For most of my career, work came with clear boundaries.

Everyone had a title. Everyone had a territory. And as long as you found the right person within that territory, things usually got done properly, and “accordingly.” There was comfort in that clarity.

In corporate environments, people are often careful not to step into someone else’s territory. Sometimes it’s about respect. Sometimes it’s about process. And sometimes, jokingly but not entirely untrue, it’s because stepping in might mean someone else doesn’t have enough work.

Then I stepped into the startup world — and everything flipped.

In a startup, people want you to step into their territory. Resources are constantly stretched. Time is limited. Headcount is tight. An extra pair of hands, or even just another brain thinking through a problem, is more than welcome.

No one asks which team you’re on or what your job title is. If you can help, you’re in.

Only later did I realise this mindset closely resembles a company slogan I once heard from China: “As long as you can do it, you step up.” Back then, it sounded motivational. Now, I finally understand it.

Learning to manage my own “highway”

Another adjustment came from something seemingly small, yet deeply telling: how people collaborate.

For years, I worked in Google Workspace — shared documents, real-time edits, seamless collaboration. It felt efficient and natural.

Then I joined the startup and found Excel files being emailed back and forth. Versions of versions. Updates layered on top of updates.

My first instinct was disbelief. My second was to change it.

But I learned quickly that changing how people work isn’t just about better tools. It’s about timing, trust, and shared readiness.

So I took a deep breath. I swallowed my internal commentary. I kept my head up, my smile on, and worked with what the team was comfortable with.

My way was not the highway — even if, in my opinion, it was still the better one (well, says a Xoogler).

Also Read: Value creation: When startups die surrounded by capital

In startups moving at light speed, getting things done matters more than rebuilding infrastructure. There will be time to improve systems later — if the business survives long enough to get there.

Sometimes, progress starts with letting go of your own fixation.

Being ready to pivot — constantly

My title on this journey has been “Head of Special Projects.” In reality, that meant being thrown into operations, marketing, customer service, sales, hiring, training, PR, procurement, and whatever else came up.

If you ask me, honestly, which of these I had experience in before, the answer is simple: none. Absolutely none.

My background was in partnerships and business development. That was my comfort zone.

But I chose not to let my past experience define what I could do next.

This journey has been a long series of saying “yes, and” to projects I had no idea how to handle — and then figuring things out along the way. What made it possible was knowing I wasn’t alone. Most people on the team were facing steep learning curves, too.

There were no formal training programmes. No certifications. No colour-coded belts like in corporate life. There was orientation, and then there was reality.

We learned by doing. By talking to people. By making mistakes — and fixing them fast.

That’s the fun part. And also the hard part.

Also Read: Cruising the startup ocean: Building without a playbook 

Do I miss the corporate version of myself?

Yes, I do.

Corporate work feels easier now — familiar systems, predictable rhythms, fewer daily surprises. Well, except for the politics.

Have I burned out in my startup journey? Absolutely.

But burnout here feels different. It’s not just exhaustion — it’s a process of rebuilding and reshaping your internal shield for something tougher. In startups, there is no floating. Every day brings new problems that can save or break the business.

In corporate roles, challenges often drive incremental growth. In startups, challenges are about survival.

Who am I becoming?

What I’ve realised is this: the startup world sharpens you. It keeps you on your toes. You have less time to sit with sensitivity, because everyone, including yourself, is focused on moving forward or finding a way forward.

Empathy still matters. But so does the ability to set things aside quickly, change gears, and keep going.

So who am I now, deep in the startup ocean?

Maybe I’m still learning how to swim. But with less panic. More calm. And a better relationship with the panic itself.

Panic is part of the daily routine anyway. The goal is no longer to avoid it — but to learn how not to drown.

—

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Global markets shifted sharply into risk-off mode as President Trump announced proposed 10 per cent tariffs on eight European countries that opposed US plans regarding Greenland. The move reignited trade-war anxieties, triggering a broad retreat from risk assets and sending haven assets to new highs.

US equity index futures reflected the unease, with the S&P 500 down 0.9 per cent and the Nasdaq 100 falling 1.1 per cent. European stock futures dropped 1.2 per cent, while most Asian markets followed suit except China, where equities rose 0.3 per cent after official data confirmed the economy grew by five per cent in 2025, meeting its annual target despite a fourth-quarter slowdown.

The flight to safety propelled gold to a record US$4,635.88 per ounce, up 0.9 per cent, while silver also surged. In contrast, oil prices declined as geopolitical tensions around Iran eased. Currency markets mirrored the shift in sentiment, with the US dollar weakening broadly. The euro climbed 0.3 per cent to US$1.1627, and the Japanese yen strengthened to 157.66 per dollar. Cryptocurrencies did not escape the selloff. Bitcoin plunged 3.2 per cent to US$92,310.23, and the broader crypto market shed 2.9 per cent over the past 24 hours.

Also Read: Building trust in turbulent times: The new security paradigm for crypto exchanges

Three interlocking forces drove this downturn.

First, renewed US–EU trade tensions created immediate policy uncertainty. With US cash markets closed for Martin Luther King Jr. Day, futures bore the brunt of investor anxiety, and crypto, which often correlates with tech-heavy equities, got caught in the downdraft. The threat of retaliatory tariffs by February 1, coupled with a 54.5 per cent probability of a formal US move on Greenland according to prediction markets, kept volatility elevated.

Second, excessive leverage in crypto markets turned a modest dip into a cascade. As Bitcoin broke below US$92,000, over US$357 million in leveraged long positions were liquidated within an hour, contributing to total crypto liquidations of US$865 million. Open interest stood at US$645 billion, up nearly 20 per cent recently, signalling crowded bullish positioning. Negative funding rates of –0.000255 per cent further revealed that longs were paying shorts to stay in the market, a classic sign of overheated optimism vulnerable to reversal.

Third, technical breakdowns accelerated the decline. Bitcoin’s failure to hold the US$95,000 support level triggered algorithmic sell orders and panic among retail traders. The global crypto market cap fell below its 30-day exponential moving average of US$3.12 trillion, and the RSI dipped to 41.8, indicating waning momentum. Altcoins suffered disproportionately, with Solana down 10.63 per cent and Filecoin sliding 10.86 per cent. Among the top 50 assets, Aster posted one of the steepest losses, dropping more than 15 per cent.

Despite these headwinds, underlying fundamentals in parts of the crypto ecosystem remain robust. Ethereum continues to see record staking demand, suggesting strong conviction in its long-term utility. Macro fears have temporarily overridden such positives.

