In a compelling fireside chat at Echelon Philippines 2025, Raffy Montemayor, Co-Founder of Salmon, shared insights into the startup’s remarkable journey from zero to one million users and the launch of a bank within just 18 months.

Moderated by Thaddeus Koh, Co-Founder and Programs Director of e27, the discussion highlighted Salmon’s ambition to become the leading credit-led modern bank in Southeast Asia, starting in the Philippines.

Montemayor emphasised the importance of a strong founding team, stating that they offer the most attractive Employee Stock Ownership Plan (ESOP) in the region. He noted that the decision to establish a bank stemmed from a need to provide comprehensive financial services to underserved populations. “I can now understand why some companies have co-CEOs because it is not something that I want to do on our own,” he remarked, illustrating the collaborative spirit that drives Salmon’s growth in the local startup ecosystem.

The post Echelon Philippines 2025 – Zero to 1M users and a bank in 18 months appeared first on e27.

During a recent visit to Singapore from February 2-4, Endeavour CEO and Co-Founder Linda Rottenberg engaged with local entrepreneurs and leaders at a pivotal moment for the organisation. Her trip coincided with Endeavor’s first International Selection Panel (ISP) of the year, gathering founders from across Asia and beyond for the final stage of Endeavor’s global selection process.

This visit also marked the soft launch of Endeavor’s global hub in Singapore, ahead of an official launch later this year.

In an email interview with e27, Rottenberg shared her insights on the evolving landscape of entrepreneurship in the region.

“Being back in Singapore for our first ISP of the year feels like a shot of adrenaline,” she remarked. “The shift in founder mindset across Asia is unmistakable and a lot more optimistic than when I was here last year.”

She highlighted Singapore’s emergence as a global hub, attracting businesses such as GoTyme Bank and fostering a new generation of founders eager to scale their ventures internationally. According to Rottenberg, Southeast Asian (SEA) entrepreneurs have developed a remarkable discipline, thriving in challenging capital environments and honing their focus on unit economics and operational resilience.

Also Read: Echelon Philippines 2025 – Zero to 1M users and a bank in 18 months

The following is an edited excerpt of our conversation with her.

After nearly three decades of building Endeavor, you have seen multiple waves of entrepreneurship worldwide. In your view, what distinguishes the small percentage of founders who go on to achieve the true 10x scale?

After almost thirty years of working with founders, one thing still holds true: “Crazy is a compliment.” The ones who scale 10x are willing to dream big and be misunderstood.

But dreaming big is not enough: It is also critical to build operating systems early, focusing on governance, culture, and a repeatable go-to-market strategy. While startup founders are understandably focused on product-market fit and unit economics, we have seen that the softer skills, such as culture and team building, are often what trip people up at scale. You cannot grow your company by 10x if you haven’t tackled these people-and-culture issues early on. The entrepreneurs who succeed also treat constraints as advantages and combine humility with the ability to attract top talent and capital.

Endeavor’s Global VC Trends for 2026 highlights shifting investor priorities globally. What signals are you seeing in Asia’s venture landscape right now that founders should be paying closest attention to?

We are entering what I would call a “Funding Spring”, but it is a cooler, more disciplined one. Seed deals are down sharply, while late-stage rounds are getting bigger. Capital is concentrating behind proven, resilient winners.

The biggest shift is what we call the profitability reset. Investors are no longer impressed by topline growth alone. They want to see EBITDA, strong margins, and defensible technology, especially in AI. In sectors such as fintech, consolidation is accelerating. A handful of deals now account for the majority of funding.

The message is clear: be the consolidator, or get consolidated.

In terms of AI, nearly all conversations in 2025 focused on foundational models, which are being built in Silicon Valley and China. The next wave of AI value creation, Endeavor believes, will be built in the application layer. Much of that innovation will come from elsewhere, including Asia.

Also Read: Why most tokenised real estate startups in SEA fail

In relation to the previous question, Endeavor Catalyst has become a key part of your model for backing high-growth entrepreneurs. How has the role of long-term, founder-first capital evolved as markets become more selective?

In an environment where trust is scarce, founder-first capital matters more than ever. Endeavor Catalyst’s high-conviction, high-trust model backs founders as a co-investor, seeking to “crowd in” smart, connected capital. Our role is to look past the cycle’s noise and back the founder’s long-term vision.

We show up at pivotal moments, whether that means facilitating introductions, offering a sounding board for ideas, or helping provide “reverse due diligence” to help founders really get to know their potential investors. We aim to always do the right thing for the long-term interests of the founders and the company, even if that means pricing a new round of capital as a flat or down-round. There is too much “short-term thinking” in venture today; we aim to play for the very long-term.

In 2025 alone, we made over 320 investor introductions and invested in companies such as Astro and Staffinc in Indonesia. We remain focused on long-term outcomes, not market cycles.

Endeavor’s mission has always been about building multiplier effects—founders helping founders. How do you foster that kind of pay-it-forward ecosystem across very different markets in Asia?

At Endeavor, success is not just measured by valuation. It is measured by what we call the Multiplier Effect: how many others you lift as you rise.

We curate trust-based communities of the top one per cent of entrepreneurs and intentionally break down hierarchy. It is founder-to-founder mentorship, not top-down advice. From day one, there is an expectation to give back.

What is so meaningful is how it compounds. Role models such as Carro, GoTyme Bank, and Thunes do not just scale their own companies; they mentor, invest in, and inspire the next generation.

Also Read: Everyone wants AI agents, but few have the plumbing

When liquidity happens, that capital, experience, and confidence stay local.

Looking ahead, Endeavor is clearly doubling down on Asia at a pivotal time. What is your long-term vision for the region’s role in the global entrepreneurship movement over the next decade?

Asia is at a true inflexion point. We see Singapore serving as the regional nerve centre for capital, talent, and diaspora founders. With upcoming exits, secondaries, and IPOs, we anticipate liquidity that will fuel more multipliers.

