Gobi Partners, a leading Asian venture capital firm, has announced an undisclosed strategic investment in ArmourZero Holdings, a cloud-based cybersecurity platform based in Malaysia.

The investment, made through the Gobi Dana Impak Ventures (GDIV) fund, is backed by Khazanah Nasional and aligns with Khazanah’s Dana Impak mandate.

According to Tho Kit Hoong, CEO of ArmourZero, the investment will accelerate innovation.

Co-founded in 2022 by cybersecurity expert Hoong and tech innovator Chong Wai Lun, ArmourZero aims to address the cybersecurity needs of software developers and small and medium enterprises (SMEs).

Also Read: Embracing unity: A celebration of diversity and inclusion at ArmourZero

The platform tackles issues such as high cyber threat incidence, inadequate threat containment, prohibitive costs, and limited access to integrated security systems.

Key solutions:

ShieldOne: A unified threat monitoring, management, and response system. It integrates endpoint security, email protection, and patch management into a single platform. ShieldOne provides real-time threat protection, 24×7 Managed Detection and Response (MDR), and partners with industry leaders such as CrowdStrike and Checkpoint.

Managed Detection and Response (MDR): A core feature of ShieldOne, it offers real-time threat detection, proactive incident management, and rapid response through a dedicated team of cybersecurity analysts.

ScoutTwo: An AI-powered application security system that secures web and mobile applications from development to deployment. It provides instant vulnerability detection, risk prioritisation, and AI-powered remediation recommendations.

ArmourZero aims to bridge this gap by helping SMEs mitigate risks, reduce costs, and strengthen their digital defences. In Malaysia, over 28,000 cyberattacks were recorded in 2022, with incidents between 2017 and 2021 resulting in RM2.23 billion (US$490 million) in financial losses.

ArmourZero has subsidiaries in Malaysia, Singapore, and Indonesia. The company’s core activities are based in Malaysia.

The cybersecurity market in Southeast Asia is projected to grow from US$35 billion in 2023 to US$84 billion by 2028. SMEs, which make up 99 per cent of Malaysian businesses, are particularly vulnerable due to limited resources and awareness.

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As artificial intelligence (AI) continues to redefine industries and workplaces, concerns about job displacement persist. However, rather than rendering human workers obsolete, AI is expected to complement human capabilities—emphasising the need for uniquely human skills. A recent Workday study reveals that the tech will be a driving force behind a global skills revolution, making human-centric skills more valuable than ever.

The report elaborates how AI is playing an increasingly pivotal role in skill development by alleviating workers from routine processes and enabling them to focus on higher-order tasks. By automating repetitive activities, the tech allows individuals to channel their creativity and problem-solving abilities into more strategic and imaginative work.

Additionally, AI-driven skills assessment and gap analysis improve productivity by ensuring that employees receive targeted learning opportunities, making professional development more efficient and data-driven.

Beyond productivity gains, AI fosters adaptability and resilience—critical skills in an era of rapid technological change. By offering interactive learning experiences and processing vast amounts of data to provide insights and decision support, AI enhances employee engagement and professional growth. This empowerment extends beyond individuals, as the tech facilitates the exchange of information, making skills data actionable at scale and enabling businesses and governments to expand workforce opportunities.

AI excels at processing vast amounts of data, automating repetitive tasks, and enhancing efficiency. Yet, it lacks the nuanced understanding, empathy, and ethical reasoning that define human interactions. This is why several human-centric skills continue to remain relevant even in the age of AI, according to the report.

Also Read: Atome taps BlackRock, InnoVen for expanded US$80M credit facility

As organisations integrate the tech into their operations, the ability to navigate complex social dynamics, make ethical decisions, and lead with emotional intelligence will become essential. Employers are increasingly prioritising soft skills such as adaptability, collaboration, and critical thinking. These competencies enable individuals to work effectively with AI-driven tools, fostering innovation, enhancing teamwork, and maintaining a workplace culture built on trust and transparency.

Strategies for developing human-centric skills

To prepare for an AI-enhanced future, organisations and individuals must focus on skill development in key areas. Workday’s research highlights several strategies for strengthening human-centric capabilities:

1. Prioritising upskilling and reskilling

The evolving job market demands continuous learning. Businesses should invest in training programmes that enhance AI-related skills while reinforcing human strengths such as problem-solving, leadership, and adaptability. Employees who embrace lifelong learning will remain competitive in a shifting landscape.