For now, the path forward hinges on two variables: whether the US and EU can de-escalate tariff rhetoric before the February 1 deadline, and whether Bitcoin can reclaim the US$93,000 level to signal short-term stabilisation. If trade tensions ease, altcoins may find relief, but until then, the market will likely remain hostage to geopolitical headlines and the fragility of overleveraged positions.

—

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SPUN, an artificial intelligence (AI) startup building digital infrastructure for visa processing, has raised US$1.8 million in seed funding.

The round was led by Japan’s Genesia Ventures, with participation from Antler, Iterative, and Kopital Ventures.

The capital will support SPUN’s expansion across Southeast Asia amid rising demand for streamlined cross-border travel tech.

Also Read: What Japan and Southeast Asia teach us about co-creating innovation

SPUN operates as a backend platform that simplifies visa applications and approvals for governments, travel agencies, and businesses. In essence, it provides APIs and software tools that integrate with national immigration systems, automating document verification, eligibility checks, and application tracking. Users submit details through partner apps or websites, and SPUN’s system handles the rest — routing data securely to authorities and delivering real-time status updates.

This technology addresses longstanding friction in global mobility. Traditional visa processes rely on paper forms, embassy queues, and manual reviews, often take weeks, and are prone to errors or fraud. SPUN’s digital layer reduces processing times to days or hours, cuts administrative costs by up to 40 per cent, and enhances security through biometric matching and AI-driven risk assessment. Its importance lies in enabling scalable, contactless travel infrastructure, critical as international tourism rebounds post-pandemic and remote work fuels digital nomadism.

For Indonesia, the funding marks a milestone in its tech ecosystem. As Southeast Asia’s largest economy, Indonesia issues millions of visas annually to tourists, workers, and investors, but its system has faced bottlenecks –evident in 2024 delays during peak travel seasons. SPUN, founded in 2023 by Jakarta-based engineers, already powers parts of Indonesia’s e-visa portal.

The investment signals growing investor confidence in local startups tackling public sector inefficiencies. It could accelerate Indonesia’s digital transformation goals under its “Making Indonesia 4.0” roadmap, potentially boosting tourism revenue (which hit US$20 billion in 2025) by making entry smoother for 15 million annual visitors. Critics note risks, like data privacy concerns in a country with patchy cybersecurity regulations.

SPUN is now expanding into three Southeast Asian countries: Thailand, Vietnam, and the Philippines. These markets were selected for their high visa volumes — Thailand alone processes over 30 million tourist visas yearly — and openness to tech partnerships.

Also Read: Japanese startups seek strategic partnerships in Southeast Asia

The company has partnered with immigration authorities in six countries so far. These include Indonesia, Singapore, Malaysia, Thailand, Vietnam, and one additional Southeast Asian nation not publicly named. Partnerships involve co-developing APIs tailored to each country’s regulations, such as Singapore’s strict biometrics standards or Malaysia’s labor migration focus.

Customers — ranging from travel platforms like Trip.com to corporate relocators and government agencies — gain tangible benefits. Processing times drop from seven to 14 days to under 48 hours in tested pilots. Costs fall via automation, eliminating physical handling fees. Fraud detection improves with machine learning that flags inconsistencies in 95 per cent of cases, per SPUN’s internal metrics. Applicants receive mobile notifications and one-click submissions, while governments get analytics dashboards for demand forecasting.

Competition is heating up. Regionally, Singapore-based Visa2Fly offers similar API integrations but focuses more on airline partnerships. In Southeast Asia, Travel Visa Pro competes with agent-facing tools.

Globally, players like iVisa (US-based) provide DIY application portals, while Atlys (India) emphasises consumer apps with embedded visa services. Larger incumbents such as VFS Global dominate outsourced processing with physical centres in over 150 countries, though they lag in full digitisation. SPUN differentiates through its government-first approach, embedding directly into official systems rather than third-party facades.

Also Read: East meets Southeast: How Japan can empower a new wave of SEA startup innovation

Genesia Ventures, known for early bets on Southeast Asian fintechs like Gojek, sees SPUN as a fit for a US$50 billion regional travel tech market projected to grow 15 per cent annually through 2030. “Visa infrastructure is the hidden bottleneck in SEA’s mobility boom,” said a Genesia partner in a statement. SPUN plans to use the funds for engineering hires and compliance certifications.

The deal underscores Japan’s deepening ties with Indonesia’s startup scene, following investments in firms like Xendit. However, challenges remain: navigating diverse regulations across ASEAN and ensuring data sovereignty amid US-China tech tensions. As SPUN scales, it will test whether niche infrastructure plays can thrive amid giants.

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As Southeast Asia’s digital economy surges past the US$1 trillion mark in 2026, propelled by rapid fintech adoption and AI-driven enterprises, the region’s cybersecurity landscape is a battlefield of innovation and peril.

With over 400 million internet users across ASEAN nations, cyber threats have evolved into sophisticated, state-sponsored operations and AI-augmented attacks.

Also Read: Super apps, fintech wallets and mobile payments: Southeast Asia’s next big cyber risk

According to the “ASEAN Cybersecurity Cooperation Strategy 2025” report, incidents rose 28 per cent year-on-year, costing businesses an estimated US$12 billion. Yet, amid this turbulence, startups and governments are forging resilient defences. Here are the pivotal trends defining 2026.

1. AI-powered threat detection and the rise of ‘defensive AI’

Artificial intelligence is no longer just a buzzword; it’s the cornerstone of cybersecurity in Southeast Asia. Singapore’s Cyber Security Agency (CSA) reports that 65 per cent of enterprises now deploy AI-driven tools for real-time threat detection, a sharp rise from 42 per cent in 2025.

Indonesian startup SekurID, fresh off a US$15 million Series A, exemplifies this with its AI Sentinel platform, which uses machine learning to predict ransomware patterns with 94 per cent accuracy.

The flip side? Adversaries are weaponising AI too. ‘Deepfake phishing‘ attacks spiked 150 per cent in the Philippines and Vietnam, per Interpol data, where generative AI crafts hyper-realistic executive impersonations. Thailand’s National Cyber Security Agency (NCSA) thwarted a US$50 million scam targeting Bangkok banks using voice-cloned calls.

Defensive AI countermeasures, like multimodal verification from Malaysian firm CyberShield, are gaining traction, integrating biometrics and behavioural analytics to outpace attackers.