But what excites me most is the shift beyond commerce and manufacturing. Deep tech is emerging at scale – robotics and physical AI in Japan, hardware innovation in Vietnam, superapps and integrated platforms serving hundreds of millions, and financial infrastructure that is being exported globally. We are watching R&D leave the lab and turn into real businesses.

Last year alone, we selected new Endeavor companies from Japan, Malaysia, Vietnam, and Indonesia. Founders such as Yoshi Yokokawa of Alpaca represent this next generation: global from day one, technically ambitious, and committed to paying their success forward.

Ultimately, Asia is emerging as the global home of platform-scale companies, and Endeavor’s role is to convert today’s “Funding Spring” into a decade of durable growth.

—

Image Credit: Endeavor

The post Endeavor CEO Linda Rottenberg on why a “Funding Spring” is coming up in Asia appeared first on e27.

Does your team use GenAI tools to review contracts or other sensitive documents?

If you answered yes, you’re not the minority. It seems harmless enough — you paste company text into ChatGPT, type “Help me review this,” and within seconds, you have an analysis of a confidential document.

It feels fast, easy, and harmless. Yet, many do not realise that they have just uploaded confidential corporate data into a public AI model, now beyond your organisation’s control.

This scenario is anything but theoretical. A 2025  report notes that nearly 1 in 20 enterprise users regularly use GenAI tools, and internal data sent to these platforms has surged 30 times year‑on‑year. The same report found that 72 per cent of this shadow AI use, or employee use on personal accounts, occurs outside IT’s purview.

Crucially, this isn’t about bad actors; it’s about convenience. Employees are simply trying to work smarter. But in the process, they’re unwittingly pivoting into insider threats, leaking data outside detection, under the watch of traditional security systems.

The GenAI-driven insider threat landscape

GenAI tools introduce new risks beyond data copy-paste. Prompt injection attacks, where hidden commands are embedded in documents or queries, can co-opt these systems into revealing confidential info or ignoring security protocols. There are real-world exploits like University of California, San Diego’s (UCSD) Imprompter, which had nearly an 80 per cent success rate in extracting personal data via obfuscated prompts.

The risks are compounded when employees unknowingly expose sensitive information like API keys, login credentials, or confidential files in GenAI platforms. Once that data is retained or intercepted, attackers can exploit it to impersonate trusted users and access corporate systems undetected. In such cases, traditional security tools often fail to flag the activity because the access appears legitimate and the data flows may traverse encrypted channels.

Also Read: Bridging the gender gap in GenAI learning: Strategies to get more women involved

Why traditional security alone isn’t enough

Network-level defences like Data Loss Prevention (DLP) and behavioural analytics (such as User and Entity Behaviour Analytics, or UEBA) are vital parts of a layered security strategy. These software tools monitor activity across the network and applications, scanning for risky behaviour like large data exports or unusual file access patterns. They can flag when an employee uploads sensitive files to unsanctioned cloud platforms or external GenAI tools.

But there are limitations. Many rely on visibility into network traffic or sanctioned applications. But when employees upload sensitive documents into public GenAI platforms, these actions can easily bypass logging and monitoring — especially if traffic is encrypted or routed through personal accounts. And in cases where credentials are compromised, attackers can operate from within, circumventing network protections entirely.

A critical missing puzzle piece lies with elevated security, where data lives in the memory of the endpoint.

Layering hardware-based zero trust into GenAI risk management

This is where hardware-level zero-trust comes in, and I’m not talking about passive security like encryption or key management. Encryption is essential for protecting data at rest, and effective key management ensures only authorised parties can decrypt that data. But neither prevents a legitimate user or a GenAI tool with granted access from reading and exfiltrating sensitive information.

Dynamic hardware-level zero trust moves beyond passive safeguards, enabling organisations with:

• Continuous validation of access attempts at the chipset or SSD level
• Anomaly detection for abnormal data reads/writes, including large transfers or mass deletions
• Autonomous lockdowns that block suspicious activity before data leaves the device

Imagine an employee, unaware of the risks, pastes sensitive login credentials or confidential documents into a public GenAI platform to “streamline” a task. Those details are now retained in the AI model or intercepted by threat actors exploiting vulnerabilities in the platform. Later, hackers use the leaked credentials to access corporate systems and attempt to siphon large volumes of sensitive data.

Also Read: GenAI in lending: Faster approvals, smarter risks, and personalised credit

Traditional security tools might miss this, especially if the attackers use the compromised credentials to operate under the guise of a trusted insider. Network monitoring could also be bypassed if the data exfiltration happens over encrypted channels or through sanctioned apps.

Dynamic hardware-level security, however, can detect unusual access patterns — like mass file transfers or abnormal read/write activity– at the physical layer. It does not rely on user credentials or network visibility. Instead, it autonomously blocks the suspicious transfer before any data leaves the device, effectively neutralising the threat even after the breach of access credentials.

Building a GenAI-aware insider threat strategy

To circumvent this threat, a multilayered strategy beyond traditional network security is critical:

• Governance and AI-ready policy: Define which AI tools are approved, specify allowed data types, and require employee attestation.
• Education and culture: Many employees may not be aware of the dangers associated with feeding GenAI tools sensitive data. It’s important to empower them with the right literacy and clear guidelines so AI can be an ally, not an adversary.
• Hardware-level endpoint security: Equipping drives with embedded zero-trust capabilities provides the final defence, autonomously detecting and preventing unauthorised data movement at the most fundamental layer.

Fix the problem, don’t ban the tool

The goal is not to choke out innovation by banning GenAI; it is to make it as safe as possible. A sample playbook could look like:

• Approve a selected set of GenAI services
• Configure DLP and behavioural tools to watch for large data exports
• Enforce intelligent hardware-secured storage on all endpoints
• Train staff on what data should not be shared and why

In the GenAI era, employees are usually well-intentioned, not malicious. Yet, without proper safeguards, they can unintentionally act as insider threats. Bridging governance, training, network monitoring, and hardware-based zero-trust turns GenAI into a secure asset rather than a hidden vulnerability.