2. Promoting human-machine collaboration

AI should be seen as a tool that enhances human capabilities rather than a replacement for human workers. By leveraging the tech for data-heavy tasks, employees can focus on strategic decision-making, creativity, and interpersonal relationships—areas where human intelligence is irreplaceable.

3. Strengthening communication and teamwork

AI can streamline workflows and facilitate collaboration, but strong interpersonal skills remain critical. Organisations should foster environments that encourage relationship-building, diverse perspectives, and collective problem-solving.

4. Cultivating human-centric leadership

Leadership in the AI age requires a shift toward empathy, emotional intelligence, and people-focused management. Effective leaders must balance AI-driven insights with human judgement, ensuring that employees feel valued, supported, and motivated.

5. Addressing skills gaps

A skills-first approach to talent development is essential. Organisations should identify gaps in human-centric competencies—such as ethical decision-making, cultural awareness, and resilience—and integrate these into training initiatives.

Also Read: Atome taps BlackRock, InnoVen for expanded US$80M credit facility

6. Building a culture of trust and transparency

For AI adoption to succeed, organisations must ensure transparency in AI-driven processes. Employees should have access to explainable AI systems and understand how technology impacts decision-making. Trust fosters a more inclusive and engaged workforce.

7. Encouraging ethical AI development

AI systems should align with ethical and organisational values. Businesses must equip employees with the skills to assess AI-driven decisions critically, ensuring fairness, accountability, and responsible technology use.

8. Strengthening critical thinking and problem-solving

AI can enhance analytical capabilities, but human judgment remains crucial. Training should emphasise creative reasoning, adaptability, and decision-making to ensure employees can interpret AI-generated insights effectively.

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Image Credit: Annie Spratt on Unsplash

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The artificial intelligence (AI) landscape is evolving rapidly, and DeepSeek’s emergence could have significant implications for AI adoption and market dynamics. Bain & Company’s latest analysis presents a range of potential scenarios, offering key takeaways for businesses and industry leaders navigating this transformation.

DeepSeek’s impact will likely unfold across three possible scenarios, ranging from bullish to bearish, depending on how AI infrastructure costs and investments develop.

Bullish scenario: Expanding AI adoption
In an optimistic outlook, ongoing efficiency improvements lead to cheaper inference costs, accelerating AI adoption in a phenomenon known as Jevons’ paradox.

As AI becomes more accessible, demand for high-end training and advanced models will remain strong, encouraging sustained investment in cutting-edge AI capabilities. This scenario envisions a future where businesses increasingly integrate AI into their operations, leading to a broader and more dynamic AI ecosystem.

Moderate scenario: Infrastructure cost reduction
A more measured scenario predicts that while AI training costs remain stable, spending on AI inference infrastructure could decline by 30 to 50 per cent. This shift would prompt cloud providers to scale back their capital expenditures from an estimated US$80 billion to US$100 billion annually to a range between US$65 billion and US$85 billion per provider.

Despite this reduction, the expenditure would still represent an increase over 2023 levels, suggesting continued growth but at a more controlled pace.

Also Read: Gobi invests in ArmourZero to bolster SME cybersecurity defences

Bearish scenario: Constrained investment
In the most cautious outlook, AI training budgets shrink significantly, and spending on inference infrastructure declines sharply. Cloud providers’ capital expenditures could drop to between US$40 billion and US$60 billion, a level that, while still higher than in 2023, signals a slowdown in AI infrastructure expansion.

If realised, this scenario could indicate a temporary cooling-off period in AI investment, potentially leading to more selective AI deployments and a focus on cost efficiency rather than aggressive expansion.

Strategic considerations for CEOs

Given the uncertainty surrounding DeepSeek’s impact, Bain & Company’s report offers strategic advice for CEOs who want to effectively navigate the evolving AI landscape.

Prepare for cost disruption
Businesses should anticipate a future where AI inference becomes significantly cheaper, creating new competitive dynamics. Companies that proactively adjust their strategies to leverage more cost-effective AI solutions will be better positioned to capitalise on the changes.

This includes reassessing existing AI budgets and exploring new AI-driven opportunities beyond cost reduction.

