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Why Businesses Struggle to Adopt Generative AI in Asia

Uncover key hurdles to generative AI adoption in Asia. Explore solutions and considerations for businesses looking to harness its power.

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Generative AI Adoption in Asia

TL;DR

  • Companies are struggling to adopt generative AI in Asia due to security concerns, unclear use cases, talent shortages, low model maturity, and evolving regulations.
  • Less than 40% of organisations have successfully deployed an AI project, highlighting the challenges of implementation.
  • Staying informed about AI advancements and addressing these barriers is crucial for successful AI adoption.

Speedbumps on the Road to Success in Asia

Generative AI, a branch of artificial intelligence (AI) focused on creating new content, holds immense potential for businesses across various industries in Asia. However, despite the enthusiasm, many companies are encountering significant hurdles hindering their AI adoption journey. This article explores the key roadblocks currently impeding the widespread adoption of generative AI in Asia, along with potential solutions and future considerations.

Navigating the Maze of Cybersecurity Threats

One of the most prominent concerns surrounding generative AI adoption is the rise in cybersecurity threats. These AI-powered models, particularly those utilizing large language models (LLMs), introduce a new layer of vulnerabilities that traditional security measures might not adequately address.

According to a study by Foundry and Searce, a staggering 58% of respondents identified data security as a primary barrier to AI adoption. Jake Williams, a cybersecurity expert at IANS Research, emphasises the lack of understanding regarding the unique security risks associated with AI applications. He highlights the need for specialised security training and certifications tailored to AI, as existing tools in this domain are still under development.

Companies can mitigate these risks by prioritising threat modelling specific to their AI applications and actively seeking to educate their teams on AI security best practices.

Finding the Right Use Case: Balancing Impact and Complexity

Another significant barrier to generative AI adoption is the struggle to identify suitable use cases with a clear return on investment (ROI). Many businesses lack a strategic approach, often selecting use cases that are either too ambitious or offer minimal impact, ultimately leading to project failures and organisational skepticism.

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Vrinda Khurjekar, a senior director at Searce, emphasises the importance of establishing an AI council to streamline the selection process. This council, comprised of representatives from various departments, can comprehensively assess the organization’s needs and prioritize high-impact use cases with achievable complexity. By prioritising use cases strategically, businesses can ensure a smoother adoption process and maximise the potential benefits of generative AI.

Addressing the Talent Gap: Building a Strong Generative AI Workforce in Asia

The scarcity of skilled professionals in the AI field poses another significant challenge to widespread adoption. The rapid pace of technological advancements makes it difficult for organizations to attract and retain top talent, hindering their ability to effectively launch and manage AI initiatives.

Khurjekar suggests that companies should invest in proactive talent acquisition strategies and implement training programs to equip their existing workforce with the necessary AI skills. This comprehensive approach can help organisations build a robust AI talent pipeline and overcome the limitations imposed by the current talent shortage.

Mitigating Hallucinations When Adoption Generative AI in Asia

The limited maturity of current generative AI models can also impede adoption. These models are susceptible to “hallucinations,” where they generate factually incorrect outputs due to limitations in their training data or algorithms. This unreliability can be particularly concerning for industries like healthcare and finance, where accuracy is paramount.

Khurjekar acknowledges this challenge and anticipates that model maturity will improve over time. However, companies in sectors demanding high precision may need to exercise caution and adopt a wait-and-see approach until these models become more reliable.

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Regulatory Uncertainty and an Evolving Landscape

The evolving regulatory landscape surrounding AI also presents a hurdle to adoption. As AI technology is still nascent, regulatory bodies are still formulating guidelines and policies to govern its responsible implementation. This uncertainty can deter businesses, particularly those operating in highly regulated industries, from embracing AI due to the potential for future regulatory changes that might necessitate costly adjustments.

Khurjekar suggests that companies stay informed about regulatory developments and maintain a flexible approach to adapt to evolving policies. By closely monitoring the regulatory landscape, businesses can make informed decisions regarding AI adoption while minimising the risk of future disruptions.

Conclusion: Embracing Continuous Learning for a Successful AI Journey

In conclusion, while generative AI offers immense potential for businesses in Asia, several significant roadblocks currently hinder its widespread adoption. These challenges include cybersecurity concerns, unclear use cases, talent shortages, low model maturity, and evolving regulations.

Companies can overcome these hurdles by prioritising security measures, adopting a strategic approach to use case selection, investing in talent development, acknowledging model limitations, and staying informed about regulatory updates. Ultimately, successful generative AI adoption in Asia requires a continuous learning mindset and a commitment to adapting to the ever-evolving technological landscape.