Security needs to follow the data to the drive, because that’s where the invisible line between productivity and exposure is drawn.

—

Are you ready to join a vibrant community of entrepreneurs and industry experts? Do you have insights, experiences, and knowledge to share?

Join the e27 Contributor Programme and become a valuable voice in our ecosystem.

Image courtesy: Canva

The post The use of GenAI is turning innocent employees into insider threats: Here’s how to fix it appeared first on e27.

Most startup and growth-company boards talk about “good governance.”

Very few talk honestly about power.

In Venture Capital and Private Equity backed companies, boards are often presented as a collection of equals: executives, nominee directors, and independent directors all sitting around the same table, bound by the same fiduciary duties.

That’s the theory. The reality is far more asymmetric.

The most important difference between nominee directors and independent directors isn’t experience, intelligence, or intent. It’s who they represent and what incentives they carry into the room.

Nominee directors: Speed, capital, and outcomes

VC and PE nominee directors are appointed for a reason: They represent capital with expectations.

They often bring:

• Pattern recognition from dozens of portfolio companies
• Access to funding, talent, and acquirers
• A bias for speed, decisiveness, and accountability

They ask hard questions early:

• Are we growing fast enough?
• Is the CEO still the right person?
• What’s the path to liquidity?

And in many cases, they create enormous value, especially in early and scaling stages where momentum matters more than elegance.

But nominee directors don’t operate in a vacuum.

Their incentives are shaped by:

• Fund return targets
• Exit timelines
• Portfolio-level risk management

This doesn’t make them “bad governors.” It makes them focused owners.

The problem arises when boards pretend those incentives don’t exist.

Independent directors: Stewardship without a sponsor

Independent directors are meant to represent something very different: The institutional integrity of the company itself.

At their best, they:

• Pause board momentum when risk exposure is uneven
• Protect minority shareholders and management credibility
• Ask uncomfortable second-order questions
• Focus on sustainability, culture, and leadership depth

They are often the only people in the room without a liquidity clock ticking.

But independence alone doesn’t create impact.

Many independent directors are:

• Appointed too late
• Poorly briefed on power dynamics
• Treated as ceremonial rather than influential
• Outnumbered in moments that matter most

When that happens, independence becomes ornamental, not functional.

Also Read: Cybersecurity and data governance in the boardroom: A strategic imperative for Asian boards

The real tension isn’t strategy — it’s incentives

Most board conflicts aren’t about market opportunity or product vision.

They’re about:

• Exit timing vs enterprise readiness
• Speed vs resilience
• Control vs stewardship
• Replacement vs development of leadership

Nominee directors tend to optimise for velocity and outcomes. Independent directors tend to optimise for coherence and longevity.

Neither is wrong.

But pretending they are the same role is how boards drift into dysfunction.

Where each role creates the most value

Early and Growth Stages

Nominee directors often create disproportionate value:

• Faster decisions
• Clear accountability
• Capital discipline

Independent directors can struggle to gain traction if the company isn’t ready to listen.

Scaling, pre-IPO, and complexity

Independent directors become essential:

• Risk management
• Governance maturity
• CEO succession
• Reputation and regulatory readiness

This is often where tensions with nominee directors intensify, especially when fund timelines and company readiness diverge.

Also Read: From labs to boardrooms: QAI Ventures bets on Singapore’s quantum future

What great boards do differently

High-performing boards don’t choose between nominee and independent directors. They design the balance deliberately.

They:

• Acknowledge incentives openly
• Empower independent directors early, not late
• Ensure committees aren’t dominated by a single shareholder voice
• Expect nominee directors to govern, not just push outcomes
• Expect independent directors to challenge, not just observe

The most effective boards understand one thing: Speed without guardrails is reckless. Guardrails without speed are irrelevant.

A final provocation

If your board discussions feel “civil” but unresolved, ask yourself:

• Are independents truly independent, or just polite?
• Are nominee directors acting as stewards, or as enforcers?
• And when incentives diverge, who actually decides?

Because governance isn’t about how many seats are independent. It’s about whether power, incentives, and accountability are aligned, especially when it’s uncomfortable.

That’s where real boards earn their keep.

This article was first published on The Boardroom Edge.

—

The post Nominee directors vs independent directors: Who really governs the company? appeared first on e27.

A global wave of AI-driven layoffs is reshaping the tech industry in 2026, with companies citing efficiency gains from artificial intelligence as they trim headcounts amid macroeconomic pressures and massive investments in AI infrastructure. Over 245,000 tech jobs were cut globally in 2025 alone, and early 2026 data shows continued momentum, including significant reductions at major players like Amazon, Meta, and others redirecting resources toward AI. AI luminaries like Geoffrey Hinton have warned that 2026 could mark the onset of more permanent job displacements as the technology gains capabilities to replace roles across sectors.

In this environment, Singapore and broader Asian tech workers are feeling the chill, with social media amplifying stories of restructuring, senior engineers losing positions, and debates over mid-career crises. Two compelling cases highlight a common vulnerability: over-reliance on legacy Windows Server ecosystems in an era dominated by Linux-optimized AI workflows.

Consider Tommy, a veteran Taiwan-based IT leader with over 25 years mastering Windows environments from Active Directory to Azure migrations. Despite strong credentials and high past earnings, he struggled in 2025 interviews at AI-forward companies. Feedback was consistent: solid Windows experience, but a pressing need for Linux talent to handle modern AI deployments.

Similarly, Joycelyn, a Gen X IT manager in London, built her career on Windows Server dependencies, outsourcing complex tasks and advancing through vendor relationships and presentations. When her firm underwent private equity acquisition, scrutiny exposed gaps—she couldn’t manage basic Linux commands or deploy local AI models with tools like Ollama. Insisting on Windows Server in a critical bid backfired when younger engineers flagged it as costly and regressive, leading to lost contracts and her eventual exit.