Monitor market signals closely
CEOs must stay attuned to industry trends, particularly capital expenditure patterns, GPU demand, and AI adoption rates. A slowdown in infrastructure spending may indicate that efficiency improvements are reshaping AI economics. Understanding these shifts can help businesses adapt their AI strategies accordingly.

Also Read: How upcoming CPI data could influence fed policy and cryptocurrency prices

Key market signals to watch include:
– Sustained enterprise demand for high-performance AI models.
– Increasing restrictions on AI model access and distillation controls by leading AI labs.
– Validation of cost-saving projections and the emergence of previously unaccounted-for expenses.
– Evidence that DeepSeek was trained on existing models, potentially influencing AI development strategies.
– Continued prioritisation of advanced, frontier AI models for training purposes.
– The rapid proliferation of derivative models and new competitors.
– The growing popularity of low-cost open-source models, which may accelerate AI adoption in diverse sectors.

Think beyond productivity
While many companies initially adopt AI to improve operational efficiency, Bain & Company advises businesses to go further by leveraging AI to redefine their core offerings. The most successful firms will be those that move beyond automation and embrace AI-driven innovation.

This could take the form of personalised customer experiences, AI-enhanced product development, or entirely new services that leverage AI capabilities.

Broader implications for the AI market

DeepSeek’s emergence is part of a larger trend in AI development, where open-source and cost-efficient models are gaining traction. If AI inference costs continue to decrease, it could democratise AI access, enabling smaller businesses and startups to integrate AI solutions that were previously cost-prohibitive.

This shift could lead to a more competitive and dynamic AI ecosystem, where innovation is driven not only by major tech firms but also by emerging players leveraging new AI models.

At the same time, concerns over model security, data integrity, and ethical AI development are likely to remain at the forefront. Companies must balance cost considerations with responsible AI implementation, ensuring that AI models are not only efficient but also aligned with regulatory and ethical standards.

DeepSeek represents a pivotal development in AI, with the potential to reshape how businesses approach AI adoption and investment. Whether the market follows a bullish, moderate, or bearish trajectory, companies must remain agile, closely monitoring cost trends and market signals while actively seeking ways to innovate beyond mere efficiency improvements.

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Image Credit: Mimi Thian on Unsplash

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Across Southeast Asia, from Singapore’s fintech hubs to Indonesia’s e-commerce powerhouses, startup founders are evaluating DeepSeek’s promise of democratising advanced AI capabilities at a fraction of traditional costs.

With performance levels reportedly matching industry giants like GPT-4 and Claude-3.5, DeepSeek’s emergence marks a potential turning point for regional startups traditionally priced out of cutting-edge AI development.

But as regional tech leaders and investors weigh its implications, a crucial question emerges: Could this be the catalyst that propels Southeast Asia’s startup ecosystem into AI’s next frontier?

We spoke with several VCs, AI experts, founders and top executives at AI startups to learn how DeepSeek will impact the local startup ecosystem.

Below are the insights they shared:

Mauro Sauco, CTO of Transparently.ai, an accounting fraud detection firm

DeepSeek has generated buzz for a good reason. Its innovative approach to AI model development is already influencing how large language models are built and could fundamentally reshape our future in AI.

That said, I tend to be cautious when technology is surrounded by so much hype. While DeepSeek’s approach is innovative and impressive, I’m still on the fence about who will truly benefit from it in the long run.

Also Read: DeepSeek: The smart disruptor in the AI race

Here are some of my thoughts:

The impact on the ecosystem:

DeepSeek’s advancements have advanced the state of the art in LLM development. However, major frontier model developers are likely to quickly adopt these innovations, which might diminish DeepSeek’s lasting competitive edge.

Who stands to benefit:

Frontier model developers are likely to gain the most from incorporating this innovative approach to AI model development, which will lower costs and drive further innovation.

a) Large enterprises: Companies with specialised requirements might fine-tune DeepSeek to better suit their needs.

b) Regulated industries: Organisations that need to operate models within a controlled, private infrastructure could find value in DeepSeek.

c) Startups: For most startups, the direct benefits appear limited. However, any potential benefits might come indirectly through cost reductions passed down from the savings that mainstream frontier model providers eventually deliver.