Do you believe the potential benefits of generative AI outweigh the challenges it presents, or should businesses in Asia proceed with caution? Share your thoughts in the comments below!

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Will AI Take Your Job—or Supercharge Your Career?

AI-driven job disruption is already here. Discover practical steps for workers in Asia to stay employable, relevant, and ready for the future.

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AI job disruption

TL;DR – What You Need to Know in 30 Seconds

  • Generative AI is already reshaping careers, causing job losses in industries from finance to creative roles.
  • Workers must continually upskill, strategically plan career moves, and focus on roles AI complements rather than replaces.
  • Companies and governments must significantly increase retraining efforts to help workers adapt effectively.

Is AI About to Steal Your Job? Here’s How to Stay Ahead in Asia

For many, AI started as a helpful assistant for menial tasks, quick research, or even generating funny memes. But today, it’s taking a serious turn, reshaping industries, displacing jobs, and changing careers overnight.

Just ask Jacky Tan. After thriving for over 15 years as a freelance marketing consultant in Singapore, Jacky found his livelihood disrupted—not just by the pandemic—but by generative AI tools like ChatGPT, which empowered his clients to produce their own content. The result? Jacky, along with countless others, faced a stark choice: adapt quickly or risk becoming obsolete.

Jacky pivoted completely, leaving marketing to open a successful home-based food business, CheekyDon, specialising in Japanese rice bowls. But not everyone can—or will—reinvent themselves so easily. As AI continues to infiltrate the workforce, what can you do to ensure you’re prepared?

Job Disruption: More Real Than Ever

It’s no longer theoretical. Meta, ByteDance, DBS Bank, Grab, and Morgan Stanley have all announced layoffs or workforce reshuffling directly linked to AI-driven efficiencies. Analysts predict as many as 200,000 banking jobs globally could vanish within five years due to AI, highlighting sectors like finance, customer service, risk management, and tech as especially vulnerable.

The numbers don’t lie: The World Economic Forum anticipates 11 million new AI-related jobs globally by 2030—but 9 million existing roles will disappear. And the shift won’t just hit repetitive tasks. Highly skilled roles like writers, programmers, PR professionals, and even legal experts face substantial disruption.

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Why AI Displaces Jobs—and Creates New Ones

Here’s the paradox: while AI promises increased productivity, it often leads to job losses because current skills don’t match the needs of new AI-augmented roles. Retraining existing workers is crucial but challenging. In places like Singapore, where skilled workers are scarce, companies struggle to balance the speed of AI integration with retaining talent.

The good news? Jobs involving deep human interactions, emotional intelligence, strategic thinking, or managing AI tools themselves remain safer—for now.

How to Stay Relevant in an AI-Dominated Market

So, how can you protect your career from being displaced by AI? Here are actionable steps tailored for the rapidly shifting Asian job market:

1. Continuous Upskilling Is Non-Negotiable
The days of one-off training are over. Commit to lifelong learning by acquiring skills in AI-related fields, from data analytics to AI management tools. Invest in soft skills—like critical thinking, empathy, and strategic communication—which AI struggles to replicate effectively.

2. Proactively Plan Your Next Career Move
Ask yourself, as EY’s Samir Bedi suggests: “What am I upskilling for?” Plan two or three career steps ahead, not just for immediate skill gaps. Explore lateral career transitions that diversify your skillset, making you versatile across industries.

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3. Look for Roles Complemented by AI, Not Replaced by It
Jobs with tasks AI can augment rather than entirely replace—like managing automated systems, strategic marketing, or roles that require significant human touchpoints—are safer bets.

Employers Must Step Up, Too

The responsibility doesn’t rest solely on workers. Companies must actively retrain employees to handle AI disruptions effectively. Currently, only around half of Singaporean workers feel their employers provide sufficient training opportunities. Organisations that actively support their teams through retraining will reap long-term rewards, maintaining both institutional knowledge and market reputation.

Asia’s Workforce at the Crossroads

We’re facing nothing less than the Fourth Industrial Revolution, driven by generative AI. Unlike previous waves of automation, AI can replace tasks once thought too complex or creative for machines. But remember, while AI might take your current role, it also opens doors to entirely new career paths—provided you’re ready to step through them.

Are you prepared to let AI shape your future—or will you shape your own future with AI? Let us know in the comments below!

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The Three AI Markets Shaping Asia’s Future

Explore the three interconnected AI markets shaping Asia’s technological landscape—traditional AI, training infrastructure, and enterprise solutions—and discover how each drives innovation.