Also read: Costing comparison of top 7 popular ERP software for food manufacturing in Singapore

These stories share stark parallels in the AI era:

• Windows as a liability: AI frameworks like PyTorch, TensorFlow, and LLM fine-tuning tools are optimized for Linux, where GPU management, multi-card parallelism, and CUDA perform efficiently. Windows’ complex drivers and opaque kernel create bottlenecks for AI workloads.
• Cost scrutiny rules: Enterprises apply rigorous FinOps in 2026, viewing Windows Server licensing and maintenance as expensive compared to Linux plus Kubernetes, which slashes costs and integrates seamlessly with AI pipelines.
• Depth over delegation: Outsourcing core technical work leaves professionals vulnerable. Basic AI tools now enable even novices to run local models on Linux, while managers unfamiliar with command lines risk obsolescence. Companies seek leaders who build and optimize AI systems hands-on.
• Generational shifts: Gen Z engineers prioritize technical integrity and efficiency over traditional hierarchies, viewing legacy commitments as debt. Senior roles once protected by tenure now appear burdensome in agile, AI-centric firms.

The result? Comfort zones become layoff traps amid open-source AI explosions, talent influx, and economic tightening. For Singapore IT workers—operating in a competitive hub with heavy finance-tech overlap and rapid AI adoption—these dynamics hit close to home. Local firms mirror global trends, prioritizing cost control and agility as they integrate AI agents and cloud-native setups.

To avoid becoming the next casualty, Singapore-based IT professionals, especially managers, must act decisively in 2026:

• Prioritize Linux and open-source AI mastery: Treat Linux (Ubuntu, CentOS) as core, not secondary. Daily practice with commands, Docker/Kubernetes deployments, CUDA setups, and tools like Ollama or Hugging Face enables hands-on pilot projects. Singapore enterprises increasingly demand cloud cost efficiency and AI speed—Linux is now mandatory.
• Reclaim technical ownership: End over-reliance on vendors. Lead teams in dissecting systems, enhancing AI workflows, and applying FinOps to compare Windows vs. Linux TCO. Managers who personally construct AI agents demonstrate irreplaceable value.
• Adopt Gen Z perspectives and lead with AI: Embrace technical honesty and efficiency. Shift from being replaced by AI to commanding it—master prompting, agentic workflows, and internal pilots to position yourself as an accelerator, not a bottleneck. Monitor mental health amid widespread upskilling anxiety.

Also read: AI agents and ERP: Why Singapore businesses must act now

AI isn’t the enemy—it’s a transformative tool. Staying entrenched in Windows-centric comfort zones risks mirroring Tommy and Joycelyn’s fates. For Singapore IT workers, survival boils down to outpacing machines and outrunning the layoff wave: upskill faster, transform sooner.

Why we write this article

PRbyAI aims to share updated market news using our team’s tech knowledge, helping B2B customers make informed decisions.

—

Want updates like this delivered directly? Join our WhatsApp channel and stay in the loop.

This article was shared with us by PRbyAI

We can share your story at e27 too! Engage the Southeast Asian tech ecosystem by bringing your story to the world. You can reach out to us here to get started.

Featured Image Credit: Canva Images

About PRbyAI

PRbyAI is a tech-driven Martech startup leveraging cutting-edge AISEO to help customers generate leads and tap into new markets.

The post The 2026 AI layoff wave hits tech: Why clinging to windows server expertise could cost singapore IT workers their jobs appeared first on e27.

At the recent Echelon Philippines 2025, we got to witness this keynote speech by Franco Varona of Foxmont Capital Partners on why foreign startup stakeholders are finally all in on the Philippines. The speech was meant to uncover the dynamic forces behind this major shift.

It revealed how starting in 2024, investments into the startup ecosystem in the Philippines rose with climate tech and logistics leading the charge.

At the end of his speech, Varona stressed on the importance for local ecosystem players to keep on believing despite challenges and naysayers.

The post Echelon Philippines 2025 – Keynote Speech: Confidence. Capital. Country appeared first on e27.

Eezee has secured US$5 million in an oversubscribed pre-Series B round, as the Southeast Asia (SEA)-based procurement platform accelerates regional expansion and deepens investment in AI-driven software.

The funding round was led by Korea Investment Partners Southeast Asia, with existing backers including Kickstart Ventures and Wavemaker Ventures doubling down on their support.

Several strategic investors also participated. The fresh capital will enable Eezee to strengthen its presence across the region and further develop its AI-powered procurement tools, RFQBot and ProcureFlow.

Founded to address inefficiencies in enterprise tail-end spend, Eezee focuses on digitising and automating long-tail, low-value purchases that are often handled manually and remain highly fragmented. The company said its platform reduces procurement cycles from days to minutes, helping customers achieve cost savings of 20 per cent or more.

As part of its growth strategy, Eezee has officially launched operations in Thailand, adding to its footprint in Singapore, Malaysia, Indonesia and the Philippines. The regional push comes amid a more cautious funding climate for SEA’s startups, marked by declining investment volumes and heightened scrutiny around governance and fraud. Against this backdrop, Eezee said the round was oversubscribed, reflecting sustained investor confidence.

Also Read: Why Bitcoin dropped to US$64,100: Trump tariffs, US$2.6B ETF outflows, and extreme fear grip crypto

Since the first quarter of 2025, Eezee said its growth has accelerated quarter by quarter. Its operations in Indonesia and Malaysia have reached operational profitability, while RFQBot and ProcureFlow AI are undergoing a multi-market rollout in the first half of 2026.

Logan Tan, CEO and co-founder of Eezee, said procurement and supply chain workflows have changed little over the past four decades. “Recent advances in AI now make it possible to reimagine both the software layer and the physical movement of goods, combining automation with supply chain optimisation to drive meaningful efficiency and cost outcomes,” he said.