2. Quantum-resistant cryptography amid Quantum breakthroughs

Quantum computing‘s commercial dawn in 2026 has the region scrambling. IBM’s Singapore quantum hub and Alibaba’s Kuala Lumpur lab accelerated hybrid quantum attacks, cracking legacy RSA encryption in lab tests. The Monetary Authority of Singapore (MAS) mandated quantum-resistant algorithms for financial institutions by Q3, spurring a boom in post-quantum cryptography (PQC) startups.

Also Read: Southeast Asia’s cyber boom is fuelled by fear—and AI

Vietnam’s QuantumSafe Tech raised US$20 million to develop lattice-based encryption tailored for IoT devices in smart cities. Regional adoption, however, lags behind; only 22 per cent of Indonesian firms are PQC-ready, per a Deloitte survey, exposing supply chains to ‘harvest now, decrypt later’ threats. Governments are responding: Malaysia’s MyDigital blueprint allocates RM500 million for quantum-safe infrastructure, fostering collaborations with startups like Qryptix.

3. Zero-trust architectures go mainstream in hybrid workforces

The pandemic’s hybrid work legacy persists, with 70 per cent of SEA firms operating distributed models. Zero-trust architectures (ZTA) — verifying every access request — have become non-negotiable. Gartner’s 2026 forecast predicts 80 per cent adoption in Singapore and the Philippines, driven by tools from local innovators like Node42 in Jakarta, whose ZeroGate platform reduced breach dwell time by 60 per cent.

Supply chain vulnerabilities, highlighted by the 2025 SolarWinds-style attack on Vietnam’s VinGroup, underscore ZTA’s urgency. Brunei and Cambodia are catching up via ASEAN Digital Economy Framework pacts, integrating ZTA into national cloud mandates.

4. Ransomware-as-a-service targets SMEs and critical infrastructure

Small and medium enterprises (SMEs), the backbone of SEA’s US$300 billion digital economy, face existential ransomware threats. Groups like LockBit 4.0 offer ‘RaaS’ kits, hitting 40 per cent more Indonesian SMEs in 2026, per Check Point Research. Critical infrastructure (ports in Singapore, power grids in Thailand) saw 35 per cent attack surges, with Laos’ hydropower network offline for 72 hours after a US$10 million demand.

Philippine startup RansomBlocker uses blockchain for immutable backups, securing over 500 SMEs. Regional initiatives, like Singapore’s SGSecure+ and Indonesia’s BSSN Cyber Drill, emphasise resilience training.

5. Regulatory harmonisation and the ASEAN cyber shield initiative

Fragmented regulations are unifying under the 2026 ASEAN Cyber Shield Initiative, standardising data protection akin to GDPR. Singapore’s PDPA amendments impose fines up to 10 per cent of global turnover, while Thailand’s PDPA enforcement netted US$5 million in penalties. This spurs cross-border startups: for e.g., Hanoi-based SecureNet, offers compliance-as-a-service for 1,000+ firms.

Also Read: Why does cybersecurity training for employees in Malaysia matter and how to go about it?

Talent shortages persist; SEA needs 2.5 million cyber experts by 2030.

Looking ahead: Resilience through innovation

Southeast Asia’s cybersecurity in 2026 is a tale of dual forces: escalating threats met by agile innovation. Startups like SekurID and QuantumSafe are leading the charge.

For founders and executives, the mantra is clear: invest in AI defences, embrace zero-trust, and align with regional regs. As digital transformation accelerates, those who fortify now will thrive in tomorrow’s connected frontier.

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Fujitsu Limited and SC Ventures have unveiled a roadmap for Qubitra Technologies, a joint venture designed to accelerate quantum computing adoption and innovation across Asia Pacific and Southeast Asia.

By combining Fujitsu’s quantum expertise with Standard Chartered’s innovation ecosystem, the partnership seeks to transform how organisations access and leverage quantum resources.

Understanding Qubitra: Quantum made accessible

In simple terms, Qubitra functions as a digital marketplace and collaboration hub for quantum computing. Think of it as a bridge connecting quantum researchers, developers, and enterprises who need quantum solutions but lack the infrastructure or expertise to build them independently.

Also Read: How quantum computing moved from components to applications in 2024

Here’s how it works: The platform integrates quantum computing resources (including hardware, software, and algorithms) alongside a curated network of quantum talent and expertise. Organisations can access quantum capabilities on demand through a unified digital interface, eliminating the need for massive upfront capital investments in quantum infrastructure.

Whether a financial institution needs to optimise portfolios or a pharmaceutical company requires molecular simulations, Qubitra provides the tools and talent to solve complex quantum problems without building quantum labs from scratch.

Accelerating innovation through strategic partnership

The Fujitsu-SC Ventures collaboration creates an innovation multiplier effect:

• Fujitsu’s contribution: As a pioneer in quantum computing, Fujitsu brings cutting-edge quantum technology, including its Digital Annealer and quantum-classical hybrid systems, alongside decades of enterprise computing expertise.
• SC Ventures’s network: Standard Chartered’s global financial services network and innovation platform provides immediate access to enterprise clients across banking, finance, and other sectors hungry for quantum solutions.

Also Read: Quantum’s inflection point: Why the smart money is watching now

• The synergy: By combining these strengths, Qubitra removes traditional barriers to quantum adoption. Organisations gain access to enterprise-grade quantum resources without vendor lock-in, while quantum developers and startups find a ready market for their innovations. This ecosystem approach dramatically reduces the time-to-value for quantum applications and attracts new talent to the field.

Asia Pacific and SEA: A quantum growth story

The quantum computing sector in Asia Pacific is experiencing remarkable momentum:

• Regional investment surge: Asia Pacific has emerged as the second-largest quantum computing market globally, with government initiatives and private investment flowing into quantum research centres across China, Japan, South Korea, Singapore, and India.
• Government backing: Singapore has positioned itself as a quantum hub through initiatives like the National Quantum-Safe Migration Programme. Japan continues significant quantum R&D investment, while India has launched its National Quantum Mission to develop indigenous quantum technologies.
• Enterprise adoption: Financial institutions, particularly in Singapore and Hong Kong, are actively exploring quantum applications for portfolio optimisation, risk analysis, and cryptography. Pharmaceutical and manufacturing sectors are investigating quantum simulations for drug discovery and materials science.
• Southeast Asia’s emerging role: While still nascent, Southeast Asia is rapidly becoming a focal point for quantum development. Countries like Singapore, Vietnam, and Thailand are establishing quantum research initiatives, creating fertile ground for platforms like Qubitra to accelerate adoption.