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AI markets

TL;DR – What You Need to Know in 30 Seconds

  • AI isn’t one monolithic market—it’s three interconnected segments:
  • 1. Pre-GenAI (traditional AI): Fundamental techniques that underpin data-driven solutions.
  • 2. AI Training Market: Resource-intensive frontier models driving the next AI breakthroughs.
  • 3. Enterprise AI Market: Real-world applications delivering measurable business outcomes.
  • Understanding their interplay is critical for Asian businesses aiming to maximise ROI from AI investments.

Are We Missing the Bigger Picture in the AI Race?

From smarter chatbots to insightful analytics, AI’s not one market—it’s three interconnected ones, each shaping how Asia leverages technology.

If you’ve spent any time recently skimming headlines about artificial intelligence, you’d be forgiven for thinking that generative AI is the only show in town. But AI isn’t just ChatGPT, Midjourney, or flashy avatars of celebrities endorsing your new favourite tech gadget. Behind the scenes, three distinct but intertwined markets are at play: the Pre-GenAI Market, the Training Market, and the Enterprise AI Market.

But what exactly are these three markets, and why should Asian businesses care?

Let’s unpack them one by one and understand how they converge to drive the future of innovation across Asia.

1. The Pre-GenAI Market: The Building Blocks of AI

Generative AI may be the current media darling, but the roots of AI go far deeper. We’re talking about traditional AI—technologies like machine learning (ML), reinforcement learning, and computer vision. These foundational techniques have been quietly evolving for decades, long before ChatGPT ever typed out its first response.

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Contrary to popular belief, traditional AI hasn’t lost its relevance—far from it. In fact, the rise of generative AI has amplified its importance. Why? Because generative AI feeds on data often produced by traditional AI methods. For instance, Dell Technologies frequently uses machine learning to streamline supply chains or improve factory efficiency. These methods don’t get less important just because GPT-5 is around the corner—they become essential.

In short, traditional AI is like rice in Asian cuisine—fundamental, reliable, and always necessary, no matter what fancy new dish appears on the menu.

2. The Training Market: Powering AI’s Frontier

Next up is the AI training market—think of it as AI’s heavy lifting division. This market is dominated by big names you’ll recognise (OpenAI, Google DeepMind, Nvidia, Meta) who are making gigantic investments in infrastructure to create foundational AI models. Picture rows and rows of servers, massive GPU clusters, and sprawling data centres, humming 24/7.

These frontier models—like GPT-4 or Gemini—require immense computational resources. This isn’t just about bragging rights; it’s about pushing the boundaries of what AI can do. The innovations here spill directly into practical tools businesses use every day, like AI-driven coding assistants or creative platforms for content creation.

In Asia, we’re seeing heavy investment in this market too. Take Singapore’s AI supercomputing initiatives or China’s Baidu and Alibaba building mega-AI clusters. These moves aren’t just technological vanity—they’re strategic investments in the future.

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3. The Enterprise AI Market: Real-World Results

And then there’s the enterprise AI market, arguably the most pragmatic of the three. Enterprises aren’t racing to build the next ChatGPT killer. Instead, they’re laser-focused on AI that solves real business problems—like optimising inventory management, enhancing customer support, or boosting marketing effectiveness.

Unlike the flashy training market, the enterprise market moves slower but deliberately. Enterprises demand reliability, compliance, and measurable outcomes—exactly the opposite of the ‘move fast and break things’ mentality we see in frontier AI research.

Across Asia, the enterprise AI market is thriving precisely because it offers clear returns. Banks in Indonesia deploy AI-driven chatbots to handle customer queries efficiently. E-commerce giants in Vietnam and Thailand integrate predictive analytics to forecast inventory and customer demand. It’s AI that’s practical, measurable, and directly linked to ROI.

How These AI Markets Interconnect

Here’s the real takeaway: These three markets aren’t isolated islands; they’re deeply interconnected ecosystems.

Traditional AI gathers and prepares the essential data. The training market produces foundational AI models and cutting-edge tech innovations. Enterprises then integrate both, using these tools and data to transform operations and customer experiences.

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Think about it this way: traditional AI builds the roads, the training market crafts powerful engines, and the enterprise market drives the cars, delivering real-world value. Without any one of these, the system falters.

For instance, enterprises use AI-powered data agents to analyse massive datasets prepared by traditional AI methods. They then leverage frontier AI models (like generative AI) trained in data centres to extract actionable insights. The whole system is interdependent—each component driving progress in the other.

Why Does This Matter to Asia?

Asia is a unique melting pot of digital maturity, economic growth, and competitive intensity. Understanding these three markets isn’t just academic—it’s crucial for businesses looking to harness AI’s full potential.

For instance, enterprises in Southeast Asia’s rapidly expanding digital economy (expected to hit $263 billion GMV by 2025 according to Google’s recent e-Conomy SEA 2024 report) need practical AI solutions that deliver immediate business value. On the other hand, countries like Singapore, South Korea, and Japan are leading investments into the training market, building the infrastructure needed to power Asia’s next generation of AI innovations.

