environmental responsibility, solidifying its position as a leading Asian data centre hub.

Malaysia. Initiatives like MyGovCloud and the Digital Economy Blueprint are driving Malaysia’s public sector towards cloud-based solutions, aiming for 80% use of cloud storage. Tenaga Nasional Berhad also established a “green lane” for data centres, solidifying Malaysia’s commitment to environmentally responsible solutions and streamlined operations. Some of the big companies already operating include NTT Data Centers, Bridge Data Centers and Equinix.

The district of Kulai in Johor has emerged as a hotspot for data centre activity, attracting major players like Nvidia and AirTrunk. Conditional approvals have been granted to industry giants like AWS, Microsoft, Google, and Telekom Malaysia to build hyperscale data centres, aimed at making the country a leading hub for cloud services in the region. AWS also announced a new AWS Region in the country that will meet the high demand for cloud services in Malaysia.

Indonesia. With over 200 million internet users, Indonesia boasts one of the world’s largest online populations. This expanding internet economy is leading to a spike in the demand for data centre services. The Indonesian government has also implemented policies, including tax incentives and a national data centre roadmap, to stimulate growth in this sector.

Microsoft, for instance, is set to open its first regional data centre in Thailand and has also announced plans to invest USD 1.7 billion in cloud and AI infrastructure in Indonesia. The government also plans to operate 40 MW of national data centres across West Java, Batam, East Kalimantan, and East Nusa Tenggara by 2026.

Thailand. Remote work and increasing online services have led to a data centre boom, with major industry players racing to meet Thailand’s soaring data demands.

In 2021, Singapore’s ST Telemedia Global Data Centres launched its first 20 MW hyperscale facility in Bangkok. Soon after, AWS announced a USD 5 billion investment plan to bolster its cloud capacity in Thailand and the region over the next 15 years. Heavyweights like TCC Technology Group, CAT Telecom, and True Internet Data Centre are also fortifying their data centre footprints to capitalise on this explosive growth. Microsoft is also set to open its first regional data centre in the country.

Conclusion

Southeast Asia’s booming data centre market presents a goldmine of opportunity for tech investment and innovation. However, navigating this lucrative landscape requires careful consideration of legal hurdles. Data protection regulations, cross-border data transfer restrictions, and local policies all pose challenges for investors. Beyond legal complexities, infrastructure development needs and investment considerations must also be addressed. Despite these challenges, the potential rewards for companies that can navigate them are substantial.

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