Tan added that the company is seeing a more mature market, increased inbound demand, and a reduced need to educate customers about Eezee’s offering. He described the backing from Korea Investment Partners and returning shareholders as a strong vote of confidence as Eezee works to transform procurement in what he called a pivotal AI era.

With the new funding, Eezee expects to achieve group-level profitability in the second half of the year. The company plans to continue scaling across SEA while expanding its suite of AI-driven procurement tools.

By combining technology with supply chain capabilities, Eezee aims to modernise one of the least transformed enterprise functions, positioning itself as a key player in the region’s evolving digital economy.

Also Read: Singapore’s Diaflow raises seed funding to challenge legacy workflow tools

“Procurement remains one of the largest yet least optimised enterprise functions globally,” said Shane Ang, vice president at Korea Investment Partners Southeast Asia. He added that Eezee has demonstrated strong execution and disciplined growth in a fragmented region, positioning the company to redefine how enterprises manage tail-end spend across SEA.

Established in 1986, Korea Investment Partners is South Korea’s largest venture capital firm by assets under management. Through offices in Seoul, Singapore, Silicon Valley, Beijing and Shanghai, the firm has backed companies including Kakao, YG Entertainment, ABL Bio and Moloco.

—

Image Credit: Eezee

The post Eezee raises US$5M to scale AI procurement tools, fuel Southeast Asia expansion appeared first on e27.

DBS is moving decisively deeper into private markets — and this time, it’s not going alone. It’s bringing its wealth clients with it.

The bank’s three-year partnership with Granite Asia, launched with a US$110 million AI-focused IPO fund, is more than a product rollout. It’s a structural play. DBS is using its private banking distribution to channel capital into a curated slice of Asia’s AI pipeline — companies mature enough to contemplate public listings, yet still navigating the final stretch of growth.

AI is the hook. The ambition is larger.

With over 13,000 AI startups founded in Asia since 2015, the funnel is crowded. Few will reach IPO stage. Fewer still will do so smoothly. That’s where this partnership positions itself: combining Granite Asia’s sourcing and IPO track record with DBS’s financing, advisory, and capital markets muscle.

For founders, this could mean alternatives to dilutive equity rounds, access to structured financing, and IPO preparation support. For wealth clients, it’s institutional-style access packaged within a private banking channel.

The signal is clear. As venture funding tightens and listings cautiously reopen, DBS isn’t waiting for the cycle to turn generous again. It’s building a repeatable bridge between private wealth, growth capital, and Asia’s next wave of tech companies — starting with AI.

REGIONAL

DBS doubles down on private markets with US$110M AI IPO fund: DBS has partnered Granite Asia to channel wealth capital into AI-focused IPO funds and private financing, linking private banking clients with high-growth Asian companies seeking scale, liquidity, and market access.

US$11.5M at stake: Society Pass and ex-CMO clash ends in mixed court ruling: Nasdaq-listed Society Pass and former CMO Thomas O’Connor received a split New York verdict preserving pre-2019 warrant equity, voiding CVO contracts, forfeiting later pay, and leaving SPI facing multimillion-dollar liabilities.

SG procurement firm Eezee raises US$5M pre-Series B: Investors include Korea Investment Partners, Kickstart Ventures, and Wavemaker Ventures. The funding will support Eezee’s expansion across Southeast Asia and further development of its AI-powered procurement tools, RFQBot and ProcureFlow.

Singapore’s Diaflow raises seed funding to challenge legacy workflow tools: Insignia Ventures is the lead investor. Since launching in February 2025, Diaflow says it has grown to more than 10,000 users and organisations globally, with over 60% of adoption coming from the US.

TikTok Shop beats Shopee in Vietnam’s Lunar New Year: A report says TikTok Shop captured 52% market share as holiday spending hit US$2.6B and overall e-commerce revenue rose 9%. On the other hand, Shopee’s share declined to 48%. TikTok Shop’s growth rate was nearly twice that of Shopee during the peak period.

FEATURES & INTERVIEWS

Tech leaders applaud Singapore Budget 2026’s AI-first strategy but urge focus on context, capability: The budget places AI at the core of economic strategy, launching a National AI Council, sector missions, enterprise incentives, infrastructure, and workforce programmes to move decisively from experimentation to execution.

Jayce Tham: Rethinking creativity for Southeast Asia’s new AI economy: A seasoned creative industry leader, Tham bridges artistic talent, freelance ecosystems, and next-generation AI. Since launching CreativesAtWork in 2012, she has built a cross-border, on-demand talent network spanning branding, design, video, and production.

INTERNATIONAL

Hong Kong stablecoin unicorn RedotPay eyes US$1B US IPO: The listing could occur in New York as early as this year. The valuation may exceed US$4B, but details are still being finalised. RedotPay raised US$194M in 2025, including a Series B in December, reaching unicorn status.

Meta docs warn encryption could cut child abuse reports: The firm’s internal documents reveal that in 2019, company executives discussed potential risks associated with implementing end-to-end encryption on Facebook and Instagram messaging services, despite public claims of safety improvements.

India plans to raise US$19.7B from state IPOs by 2030: The government aims to monetise assets across sectors including railways, power, oil and gas, aviation, and coal. The IPOs include stakes in seven railway companies, which could potentially raise US$9.2B by 2030, with US$1.8B targeted in the upcoming fiscal year starting April 2026.

SK Telecom to back 15 AI, ESG startups to court Europe VCs: The Korean telco said the 15 participating startups come from diverse backgrounds, ranging from AI consulting and optimisation, cybersecurity and data security, data infrastructure, to renewable energy, and ecosystem restoration.

Coupang faces US hearing on regulations: The S Korean e-commerce firm’ interim CEO Harold Rogers testified before the US House Judiciary Committee on February 23 amid concerns over data leaks and regulatory issues. The hearing focused on allegations of discriminatory treatment by Korean authorities against US companies.