Simply put, knowing how these three AI markets interact helps Asian businesses invest smarter, act faster, and innovate effectively.

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As we look ahead, Asia is uniquely positioned to benefit from understanding this AI ecosystem deeply. Whether you’re in manufacturing, finance, e-commerce, or healthcare, your business will inevitably interact with all three markets—whether you realise it or not.

Now, here’s something for you to ponder (and comment below!):

Which of these AI markets do you think will dominate Asia’s tech landscape by 2030? Will traditional methods endure, frontier models take over, or will enterprise solutions reign supreme?

We’d love to hear your thoughts.

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Embrace AI or Face Replacement—Grab CEO Anthony Tan’s Stark Warning

ChatGPT now generates previously banned images of public figures and symbols. Is this freedom overdue or dangerously permissive?

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Anthony Tan AI Grab

TL;DR – What You Need to Know in 30 Seconds

  • Grab CEO Anthony Tan believes workers and companies that don’t embrace AI risk being replaced by those who do.
  • Grab paused normal operations for a nine-week generative AI sprint, significantly boosting innovation.
  • AI tools developed by Grab, such as driver and merchant assistants, are empowering everyday entrepreneurs.
  • Globally, many companies are downsizing due to AI, but Tan insists AI enhances human capabilities rather than replacing them.

Is Your Refusal to Embrace AI Secretly Sealing Your Fate?

Anthony Tan, co-founder and CEO of Grab—the Southeast Asian super-app that transformed regional transport, food delivery, and financial services—has made a bold and slightly unsettling prediction: “Humans who don’t embrace AI will be replaced by humans who embrace AI.”

In other words, whether you’re a company or an individual, ignoring AI isn’t merely shortsighted—it’s career suicide.

But before we panic, what exactly does Tan mean?

Making Humans ‘Superhuman’

Speaking at Converge Live in Singapore, Tan explained to CNBC’s Christine Tan that AI isn’t just a fancy tech upgrade. Instead, it’s a crucial tool to “make you superhuman” by significantly boosting productivity and freeing up valuable time.

Tan himself isn’t just preaching—he’s practising. Despite not being a coder, he’s enthusiastically using AI coding assistants for personal and professional projects. He claims AI has radically changed his productivity, helping him accomplish things previously impossible.

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I can’t code myself, but I use AI to build my own projects, for research, for Grab,” Tan explained. “It totally changes how you spend your time.
Anthony Tan, Grab CEO
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Grab’s Radical AI Experiment

Grab didn’t stop at encouraging individual AI adoption. Instead, the company took it to a whole new level, implementing an ambitious, company-wide nine-week “generative AI sprint”.

This meant putting all regular business on pause to explore AI-driven solutions across the entire company. As Tan humorously admitted:

People thought I was crazy—maybe I am—but it really moved the needle.
Anthony Tan, Grab CEO
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During this sprint, Grab developed powerful AI tools, including:

  • Driver Co-pilot: An AI assistant reducing wait times and boosting job opportunities for drivers.
  • Merchant AI Assistant: Imagine a single mother in Jakarta now equipped with an AI-driven sous chef, packaging expert, and even a chief revenue officer—all in one assistant. This innovation isn’t just about efficiency; it’s empowerment, reshaping the livelihoods of Grab’s vast network of entrepreneurs.

The Wider Implications for Asia

This isn’t just a Grab-specific phenomenon. According to the World Economic Forum’s 2025 Future of Jobs Report, 40% of employers globally plan to downsize due to AI, and a whopping 86% anticipate AI reshaping their businesses by 2030.

Asia, in particular, with its digitally fluent workforce and vibrant entrepreneurial scene, stands uniquely poised to lead this transition. Grab’s aggressive AI strategy under Tan’s leadership could become a model for businesses across Southeast Asia, showcasing how AI can be harnessed responsibly and productively.

Human vs AI: Not a Zero-Sum Game

Tan stresses AI shouldn’t evoke fear—it should inspire excitement. AI adoption isn’t about machines replacing humans. It’s about humans becoming irreplaceable by effectively harnessing these tools.

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If you’re reluctant or sceptical, Anthony Tan’s message is clear: embrace AI now, or watch as those who do leave you behind.

Hot Take

Anthony Tan might sound dramatic—but he has a point. If you’re not actively exploring AI, you’re preparing yourself (and your company) to become obsolete. The clock is ticking: Will you adapt, or will you become the adaptation?

What do you think?

Are you inspired or intimidated by Anthony Tan’s AI-driven future? Drop your thoughts below!

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