The quantum future of Southeast Asia: Opportunities and challenges

The outlook for quantum computing in Southeast Asia is decidedly optimistic, though nuanced:

Growth catalysts

• Regulatory advantage: Southeast Asian nations are establishing quantum-friendly regulatory frameworks ahead of the curve, potentially attracting quantum startups and talent from more restrictive markets.
• Talent pipeline: Universities across the region are expanding quantum education programs, creating a new generation of quantum engineers and researchers.
• Problem-solving urgency: SEA faces unique challenges—from managing complex supply chains to optimising energy grids—where quantum computing offers transformative solutions.

In the long term, Southeast Asia could transition from quantum consumer to quantum producer, with homegrown quantum technologies and intellectual property. The region’s position between global quantum leaders (China, the US, Japan) and emerging markets creates unique opportunities for quantum applications tailored to Asian business challenges.

Also Read: Quantum investor QAI Ventures picks Singapore for APAC headquarters

Critical success factor: Platforms like Qubitra that democratise quantum access will be essential. Without such bridges, quantum computing risks remaining an exclusive tool for well-funded enterprises, missing the opportunity to unlock innovation across Southeast Asia’s diverse economy.

The Qubitra announcement signals a strategic shift: quantum computing is moving from laboratory curiosity to practical business tool, and Asia Pacific is positioning itself as the epicentre of this transformation. For Southeast Asia specifically, this joint venture may represent a pivotal moment– the chance to leapfrog traditional technology adoption cycles and establish genuine quantum computing capability before the window closes.

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China’s rise in the global gaming industry is frequently attributed to surface-level factors such as population size, low production costs, or aggressive monetisation. While these elements exist, they do not adequately explain the durability or consistency of China’s success. Many countries have large populations. Many industries rely on monetisation. Few achieve sustained global leadership.

China’s advantage in gaming is structural. It lies in how games are conceptualised as systems, how players are understood as long-term participants, and how operations are optimised for longevity rather than short-term performance. To understand why China is winning, it is necessary to examine the underlying mechanics of its gaming ecosystem rather than individual success stories.

Market scale as an iteration engine

China’s domestic gaming market functions less as a revenue endpoint and more as a continuous testing environment. The sheer volume of players allows developers to observe behaviour at scale, producing reliable data on how users interact with mechanics, progression systems, difficulty curves, and monetisation options. Patterns that might take years to emerge in smaller markets can be identified quickly.

This scale enables extensive iteration before global release. Developers can adjust pacing, rebalance systems, or refine reward structures based on real engagement rather than assumptions. Importantly, failure within the domestic market does not necessarily end a project; it becomes part of the learning process.

In contrast, many Western studios face high pressure at launch, as international markets are often required to validate a game’s success. This compresses experimentation into limited post-launch windows and increases financial risk. Chinese studios, by stabilising systems domestically first, enter global markets with greater confidence and predictability.

Why mobile-first design became a structural advantage

China’s early gaming environment was shaped by constraints rather than choice. Limited access to consoles and uneven PC availability meant that mobile devices became the primary gaming platform for a broad segment of the population. This forced developers to design for mobile conditions from the outset.

As a result, Chinese games were built around short, repeatable play sessions, intuitive controls, and immediate feedback loops. Progression systems were calibrated to feel rewarding even within minutes of play. These design principles aligned closely with real-world user behavior, especially among working adults.

When mobile hardware evolved to support advanced graphics and complex gameplay, Chinese studios did not need to rethink their design philosophy. They simply expanded on an existing foundation. Western studios, which historically prioritised console and PC experiences, often struggled to adapt their mechanics to mobile platforms without compromising usability or engagement. Over time, this divergence became structural rather than temporary.

Also Read: Gaming in SEA: Understanding the growing opportunity for SMEs and payment providers

Games as services, not products

Chinese developers generally treat games as long-term services rather than finite products. This perspective influences every stage of development, from system architecture to content planning.

Instead of designing toward a launch milestone, teams design toward multi-year operation. Systems are modular, so they can be expanded or adjusted without destabilising the game. Content pipelines are continuous, ensuring that players encounter regular updates rather than sporadic expansions.

Success is measured by retention stability, player lifetime value, and engagement consistency rather than peak sales. This encourages sustainability and discourages short-term design decisions that might generate immediate revenue but harm long-term participation. Western studios, particularly those with legacy business models, often struggle to adopt this mindset fully due to publisher expectations and production constraints.

Monetisation as system architecture

In the Chinese gaming ecosystem, monetisation is embedded into the design process rather than appended after development. This integration allows monetisation systems to align closely with progression and engagement mechanics.

Features such as gacha draws, VIP tiers, seasonal passes, and limited-time events are designed to distribute spending across a player’s lifecycle. Rather than pushing for immediate high-value purchases, these systems encourage gradual commitment and long-term participation.

This approach produces more predictable revenue streams and reduces reliance on a small number of high-spending users. While these monetisation models are often criticised externally, their effectiveness lies in their ability to sustain development and content creation over extended periods without destabilising the player base.

Retention through routine, not novelty

Chinese studios prioritise retention by integrating games into players’ daily routines rather than relying on constant novelty. Daily incentives, recurring events, and predictable progression milestones encourage habitual engagement.

Instead of overwhelming players with continuous new content, these games emphasise consistency and familiarity. Characters and narratives evolve slowly, allowing emotional attachment to develop over time. This reduces cognitive fatigue and lowers churn rates.

Western studios frequently focus on content volume and novelty, which can generate short-term excitement but often leads to burnout. By emphasising routine and continuity, Chinese games achieve longer player lifespans and more stable communities.

Also Read: How sailing as a teenager prepared me for a career in tech and gaming

Operational discipline in live operations

Live operations are treated as a core competency within Chinese studios. Dedicated teams monitor player behaviour, event performance, and system balance in real time. This data-driven approach allows developers to respond quickly to emerging issues.

Features that underperform are modified or removed without hesitation. Successful mechanics are expanded and optimised. Event schedules are adjusted based on player engagement rather than fixed calendars.

This operational discipline allows games to recover from weak launches and adapt to changing player preferences. Western studios, often constrained by slower production pipelines and higher coordination costs, struggle to achieve the same level of responsiveness.

Ecosystem integration and control

China’s gaming industry benefits from vertically integrated ecosystems that encompass development, publishing, distribution, payments, social interaction, and streaming. This integration reduces friction across the player journey.

User acquisition, community engagement, and monetisation occur within interconnected platforms, lowering costs and improving efficiency. Feedback from players flows directly into development cycles, shortening iteration timelines.