Practical considerations for startups:

I’ve personally tested DeepSeek on metal (referring to the model itself, not the service) and had my team run some preliminary tests. For startups like ours, the practical benefits—especially in terms of cost savings and performance improvements—don’t seem substantial:

a) Infrastructure demands: Running DeepSeek locally (or on VMs) requires significant memory and GPU resources to achieve acceptable latency.

b) Production complexity: Setting up a production-grade system means managing redundancy, availability, and global distribution.

c) Operational costs: The overall costs and operational burdens can add up quickly.

d) Cloud provider offerings: Although some cloud providers are now offering DeepSeek via hosted endpoints, the advantages are minimal. DeepSeek R1 might be on par with, or only slightly superior to, existing reasoning models. Given that mainstream frontier models are likely to integrate these advancements in the near term, the effort and cost of refactoring software—including prompts and evaluations—to accommodate DeepSeek don’t seem justified.

Advantages of mainstream frontier models:

One major advantage of using established frontier model providers is their continuous improvement. These companies invest heavily in enhancing their models, meaning that as users, we benefit from ongoing enhancements with minimal effort on our part. DeepSeek might struggle to match this, especially when pitted against the giants in the field.

In conclusion, DeepSeek marks a significant advancement in the LLM ecosystem with its innovative approach to AI model development. While it’s clear that DeepSeek has reshaped the way we will approach AI model development in the future, its broader impact is still unfolding. For startups, in particular, sticking with established API services remains the more practical and cost-effective choice given the continuous improvements and financial backing of major frontier model providers.

Alvin Toh, co-founder of Straits Interactive, a data protection startup

DeepSeek’s affordability and accessibility democratise artificial intelligence (AI), making it attractive to ASEAN startups. Its low-cost, high-performing models enable developers in companies to rapidly prototype and integrate it into their technology stack and allow startups to innovate in various fields without prohibitive infrastructural investments.

However, there are concerns surrounding DeepSeek’s higher level of hallucination compared to other models in the market (notably, in following rules, writing, creativity, and persuasiveness) and certain biases from China in its outputs.

Additionally, DeepSeek’s ambiguous privacy policies and lack of robust compliance certifications bring pause. Its privacy policy lacks clarity on data usage, causing unease about data leakage and misuse. There is also no explicit mention of adherence to key international standards like GDPR, making it risky for startups operating in regulated industries.

Moreover, recent attempts by security researchers at Cisco and the University of Pennsylvania to jailbreak Deepseek’s model with adversarial prompts revealed that it failed to block all 50 attempts, indicating that there’s still a security gap in deployment.

Startups handling regulated, sensitive, or proprietary data must, therefore, carefully evaluate DeepSeek’s scalability and adherence to privacy laws, policies, and service-level agreements (SLAs). Compliance with local regulations, like the PDPA for Singapore-based outfits, needs to be ensured before integrating DeepSeek into critical workflows.

Until DeepSeek provides stronger assurances of data privacy and compliance, startups should presently avoid using it with sensitive data and consider alternatives with a privacy-first approach.

Rei Murakami, Venture Partner at Kadan Capital

DeepSeek has delivered a few important AI milestones: In December, version 3 was released with Mixture-of-Experts architecture, faster inference, and longer context windows, followed by the R1 model in January. But let’s be clear: the real story isn’t about one company.

LLMs are on a path to commoditisation, with open source gaining momentum. I believe the recent negative public market reaction is misplaced. In the mid-term, AI adoption is about to dramatically increase. History proves it; back in 1943, IBM’s Thomas Watson infamously predicted a world market for not more than five computers. When costs decreased, demand skyrocketed. The same is now happening with AI.

Also Read: DeepSeeking the future: The ripple effect on tech, crypto, and global markets

Nowhere is this shift more significant than in Southeast Asia. In emerging economies, SaaS solutions struggled with monetisation due to low labour costs. But with token costs set to drop, autonomous agents will become viable even in price-sensitive markets. The AI revolution isn’t slowing—it’s just getting started.

We continue to be excited about application layer AI, particularly in vertical SaaS, where AI can unlock entirely new business models and drive real operational impact.