CYBERSECURITY

Underfunded and under fire: Indonesia’s cyber startups face 2025 reality: Indonesia’s cybersecurity sector faces rising AI-driven threats and regulatory pressure, but funding remains muted, creating opportunities in anti-fraud, identity, MDR, and locally hosted, outcome-driven security solutions.

Singapore’s cybersecurity paradox: Why we must act now: After UNC3886 exposed Singapore’s cyber vulnerabilities, regional cybersecurity funding collapsed 96%, threatening digital sovereignty and underscoring urgent need for stronger investment, talent pipelines, and public-private collaboration.

Cybersecurity stocks fall as new Anthropic tool sparks AI fears: The AI lab debuted a limited research preview of a service that scans software code for vulnerabilities and offers solutions on February 20. Shares of companies such as CrowdStrike and Zscaler fell about 10%, while Netskope and Tenable dropped around 12%.

SEMICONDUCTOR

Singtel’s InfraCo, Nvidia launch AI centre of excellence: The CoE will focus on developing data centre designs for next-generation Nvidia GPUs, building an AI ecosystem, enhancing edge AI capabilities, and cultivating AI talent. The initiative aligns with Singapore’s Budget 2026, which emphasises AI as a strategic national asset.

Indonesia’s Danantara, UK-based Arm sign semiconductor deal: The collaboration involves Indonesia sending 15,000 engineers to develop expertise in semiconductor design. It aims to advance Indonesia’s control over semiconductor tech, with Arm holding significant shares in global chip design for automotive, data centres, and AI sectors.

Chip demand lifts S Korea consumer confidence to 3-month high: The consumer confidence reached 112.1 in Feb, according to the Bank of Korea. The increase was driven by improved assessments of current economic conditions and optimistic expectations, supported by strong semiconductor shipments and a rising stock market.

AI

Big Tech said to invest US$650B on AI in 2026: The figure rose from US$410B invested in 2025, according to Bridgewater Associates. Bridgewater’s co-CIO Greg Jensen noted that the AI sector is entering a “more dangerous phase,” with increased spending on physical infrastructure and reliance on outside capital.

The real risk in ASEAN’s AI race is not falling behind. It is falling apart: ASEAN’s AI ambitions face a critical test in cybersecurity, as uneven governance, digital literacy gaps, and rising AI-enabled threats risk undermining trust, cross-border resilience, and long-term regional innovation.

Southeast Asia’s AI boom is built on steel, not startups: The AI boom is driven by hyperscaler data centres, undersea cables, and power infrastructure, but local startups lag as compute investment outpaces venture funding and policy coordination.

Momentum without maturity: Southeast Asia’s AI reality: If AI tools remain priced and packaged for enterprise procurement teams, the region gets an ugly outcome: big firms compound their productivity advantages while small firms fall further behind, even if the technology itself is “available”.

How AI is enhancing personalisation in open banking through data-driven insights: AI is reshaping fintech through hyper-personalisation, enabling tailored recommendations, real-time financial advice, dynamic credit scoring, intelligent chatbots, and fraud detection to deliver frictionless open banking experiences.

THOUGHT LEADERSHIP

Why venture capital must become venture architecture: When money is no longer the hard part: As AI lowers building barriers and exits slow, Southeast Asian venture capital must evolve from picking winners to designing pathways that enable adoption, cross-border scale, and durable growth.

The agentic era of marketing: Why real-time reasoning is replacing traditional automation: Marketing is entering the agentic AI era, where systems reason, adapt, and optimise in real time, shifting focus from automation to unified intelligence, dynamic context, and scalable, autonomous operations.

How policy shocks are rewriting cloud strategy in Southeast Asia: The region’s founders are rethinking hyperscaler dependence as pricing shifts, service retirements, and regulatory fragmentation expose cloud infrastructure as strategic risk rather than neutral utility.

Beyond the spreadsheet: Why your data is dead without a storyteller: Businesses collect vast data yet struggle to drive decisions because numbers lack narrative. Turning analytics into compelling visual stories transforms information into action, creating competitive advantage for startups and enterprises alike.

5 crypto events that will make or break 2026: What investors must know before April: Q2 2026 could redefine crypto as US legislation, ETF approvals, UK tax access, Fed leadership shifts, and EU MiCA rules converge to unlock capital, clarify regulation, and reshape global liquidity conditions.

The fragmentation trap: How too many platforms are killing startups: Today’s startup ecosystem is fragmented across platforms, wasting founders’ time and rewarding vanity metrics. What it needs isn’t more tools, but consolidated infrastructure built on verified performance and open access.

From cold code to warm smiles: How Singapore automates human connection: As global tourism automates, Singapore uses AI and immersive tech to free staff, preserve empathy, and scale personalised experiences without sacrificing human warmth.

The architecture of rejection: Why ventures fail funding audits across both investors and institutional allocators: In SEA’s funding landscape, investors forgive mess but not structural risk, demanding operational discipline, clean governance, and verifiable controls before deploying institutional capital into growing ventures.

Islamic fintech in Southeast Asia: Decline or revival?: The latest Global Islamic Fintech Report shows OIC dominance, but Southeast Asia remains resilient, driven by digital assets, AI innovation, and growing regulatory cooperation to sustain regional leadership.

The post Ecosystem Roundup: DBS launches US$110M AI IPO fund; SEA’s AI boom runs on steel; Indonesia’s cyber startups face 2025 crunch appeared first on e27.

Recently, I was contacted by a local business owner who had spent over US$50,000 on a consulting project. The consultant had promised to help them set up their regional outreach, with the added incentive of helping them secure government grants to fund the expansion.

It sounded like a win-win. Until it wasn’t.

After nearly a year of waiting, the final delivery was a hastily assembled report — the kind of document an intern could have compiled in a week. It included five half-hearted meetings with local business owners, no concrete leads, and no actionable strategy.