In contrast, Western studios operate within fragmented ecosystems dominated by external platforms. This fragmentation increases dependency risks, raises acquisition costs, and limits control over player relationships.

Also Read: Cybercriminals launch 6.3M fake shopping scams; gaming platforms also under fire

Regulation as a catalyst for maturity

China’s regulatory environment has imposed strict controls on game approvals, monetisation practices, and playtime. While often perceived as restrictive, regulation has forced studios to become more disciplined and efficient.

Domestic constraints reduced reliance on rapid growth and encouraged operational optimisation. To sustain revenue, studios expanded internationally, investing in localisation, cultural adaptation, and compliance infrastructure.

Rather than weakening the industry, regulation accelerated its maturation. Studios capable of navigating regulatory complexity developed the organisational resilience needed to compete globally.

A structural shift, not a temporary trend

China’s leadership in the global gaming industry reflects long-term structural alignment rather than short-term advantage. Mobile-first design, service-oriented development, monetisation integration, operational discipline, and ecosystem control collectively form a durable framework.

This does not signal the decline of Western or Japanese gaming, but it does indicate a redistribution of industry leadership. Creative excellence remains global, but operational and economic influence has shifted.

China is winning the global gaming industry not through isolated successes, but through systems that prioritise longevity, adaptability, and scale.

—

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AGIBOT, a Chinese robotics company specialising in embodied artificial intelligence, has launched operations in Malaysia, marking the beginning of its Asia-Pacific expansion strategy.

The company held a launch event on Tuesday at i-City in Selangor, attended by Malaysian government officials and industry partners, coinciding with the opening of an AI and Robotics Experience Centre developed with local property developer I-Berhad.

Also Read: SGInnovate backs Botsync in extended Series A amid AMR market surge

The timing reflects broader shifts in Southeast Asia’s manufacturing landscape. Rising labour costs, supply chain reshoring, and government-backed automation initiatives are driving demand for robotics solutions across the region.

Malaysia’s established electronics manufacturing base, relatively business-friendly regulatory environment, and central geographic position make it a logical entry point for regional expansion.

Market position and scale

AGIBOT, founded in 2023, has achieved rapid scaling. The company claims to have shipped over 5,100 humanoid units in 2025 and was ranked No. 1 globally by market research firm Omdia for humanoid robot shipments and market share, capturing 39 per cent of the global market. The company’s 5,168th mass-produced unit demonstrates industrial-scale manufacturing capability—a significant milestone for a robotics sector historically characterised by limited production volumes.

“AGIBOT made significant strides to improve the mass production and the practical use of embodied robotics last year,” said Deng Taihua, Founder, Chairman, and CEO. “This milestone puts AGIBOT in a strong position as we start 2026.”

AGIBOT’s approach differs from traditional industrial robots designed for single, repetitive tasks. The company focuses on embodied AI systems that learn and adapt in real-world environments through reinforcement learning, enabling robots to be trained and deployed directly in operational settings rather than relying solely on pre-programmed sequences.

Malaysia partnership and testbed model

The AI World Experience Centre represents a departure from conventional robotics commercialisation. Rather than focusing exclusively on factory automation, AGIBOT and I-Berhad are deploying robots across hospitality, property management, and urban operations at i-City. The partnership plans to develop the world’s first AI and Robotics Residential Tower, positioning residential environments as a testbed for humanoid robot integration.

Also Read: Serving up the future: How robots are revolutionising the F&B industry

“This launch marks the first of several strategic initiatives we will roll out in the Asia-Pacific region throughout 2026 and beyond,” said Abel Deng, President, Asia-Pacific & Middle East Region, AGIBOT.

Tan Sri Lim Kim Hong, Chairman of I-Berhad, stated that the initiative aims to advance Malaysia’s positioning as a regional AI innovation hub and establish “a new benchmark for intelligent, human-centric living in the region.”

Product portfolio

AGIBOT’s commercial offerings span multiple use cases: the A2 series for reception and hospitality; the X2 series for entertainment and education; the G2 series for industrial manufacturing; the D1 series for inspection operations; and the C5 autonomous floor-care robot.

The company targets eight application areas, including reception, entertainment, industrial manufacturing, logistics, security, data collection, and research.

Regional context

AGIBOT’s expansion arrives at a pivotal moment for robotics adoption across Southeast Asia. While the region’s robotics sector remains smaller than those in Singapore or South Korea, growth is accelerating. Rising labour costs across manufacturing hubs like Malaysia, Thailand, and Vietnam are driving automation investments. Supply chain reshoring initiatives, accelerated by pandemic disruptions, are creating new opportunities for local robotics deployment.

The sector, however, faces challenges. Compared to mature markets, Southeast Asia has a smaller installed base of industrial robots, lower overall adoption rates in some industries, and a developing ecosystem of local robotics companies. Yet these barriers also represent opportunities for players like AGIBOT to shape market standards and build early-mover advantages.

Also Read: Robotics, space, sustainability: The forces shaping Asia’s next tech chapter

Key trends include increased AI integration, expansion beyond manufacturing into services, and growing emphasis on localised solutions tailored to regional needs.

Strategic trajectory

AGIBOT frames the Malaysia launch as the first of multiple 2026 initiatives. The company indicates plans to expand partnerships across Asia-Pacific and deploy robots in “closed-loop commercial scenarios”, operational environments where continuous learning and improvement can occur. The emphasis on robots-as-a-service models suggests a subscription-based approach rather than outright sales.

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When Toku registered its offer document for a proposed listing on the Catalist Board of the Singapore Exchange, the announcement landed as more than just another IPO filing. For Singapore’s tech startup ecosystem, it signalled a potential inflexion point that touches public market confidence, regional-first tech building, the evolution of AI infrastructure and how startups scale across Asia.

At a time when global tech IPOs remain selective and private capital is increasingly disciplined, Toku’s move carries broader implications for founders and investors navigating 2026.

Perhaps the most immediate impact of Toku’s listing is narrative-driven rather than numerical. Singapore has only just begun to see the return of IPO activity among venture-backed tech companies in 2025. Against that backdrop, Toku’s decision to pursue a local listing reinforces the relevance of SGX Catalist as a viable exit route for growth-stage tech firms.

For founders, this matters. IPOs shape long-term decision-making well before a company reaches the listing stage. A credible example like Toku helps re-anchor expectations around governance, capital efficiency, and operational maturity — qualities that public markets now prioritise more than rapid, loss-driven expansion.