Dr Sze Tiam Lin, Senior Licensing Advisor, SMU Institute of Innovation & Entrepreneurship

DeepSeek enables startups in Southeast Asia to harness cutting-edge generative AI technologies without the need for massive budgets and push the boundaries of what’s possible, offering a more dynamic and competitive landscape for innovation. It also allows smaller players to adopt efficient inference systems and benefit from significantly reduced training costs, making it easier to develop sophisticated AI solutions.

DeepSeek stands out in its efficient pre-training that accelerates the learning process and shortens the time required to deploy customised and powerful AI models. With performance levels on par with the best versions of GPT-4 and Claude-3.5, startups can harness high-level capabilities at a fraction of the cost.

Additionally, DeepSeek’s unique voting technique offers self-feedback on open-ended questions, enhancing the effectiveness and robustness of the alignment process, a critical factor in refining AI systems.

The pace of adoption across Southeast Asia will depend on the governance frameworks in place regarding the use of open-source models and data privacy in commercial deployments. Different jurisdictions may have varying regulatory environments, and this could affect innovation and AI adoption.

Matt Spriegel, CEO and founder of Atiom, an AI-powered gamified platform

Southeast Asia has been a hub for rapid digital adoption, and DeepSeek is lowering the barrier for startups to leverage AI early in their journey. From customer service automation to deep-learning analytics, its entry democratises access to AI, making advanced technology more accessible to early-stage companies.

Startups will have more access to AI without heavy R&D costs, which will also accelerate innovation. In particular, AI-first startups, especially in fintech, e-commerce and healthtech will likely experience accelerated growth.

Scalable AI solutions will also help startups to compete globally. This will impact the ecosystem, which will experience a surge in demand for more AI engineers, data scientists and machine learning (ML) specialists.

Furthermore, DeepSeek’s launch signals a shift in AI development beyond Western dominance. As more models are built and trained locally, we’ll see AI solutions tailored to Southeast Asia’s unique market needs, driving industry-specific innovation across the region.

Simon Davis, founder and CEO of GOAT Gaming, an AI-powered network of games on Telegram

DeepSeek’s emergence represents a transformative moment for Southeast Asia’s technology landscape, fundamentally altering the economics of AI deployment in the region. By dramatically reducing infrastructure costs for AI implementation, it levels the playing field for smaller companies that previously couldn’t compete due to resource constraints.

The ability to run these models locally is particularly significant for Southeast Asian startups. Not only does it slash operational costs, but it also addresses crucial data sovereignty concerns that have historically complicated AI adoption in the region. Companies can now process sensitive data on their own servers, ensuring compliance with local privacy regulations without compromising AI capabilities.

This cost-effective, local-first approach opens up exciting possibilities for market-specific AI solutions. In Indonesia, for instance, companies can now realistically develop specialised models tailored to the unique cultural nuances of the market. This localisation potential extends across Southeast Asia’s diverse markets, where one-size-fits-all solutions often fall short.

The implications are profound. We might see a surge of innovative AI applications emerging from previously underserved markets. This democratisation of AI technology could catalyse a new wave of regional innovation, powered by companies that understand their local markets intimately.

Nitin Vyas, Sr. VP (Product & Data) at RedDoorz, a budget hotel network

As a hospitality technology company, we view the emergence of DeepSeek as part of the industry’s ongoing evolution and also making AI a level-playing field for everyone.

DeepSeek, as an entity focused on AI and advanced technology solutions, represents an opportunity to enhance operational efficiency, personalise services, and elevate customer experiences in the hospitality sector. A healthy competition among the AI giants will be beneficial for this industry as it gives a more balanced global view of how AI will shape the course of our civilisation.

Also Read: AI, personalisation, and 5 marketing activities you should be doing

This competition may enable corporations to implement AI more cost-effectively. At the same time, we could see an even faster pace of innovation and more advanced capabilities in the large language model (LLM).

Remi Choong, Elev8.vc, a VC firm

Cost-effective AI infrastructure: Increasingly cost-effective models, such as DeepSeek’s, will lower API costs. This enables AI startups to deliver cheaper and better solutions, similar to the disruptions we’ve seen in the solar panel industry.

Stronger demand for AI: With more affordable options, global AI adoption and spending will likely surge. Southeast Asian startups must quickly adapt to agile go-to-market strategies to capture the growing demand, particularly among SMEs.

Competition: Given lower AI costs, it is increasingly important for companies to adopt AI to maintain a competitive advantage. We can also expect to see an uptick in adoption across a broad spectrum of industries.