Fifty thousand dollars. One year lost. Zero results.

And this isn’t an isolated case. It’s a pattern — a structural market failure powered by information asymmetry.

When trust becomes a liability

For a small business, that isn’t just disappointing — it’s devastating. That US$50,000 could have gone into hiring a sales manager, a business development lead, and expanding marketing outreach with localised content.

Let’s be honest; if you had hired a local sales manager and a BD executive instead of a consultant, would you have accepted the same results? Five casual meetings in a year? A recycled report with no measurable outcome?

Of course not. As a boss, you’d have set clear KPIs — leads generated, partnerships closed, conversion targets met. You’d track progress weekly, demand accountability, and release pay based on performance, even firing underperforming staff to find someone that meet your expectations.

Yet when it comes to consultants, agencies, and external vendors — businesses suspend these same expectations: They pay upfront. They wait for results. They accept excuses.

It’s not because they’re careless — it’s because the system is built on trust without verification.

Also Reda: The architecture of bad deals: Moral hazard in modern business

How businesses can protect themselves

The truth is, you don’t need to be cynical to stay safe — just systematic.

Trust doesn’t have to disappear from business. It just needs structure.

Here’s how to protect your company from the broken outsourcing ecosystem, and make sure every partnership you pay for produces results.

Define clear KPIs before you sign anything

Before you hire any consultant, agency, or vendor, ask: “What does success look like, and how will we measure it?”

If they can’t answer in numbers or milestones, walk away.

A real professional defines outcomes, not adjectives.

Examples:

• “Generate 1000 qualified leads in 3 months” — not “support business growth.”
• “Secure a minimum of 10 verified partner meetings” — not “explore opportunities.”
• “Launch campaign with three deliverables and two iterations” — not “increase brand awareness.”

Why it matters: Vague scope = no accountability. Clarity creates leverage.

Demand transparency in process and people

Ask who is actually doing the work, and how it’s being managed. Don’t settle for brand names or titles; request profiles, portfolios, and project structures.

Questions to ask:

• Who will be the point of contact executing the project?
• Will any part of the work be subcontracted or outsourced?
• What reporting tools or dashboards will we use to track progress?

Why it matters: When you pay an agency, you’re often paying for coordination — not expertise. Transparency helps you see where your money truly goes.

Also Read: Starting a business in 2026: What Founders should consider before chasing capital

Use milestone-based payments

Never pay 100 per cent upfront. Structure payments around delivery checkpoints.

For example:

• 20 per cent deposit upon signing (to begin work)
• 30p er cent after the first milestone (e.g., draft, mock-up, or report)
• 30 per cent after the second milestone (e.g., review and revisions)
• 20 per cent after final approval and delivery

This aligns incentives. If they disappear, you lose 20 per cent — not everything. If they deliver, everyone wins.

Why it matters: Payment schedules turn trust into measurable progress.

Keep a paper trail

Every conversation, deliverable, and update should be documented — in writing. WhatsApp messages and phone calls don’t protect you; written agreements do.

What to keep:

• Contract with clear deliverables and deadlines
• Email summaries after every key meeting
• Shared folders for deliverables and reports
• Written confirmation on change requests

Why it matters: Paper trails turn “he said, she said” into verifiable truth. They’re your best defense if accountability breaks down.

Verify before you trust

Due diligence is not optional, it’s survival.

Before hiring, check:

• References and client testimonials (and call them)
• Portfolio authenticity (ask for proof of ownership)
• Business registration and legal standing
• Presence across verified channels (LinkedIn, website, directory listings)

If something feels off, it probably is. You’re not being paranoid — you’re being professional.

Insist on performance reviews

Treat external vendors like internal staff. Schedule review checkpoints to evaluate output, timing, and quality. Don’t wait until the end to discover failure.

Example: Weekly or bi-weekly status calls, written updates, and deliverable progress reports.

Why it matters: Early detection prevents total collapse.

Use platforms that engineer trust

The easiest way to ensure all of this happens? Use systems built for it.

That’s where Globaloca Asia comes in: we are building a AI powered platform designed to provide transparent vendor sourcing and accountability in project management.

We make transparency, verification, and milestone tracking part of the workflow:

• Every vendor is verified.
• Every project runs through milestone-based escrow.
• Every deliverable is tracked and timestamped on your dashboard.

It’s not about distrust — it’s about design. We don’t replace human relationships. We protect them.

Final thought

Every business owner deserves confidence — but confidence should come from clarity, not charisma.

Define your metrics. Document your expectations. Design accountability into every deal.

Because in the Information Age, trust without verification isn’t partnership — it’s risk you should avoid.

—

The post “Let’s have that in writing”: Building real accountability in a world of empty promises appeared first on e27.

In this interview, e27 speaks with Kai Yong Kang, Partner at GenAI Fund, Southeast Asia’s first AI-focused fund dedicated to helping large organisations adopt AI responsibly and at scale. Founded by former senior executives from Amazon Web Services, the fund brings a rare inside-out perspective on enterprise transformation, shaped by years of working with governments, multinationals, and high-growth technology companies across the region.

Rather than treating AI as a standalone technology bet, GenAI Fund operates at the intersection of enterprise decision-making, execution, and long-term value creation.

This conversation forms part of e27’s broader AI Pulse coverage, which examines how organisations across the region are building, deploying, and governing AI in real-world settings.

Advancing responsible enterprise AI adoption

e27: Briefly describe what your organisation does, and where AI plays a meaningful role in your work or offering.

Kai Yong: GenAI Fund is Southeast Asia’s first AI-focused fund dedicated to helping large organizations adopt AI responsibly and at scale. The fund was founded by former senior executives from Amazon Web Services, who spent many years building and scaling the AWS startup and enterprise ecosystem across Southeast Asia and Pakistan, growing the regional business by more than 10×. In their previous roles, they worked closely with governments, multinational corporations, and high-growth technology companies, supporting the adoption of new technologies including AI that directly shaped how people work, live, and make decisions.