It also sends a message that startups do not necessarily need to look overseas for liquidity events. In an era of heightened geopolitical and regulatory complexity, a domestic listing pathway reduces execution risk while keeping companies anchored in Singapore’s ecosystem.

Also Read: Nasdaq tumbles, but Bitcoin soars past US$97K on massive short squeeze

Validating “Asia-built-for-Asia” tech

Toku’s positioning as an AI-powered customer experience platform, built specifically for complex, multilingual, and regulated markets, aligns closely with Singapore’s evolving tech identity. Rather than exporting standardised global products, the company has focused on solving problems that are particularly acute across the Asia Pacific, the Middle East, and emerging markets.

This reinforces a broader shift underway in the ecosystem: a growing emphasis on regionally grounded enterprise technology rather than consumer platforms or copycat SaaS models.

For investors, Toku’s IPO helps validate the commercial potential of startups that prioritise:

– Local compliance and data sovereignty
– Multilingual AI performance
– Deep integration with telecom and enterprise infrastructure

These are not easily replicable advantages, and they play to Singapore’s strengths as a regulatory-savvy, enterprise-facing tech hub. As a result, Toku’s listing could encourage more founders to pursue defensible, infrastructure-adjacent business models rather than chasing scale through uniform global deployment.

While AI remains a dominant theme across the startup landscape, much of the recent attention has focused on applications and user-facing tools. Toku’s story highlights a different layer of the AI stack: infrastructure that enables enterprises to deploy AI securely, compliantly and at scale.

Its end-to-end control over connectivity, orchestration and AI applications underscores the growing importance of systems-level innovation, particularly for regulated industries such as financial services, healthcare and government.

Also Read: Toku files for SGX Catalist IPO, doubles down on partner-led go-to-market strategy

This has implications for how investors assess AI startups in 2026. Rather than asking only what models or features a company offers, there is increasing scrutiny around how AI is deployed, governed, and integrated into existing workflows. Startups that can demonstrate robustness in these areas may find stronger traction with both enterprise buyers and capital providers.

Normalising partner-led go-to-market strategies

Equally significant is Toku’s emphasis on a partner-led go-to-market strategy as it scales beyond its core markets. Instead of relying solely on direct sales expansion, the company is doubling down on channel partners, systems integrators, and ecosystem alliances to efficiently enter new regions.

This approach reflects the realities of scaling in fragmented markets, where local knowledge, regulatory familiarity and on-the-ground execution often matter more than centralised sales teams. For other startups, Toku’s playbook offers a practical alternative to capital-intensive expansion models.

In 2026, this could influence how early- and growth-stage companies design their products and pricing with partners in mind from the outset. It also strengthens the role of Singapore-based enterprises, telcos, and consultancies as distribution enablers for regional startups.

More broadly, it suggests a maturing ecosystem where success is measured not only by the speed of expansion, but also by sustainable market entry and long-term customer value.

Also Read: The quiet currency shift: Southeast Asia’s strategic pivot to a multipolar monetary era

A signal beyond the listing

Taken together, Toku’s IPO represents more than a single company reaching the public markets. It reflects a broader recalibration underway across Singapore’s tech ecosystem, where investors and founders alike are placing renewed emphasis on fundamentals. In place of growth-at-all-costs narratives, there is a clearer preference for disciplined execution, clear paths to sustainability and tech that solves real, structural problems.

The listing also highlights a shift towards regional relevance over generic scale. Toku’s success has been built on addressing the complexities of multilingual, regulated and infrastructure-constrained markets, rather than forcing uniform solutions across geographies. This approach reflects a growing conviction that Singapore-based startups can succeed by embracing regional specificity, rather than competing directly with global incumbents on their own terms.

Equally important is what Toku’s story signals about the evolution of AI in enterprise settings. As excitement around AI matures, attention is shifting beyond surface-level applications to infrastructure, governance, and deployment at scale. Platforms that prioritise compliance, reliability and integration are increasingly viewed as more defensible and more valuable over the long term.

For founders, Toku’s IPO helps reset expectations around what success looks like in 2026. The pathway to public markets is no longer defined solely by speed, but by operational maturity, partner ecosystems, and credible regional strategies. These are traits that require time and patience to build, but which are increasingly rewarded.

While Toku’s long-term performance as a listed company remains to be seen, its decision to list locally already carries weight. It broadens the ambition set for Singapore’s tech sector, offering a concrete example of how companies can scale responsibly, remain regionally grounded and still access public market capital on home soil.

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The lead image is AI-generated.

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Asia-Pacific agrifoodtech startups raised US$4.2 billion in 2024, capturing 31 per cent of global sector funding. Yet across Southeast Asia, where agriculture remains a primary livelihood for hundreds of millions of people, this investment systematically misses the majority of farming communities. This isn’t just a market inefficiency—it’s a fundamental failure to understand how rural communities actually function.

Here’s the uncomfortable truth: every single agricultural app is designed for an imaginary user.

Picture Sari, a rice farmer in Central Java. Her smartphone buzzes with a weather alert suggesting she plant early because conditions are perfect. Sounds helpful, right? Except she can’t plant anything. Her village irrigation group hasn’t released water to her section yet. The planting schedule was decided three weeks ago in a community meeting she attended, but didn’t lead. Her father-in-law, the village elder, and the irrigation chief made that call together.

That weather app just became expensive digital noise.

This is the story of how Southeast Asian agritech is optimising for individual users in a world that makes collective decisions—and why the communities that need innovation most are getting left behind.

The fundamental misalignment

The person using your app isn’t the decision maker

The core problem isn’t technical sophistication or user experience design. It’s that the person using your app is rarely the person with power to change anything.

Consider the typical agritech user journey:

• Information flows to individuals (weather alerts, market prices, agronomic advice)
• Decisions are made collectively (planting schedules, input purchases, marketing choices)
• Impact requires community coordination (water management, pest control, harvest timing)

We’re building perfect steering wheels for passengers.

The three-layer reality of rural decision making

• Individual layer: The farmer who downloads your app, creates an account, receives notifications
• Community layer: Village councils, irrigation groups, farming cooperatives that make actual resource allocation decisions
• Ecosystem layer: Traders, input suppliers, financial institutions that control access to markets and credit

Most agritech stops at individual layer. Real agricultural change happens at community and ecosystem layer.

Also Read: Digital farming’s false promise: Why Asia’s US$180B bet on agritech-driven farming is failing smallholders

Case study: The US$15M weather app that changed nothing

AgriWeather (anonymised) raised US$15M Series A to provide hyperlocal weather forecasting to Indonesian farmers.