Balancing AI and hard tech: Investors need to ensure a balance between funding cutting-edge AI ventures and the infrastructure that supports them, especially in countries like Singapore with strong hard tech capabilities.

Jeff Pan, Belli.ai, which builds air cargo software for airlines

Speaking broadly, it’s unlikely that you’ll see the same velocity of change in Southeast Asia as you do in the EU/US, primarily due to the types of problems that we are solving.

Founders in the EU/US typically deal with high-capability customers who already have high internal capabilities and large IT budgets. In contrast, founders in Southeast Asia typically deal with early digitisation problems (helping low-capability customers with small IT budgets transition from paper and spreadsheets to basic CRUD applications), which will largely be unaffected by the cutting-edge progress you see being made by DeepSeek.

Much of the impact you will see (which is already happening) is that teams can generate 10x more impact with smaller teams, which you will see play out in (a) less hiring demands from startups, who don’t need as much headcount and (b) VC funds skewing away more towards top 10 per cent founders who can seize on these advantages rather than a broader base of portfolio companies.

Nofi Bayu Darmawan, founder and CEO of Komerce, an e-commerce enabler

The promise of AI in simplifying tasks and creating value, especially in the context of cost-effectiveness is huge.

When it comes to e-commerce, the impact of generative AI on customer engagement, especially its role in social media interaction, e-commerce, and automating customer service, is massive. DeepSeek can consolidate brand knowledge and communication across various platforms, including Google reviews and online chat on websites, enhancing the commerce ecosystem.

Warren Leow, CEO of Designs.ai

Deepseek has sparked a lot of interest because its progress has lowered service costs. This spurs more innovation and adoption among users as barriers to adoption are reduced.

In addition, having more choices across different vendors and technology providers, especially from open source, will only spur further improvements in the quality of applications being produced.

 

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The Asia Pacific was once primarily recognised for its kaleidoscope of cultures, but today, it’s increasingly synonymous with groundbreaking tech developments. A gradual shift in the global order has led many to reconsider the vast opportunities that APAC, with its blend of mixed economies, traditions, and lifestyles, has to offer.

While the US—particularly Silicon Valley—has long been seen as the epicentre of tech and innovation, the momentum is now steadily shifting eastward. The reasons are clear: maturing economies, improved mobility, and greater accessibility have positioned APAC as one of the most fertile grounds to test ideas and tap into emerging markets.

Take Indonesia’s rural areas, for example, where efforts to democratise financial services stand in stark contrast to the sophisticated fintech landscape of Singapore, a city-state with a financially savvy populace. Yet Singapore, with its reliance on imports and limited land for waste, faces unique sustainability challenges that are driving a shift toward a circular economy. Meanwhile, in Japan, an aging population is accelerating the development of health tech and medtech, spurred by a staunch focus on well-being.

These examples are just the tip of the iceberg. Across the region, a surge of innovation is not just changing industries but reshaping everyday life in profound ways. The scope and scale of what’s unfolding are unparalleled, making APAC a pivotal space for the future of global innovation.

To further shed light, here are eight tech trends defining APAC in 2024:

Artificial intelligence goes vertical

The initial buzz around AI revolved around its potential for general-purpose tasks, like chatbots—think OpenAI’s ChatGPT, Anthropic’s Claude, and Baidu’s Ernie Bot. However, these broad applications often fall short in meeting the intricate demands of specific industries. This gap is giving rise to vertical AI, where models are tailored to specific needs.

• Adopt industry-specific AI: Businesses should evaluate the benefits of customising AI models to address the unique challenges of their industry, ensuring precision and relevance.
• Leverage local expertise: Engaging with regional AI ecosystems can provide the cultural and market-specific insights needed to refine these solutions effectively.
• Invest in tools: To fully capitalise on vertical AI, invest in technologies that enhance data organisation and accessibility—crucial for AI model training.

Self-driving revolution

The thought of cruising through the streets of Jakarta or Bangkok without the frustration of gridlock seems far-fetched now, but autonomous vehicles could soon make it a reality. Beyond reducing traffic, self-driving technology promises to enhance road safety and mobility, especially for the elderly and disabled.