The pitch deck reality

• 250,000+ downloads in six months
• 85 per cent user retention after first month
• Sophisticated machine learning models
• Beautiful, intuitive interface in local languages

The field reality

In Bali’s rice terraces, they’d never heard of subak—thousand-year-old irrigation cooperatives that manage water allocation across entire watersheds. Planting schedules aren’t individual decisions; they’re collective negotiations about water timing, pest management, and harvest coordination.

When farmers showed the app’s recommendations to their subak leaders, the response was predictable: “We’ll plant when water reaches our section, like we discussed last month.”

The outcome

Great user metrics, zero agricultural impact. The startup eventually pivoted to B2B after burning through their Series A trying to acquire individual users who couldn’t act on their product.

The lesson

Technical sophistication is irrelevant if you’re solving the wrong problem for the wrong decision maker.

The collective decision-making framework

Understanding power structures across Southeast Asia

• Indonesia: Gotong royong (mutual cooperation) principles mean agricultural decisions flow through village councils (RT/RW) and traditional cooperatives (subak, gapoktan)
• Thailand: Farmer cooperatives and Royal-initiated agricultural groups maintain significant influence over individual farming practices
• Vietnam: Commune-level agricultural cooperatives (HTX) coordinate resource allocation and market access for member farmers
• Philippines: Barangay councils and irrigation associations (IA) make collective decisions about water management and crop timing

The four decision archetypes

• Water and timing decisions: Controlled by irrigation groups and village councils
• Input and credit decisions: Managed through cooperatives and traditional lending relationships
• Knowledge and technique decisions: Shared through farmer groups and extension networks
• Market and sales decisions: Constrained by existing trader relationships and cooperative marketing

Implication: Successful agritech must integrate with these existing structures, not bypass them.

Also Read: Indonesia’s agritech landscape: Keys to building a scalable agriculture startup

What actually works: The community-centred model

Case study: AgriCooperative’s US$50M success

Instead of targeting individual farmers, AgriCooperative worked through existing farmer cooperatives:

The approach

• Village leaders became part of the credit assessment process
• Community members provided social collateral
• The platform recognised that rural financial decisions involve community reputation

The results

• 1,847 farming families accessed US$12M in credit
• 94 per cent repayment rate (vs 67 per cent industry average for individual lending)
• Average household income increased 23 per cent over 18 months
• Platform became integral to existing community decision-making processes

Why it worked

They built for the reality of collective decision-making instead of fighting it.

The new framework: Community-centred agritech

Design principles for rural reality

• Map Power Before Building Product

• Who actually makes agricultural decisions in target communities?
• How do information and resources flow through village structures?
• What existing institutions could be enhanced rather than replaced?

• Design for Collective Intelligence

• Individual apps that feed into group decision-making processes
• Platforms that strengthen existing community coordination mechanisms
• Tools that make collective decision-making more efficient, not obsolete

• Measure Community-Level Impact

• Agricultural outcomes across entire villages or cooperatives
• Strengthening of traditional knowledge and decision-making systems
• Economic improvements at the household and community level

• Build Sustainable Revenue Models

• Community-centred solutions often require different monetisation approaches
• Success may come through institutional partnerships rather than individual payments
• Value creation happens at the ecosystem level, not just user level

Also Read: How Southeast Asia’s agritech startups are turning smallholder farms into high-tech powerhouses

Implementation roadmap

Phase one: Deep community research (three-six months)

• Ethnographic study of agricultural decision-making in target regions
• Mapping of existing community institutions and power structures
• Identification of technology integration points within collective systems

Phase two: Community partnership development (6-12 months)

• Build relationships with village leaders and cooperative managers
• Co-design solutions with community decision-makers
• Pilot programs that enhance existing coordination mechanisms

Phase three: Scaled community integration (12+ months)

• Deploy solutions through established community channels
• Measure impact at village and cooperative level
• Refine based on community-level feedback and outcomes

The investment challenge and opportunity

Why VCs struggle with community-centred models

• Traditional VC Metrics:

• Individual user acquisition costs
• Monthly active users
• Revenue per user
• Individual customer lifetime value

• Community-centred Metrics:

• Community adoption rates
• Collective behaviour change
• Village-level agricultural outcomes
• Ecosystem-wide economic impact

The multi-billion dollar opportunity

• Current market focus: Southeast Asian agritech primarily serves educated, connected, individually empowered farmers—a small fraction of the total agricultural population
• Underserved market: The vast majority of rural populations making collective decisions through traditional institutions like cooperatives, irrigation groups, and village councils
• Market potential: ASEAN agricultural production alone totaled 195.5 million tons of rice, 44.7 million tons of corn, and 82.1 million tons of cassava in 2022, representing massive economic activity largely untouched by current agritech solutions

New investment framework

• Community traction metrics:

• Number of village councils or cooperatives actively using the platform
• Collective decisions influenced by platform insights
• Community-level agricultural outcome improvements
• Integration depth with existing institutional structures

• Revenue model innovation:

• Institutional partnerships with cooperatives and government extension services
• Value-based pricing tied to community-level outcomes
• Revenue sharing with traditional institutions rather than competing with them

The competitive advantage of getting this right

Companies that successfully engage rural communities through collective decision-making systems will access currently underserved agricultural markets while building sustainable competitive advantages through deep community integration.

• Policy alignment opportunity

Asian Development Bank research highlights that Southeast Asian governments prioritize strengthening rural statistical systems and agricultural coordination—community-centered solutions align with these policy goals while improving agricultural outcomes.

• Investment trends supporting community-centred models

The 38 per cent year-over-year increase in Asia-Pacific agrifoodtech funding demonstrates growing investor confidence in agricultural innovation, creating opportunity for solutions that demonstrate genuine community-level impact rather than just individual user metrics.