Also Read: ‘AIR’ review: 3 lessons for dealmaking and entrepreneurship

• Initiate pilot projects: Companies in logistics and urban planning should collaborate to test the viability of autonomous vehicles in high-traffic cities.
• Expand and integrate services: Explore how self-driving technology can complement existing mobility services, enhancing efficiency and accessibility.
• Keep compliant: Companies venturing into this space should stay aligned with evolving regulations to maintain public trust and ensure safe implementation.

Electrification is the future

As the global push for sustainability accelerates, the shift to electric vehicles is becoming inevitable. With rising energy demands and international commitments like those from COP28, the transition from fossil fuels to renewable energy sources is gaining momentum.

• Be the first mover: Proactively invest in technologies that facilitate the transition to renewable energy, positioning your company as a leader in the field.
• Scale up infrastructure: Prioritise the development of EV charging networks to support widespread adoption and operational efficiency.
• Collaborate beyond borders: Engage in cross-border partnerships to access a wider array of sustainable innovations that fit your operational needs.

Humanoid robots near commercialisation

Robotics is no longer confined to assembly lines or science fiction. Humanoid robots, capable of replicating human movements and decisions, are on the verge of widespread adoption, bringing unprecedented efficiency and adaptability to various industries.

• Identify use cases: Businesses should assess which areas would benefit most from humanoid robots, starting with controlled environments like manufacturing.
• Partner with innovators: Collaborate with companies to ease the integration of robotics into your operations, even if your business has no prior experience.
• Prepare for workforce transition: Develop comprehensive training programs to ensure your workforce adapts smoothly to robotic assistance.

Easier, more convenient payments

Despite advancements in financial literacy and services, many still struggle with access—particularly in regions where traditional financial systems exclude those without formal credit histories or who live in remote areas. Overcoming these barriers is essential for economic equality and broader participation in the financial ecosystem.

• Broaden financial access: Financial companies should consider developing inclusive products, such as buy now, pay later (BNPL) services, to cater to underserved populations.
• Streamline transactions: Focus on enhancing cross-border payment processes through strategic partnerships and technology adoption.

Cradle-to-cradle

The depletion of natural resources is a critical challenge that threatens both the environment and future economic stability. Shifting from a linear economy to a cradle-to-cradle approach—where materials are continuously reused—is no longer optional, but necessary.

Also Read: Exploring the rise of finance-as-a-service in APAC

• Embrace circular practices: Integrate recycling and reuse into your production processes to align with cradle-to-cradle principles.
• Engage in regional initiatives: Participate in frameworks like ASEAN’s circular economy initiatives to align with broader sustainability goals.
• Invest in sustainable innovation: Prioritise R&D in technologies that transform waste into valuable resources, ensuring long-term environmental and economic resilience.

Syncing data on the edge

As digitalisation sweeps across industries, the need for high-speed, low-latency networks has never been greater. The explosion in internet and mobile usage, combined with the integration of AI and IoT, is pushing traditional networks to their limits.

• Adopt edge computing: Reduce latency and improve real-time data processing by integrating edge computing into critical applications.
• Accelerate 5G rollout: Companies should expedite the deployment of 5G networks to meet the growing demands of connectivity.
• Explore alternative technologies: Consider innovative solutions like laser-based communication to complement traditional network infrastructures.

Taking a quantum leap

Nvidia’s rise highlights the critical role of semiconductors, but the limitations of traditional computing, dictated by Moore’s law, are becoming evident. Quantum computing offers a way forward, promising to solve complex problems exponentially faster than classical systems.

• Invest in quantum research: Stay competitive by keeping abreast of the latest developments in quantum computing, which will impact most industries.
• Develop quantum-ready solutions: Begin bridging the gap between classical and quantum computing to ensure a smoother transition as the technology matures.

The seismic shifts in APAC’s tech landscape are more than just emerging trends—they are redefining the future of global innovation. From AI specialisation to the rise of electric mobility and quantum breakthroughs, these developments present both challenges and unparalleled opportunities.

To explore these trends in greater depth and understand their far-reaching impacts, join us at GITEX Asia from April 23–25, 2025, at Marina Bay Sands, Singapore. This event is where the future takes shape, and where you can engage directly with the minds and technologies driving these changes. Be there to witness, contribute, and lead.

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This article was first published on November 5, 2024

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