Also Read: Need of the hour: How agritech platforms can protect farmers from climate change

The choice point for Southeast Asian agritech

• The individual path (Current trajectory)

• Target educated, connected farmers representing a small fraction of the agricultural population
• Compete on user experience and technical features
• Measure success through app-store metrics and individual user engagement
• Generate venture returns through individual customer acquisition in urban-adjacent markets

Outcome: Sophisticated solutions serving a narrow market segment while the majority of agricultural communities remain underserved

• The community path (Untapped opportunity)

• Partner with existing rural institutions like cooperatives and village councils
• Enhance collective decision-making processes that govern resource allocation
• Measure success through community-level agricultural outcomes and livelihood improvements
• Generate returns through ecosystem-wide value creation and institutional partnerships

Outcome: Access to vast underserved agricultural markets while creating genuine rural development impact

Call to action: Building for rural reality

• For entrepreneurs: Stop building for imaginary individual farmers. Start with deep community research. Map power structures before writing code. Design for collective intelligence rather than individual optimization.
• For investors: Fund founders who understand rural power dynamics. Demand community-level impact metrics before major funding rounds. Recognise that community-centred solutions may have different growth curves but potentially larger ultimate markets.
• For the ecosystem: Question who actually benefits from “agricultural innovation.” If the answer is primarily urban, tech-savvy users, we’re solving the wrong problems with the wrong metrics.

The agricultural community question

Southeast Asian agritech has attracted billions in investment to serve the region’s agricultural communities. Yet most of those communities remain unreached by the innovation they’re funding.

The technology exists. The market need is massive—ASEAN’s agricultural output continues growing, with rice production forecast to increase to 202.34 million tons in 2024. The missing piece is understanding that rural communities don’t function like individual app users—and that’s not a problem to solve but a reality to build for.

Rural Southeast Asia is ready for agricultural innovation. The question is whether the 31 per cent of global agrifoodtech funding flowing to Asia-Pacific will finally reach the communities that actually exist, not the individuals we imagine.

The communities are waiting. What are we going to build for them?

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Over the past few years, AI in the enterprise has been about trials and piloting of new solutions. While over 70 per cent of banking institutions globally use agentic AI today, only 16 per cent have moved to actual operational deployment. This gap reveals a critical truth: the barrier to production scale is not technology. It is organisational clarity and strategic intent.

In 2026, as we move beyond AI hype to reality, executives across financial services, insurance, healthcare, and technology will face a decisive question: are we committing to production-scale deployment, or continuing to cycle through experiments?

The upside for organisations is substantial. McKinsey estimates AI could unlock US$340 billion in annual value for banking alone. Yet less than one per cent of global executives report significant ROI from AI investments, defined as 20 per cent or greater improvement in profitability or cost savings. Only three per cent report a substantial ROI of 10 to 20 per cent. This disparity reflects a systematic failure of execution.

Across industries, we see that when institutions successfully transition from pilots to production scale, they achieve improvements in processing speed, automation rates, and regulatory compliance readiness.

The strategic shift: From cost reduction to autonomous efficiency

Organisations that are succeeding at production scale are not optimising for headcount reduction, but instead, they are optimising for autonomous efficiency. This means they are using AI to eliminate routine work completely so humans can focus on revenue-generating activities.

For example, this could include a lending algorithm approving customer applications instantly without human review or a fraud detection system blocking suspicious transactions automatically. Proven revenue levers include hyper-personalised cross-sell and upsell, financial inclusion lending powered by alternative data, premium digital wealth management, and AI-augmented compliance and fraud prevention.

Also Read: Looking beyond the bots: The unsexy digital skills that actually matter in 2026

This reframing of autonomous efficiency changes ROI calculations fundamentally. According to Larridin’s 2025 Enterprise AI Report, enterprises measuring AI properly report average productivity improvements of 27 per cent, time savings of 11.4 hours per knowledge worker weekly, and cost reductions of US$8,700 per employee annually. But these improvements accrue only to organisations that commit to autonomous workflows rather than basic human augmentation layers.

For example, the production-ready approach Dyna.Ai has pioneered demonstrates this principle. By operating at sub-200 millisecond response times with over 95 per cent accuracy, the platform enables businesses to deploy autonomous agents across lending decisioning, fraud detection, and customer engagement workflows. These are not experimental applications. They are production systems handling millions of transactions with consistent, measurable performance.

Southeast Asia is laying the foundations for enterprise AI success

Singapore has long been an innovation testing ground, and now it is at a unique inflection point. With the National AI Strategy 2.0, fostering nearly 900 AI startups and attracting US$1.04 billion in fintech investment in H1 2025 alone, the country and the region are establishing themselves as a production hub for enterprise AI. Unlike markets where AI remains primarily experimental, Southeast Asia is seeing financial institutions move directly from exploration to execution. 

Southeast Asian banks are doubling AI-driven value. For instance, one bank grew from US$273 million to US$555 million year-over-year, while DBS generated US$565 million from 350 use cases in 2024 through RM co-pilots and inclusion lending. 

The acceleration of AI adoption reflects both market dynamics and regulatory clarity. The Monetary Authority of Singapore’s sandbox approach and ASEAN regulatory frameworks are creating conditions where institutions can deploy AI at scale with defined governance structures.  

Also Read: 4 marketing trends that will dominate budgets and strategies in 2026

The C-Suite must lead AI governance, infrastructure, and delivery

Moving from pilot to production requires establishing robust governance frameworks before scaling. This means creating detailed AI system inventories, prioritising use cases with clear business value, ensuring data quality, and designing workflows to enable AI autonomy with human oversight. Production success hinges on delivering AI directly into workflows like RM consoles and mobile apps, implementing policy-as-code governance, and pursuing smart partnerships: buy to explore, partner to scale using embedded squads, API-first integration, and revenue-linked contracts.

According to the Bank of England’s Artificial Intelligence in UK Financial Services survey, 84 per cent of firms have established accountable persons for their AI frameworks, and 72 per cent allocate accountability for AI use cases to executive leadership. Yet the same survey reveals that 46 per cent of firms report only partial understanding of the AI technologies they deploy, particularly those sourced from third parties. This gap between governance structures and technical understanding underscores why production-scale deployment requires simultaneous investment in governance clarity, data modernisation, and organisational capability-building.​

Data infrastructure matters equally. Financial institutions increasingly recognise that real-time data capabilities and robust data governance are foundational to production-scale AI deployment. Organisations that establish this infrastructure early, alongside accountability structures and technical understanding of their AI systems, will execute production deployment faster than those attempting simultaneous infrastructure modernisation and AI scaling.

The production transition won’t happen immediately, and organisations must establish foundational infrastructure first, operationalise early wins with measurable business metrics, then scale from demonstrated success. Those executing this roadmap rigorously will move from being stuck in AI pilots to achieving actual production scale. 

With AI adoption growing across sectors, the demand for solutions is evident. What remains is organisational will. In 2026 and beyond, that will be the differentiator between leaders and laggards across financial services, insurance, technology, and beyond.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. Share your opinion by submitting an article, video, podcast, or infographic.

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