At GenAI Fund, we operate at the intersection of enterprise decision-making, emerging technology, and long-term value creation. Every day, we see how AI moves from an abstract idea into real systems that power banks, hospitals, manufacturers, and national infrastructure and just as importantly, where AI should not be applied.

Our work spans three closely connected areas. The first is digital transformation. We help large enterprises and governments understand where AI truly creates value and where it does not. Often described as the McKinsey for AI, our role is to guide organizations from initial awareness, through pilot programs, and into scaled, production-level deployment. To date, we have supported more than 100 large enterprises across Asia, including global companies such as Coca-Cola and KFC, as well as regional institutions like UOB and Prudential. Our work involves shaping AI strategy, identifying the right use cases, and connecting organizations with the right partners from a curated network of more than 2,600 AI startups across the region. Alongside this, we have trained over 20,000 government officials and enterprise executives on how to think about AI clearly, responsibly, and pragmatically.

The second area is investment. We invest in AI startups that are ready to work with real enterprises and real constraints, rather than theoretical use cases. Through our flagship FastTrack AI Accelerator program, run in collaboration with NVIDIA, selected startups receive direct investment from GenAI Fund, are matched with guaranteed enterprise engagement opportunities, gain access to up to US$1,000,000 in compute resources, and are supported through live enterprise pilot projects. This approach ensures that innovation is tested in real business environments, where outcomes matter and assumptions are challenged.

The third area is ecosystem development. Because we see the same patterns repeated across industries and countries, we believe it is important to share what actually works. Since 2023, we have hosted 30 AI events and programs across Asia, including Japan, together with partners such as AWS, Google Cloud, NVIDIA, Databricks, and FPT. These initiatives have reached more than 4,000 participants, including C-level leaders, senior executives, and technology founders. This experience culminates in our upcoming regional AI adoption conference, which will bring together 5,000 participants, showcase more than 100 real enterprise AI case studies, and facilitate 500 curated sessions between enterprises and startups, with a clear goal of launching 100 real AI pilot projects.

Also read: AI Pulse Exclusive: How CoBALT is designing AI that teams can actually trust

Accelerating enterprise AI sourcing through matchmaking

e27: What is one concrete way AI is currently creating value within your organisation or for your users or customers?

Kai Yong: One concrete way our AI platform creates value for enterprises is by significantly reducing the time required to source, evaluate, and engage qualified AI solution providers for real operational use cases. Traditionally, enterprise AI sourcing is a slow and fragmented process, often taking weeks or months of manual research, referrals, and vendor screening before meaningful discussions begin. Our AI matchmaking platform compresses this cycle into minutes by translating enterprise use cases into structured requirements and automatically shortlisting and ranking AI startups based on technical fit, industry relevance, and deployment readiness.

This was demonstrated at Tasco Innovation Day, where Tasco JSC opened more than 30 live use cases across mobility, automotive, insurance, and infrastructure. Using our platform, Tasco was able to review over 300 global AI startup proposals and move directly into 71 closed-door business meetings with decision-makers within six weeks—something that would typically take several months through traditional sourcing channels.

Beyond a single event, this capability is scaled through our GenAI Open Innovation initiatives, where the platform supports over 100 enterprises and a curated database of 2,600+ AI startups across the region. To date, more than 500 AI startup–enterprise matches have been facilitated, with over 100 progressing into active or launched Proofs of Concept (PoCs), including one FastTrack startup that recently secured a multi-million-dollar enterprise deployment following this AI-enabled sourcing process.

Evolving from investment fund to transformation platform

e27: What was a key decision or trade-off you had to make when adopting, building, or scaling AI?

Kai Yong: A key decision we made was to evolve from a traditional investment-led model into an end-to-end enterprise AI transformation platform. Early on, we realized that capital alone does not drive real-world AI adoption—especially in Southeast Asia, where enterprises face fragmented data, limited internal AI readiness, and complex procurement processes. To generate meaningful outcomes for both startups and enterprises, we chose to move beyond being passive investors and become an active execution partner across the entire adoption journey—from leadership alignment and use-case definition to pilot delivery and production scaling. This meant investing in our AI matchmaking platform and transformation frameworks, and running “Working Backwards” workshops to help enterprise leaders align on high-impact use cases before any technical work begins.

Working this closely with enterprises requires dedicated time and new capabilities across strategy, technology, and change management, which also led us to build a strong regional network of domain experts, technical advisors, and operators who now support deployments alongside our team. That investment has paid off. We have supported over 100 enterprise AI initiatives into Proof of Concept, created structured pathways for startups to engage real buyers, and helped multiple projects progress toward production deployment and commercial contracts—turning AI from isolated experiments into revenue-generating collaborations.

Also read: AI Pulse Exclusive: How Asia AI Association is advancing human-centred AI across the region

Momentum in enterprise collaboration and scaling challenges

e27: Looking back, what has worked better than expected, and what proved more challenging than anticipated?

Kai Yong: First, looking back at 2025, what exceeded our expectations most was the level of openness from large enterprises to collaborate deeply with AI startups. We initially anticipated a slow, conservative adoption curve. Instead, over 100 enterprises across banking, mobility, retail, manufacturing, and infrastructure actively engaged our ecosystem with real operational problems. Many moved quickly from exploration to pilots—and in several cases beyond—showing strong urgency to deploy AI for immediate business impact. Most surprisingly, some enterprises were willing to go beyond being customers and explore co-investment opportunities with startups following successful Proofs of Concept. This created a high-velocity environment where startups could secure multi-million-dollar enterprise deals and regional contracts far faster than traditional B2B cycles typically allow. It reinforced our belief that when enterprise innovation is anchored in real use cases and supported by the right execution framework, momentum accelerates rapidly.

Second, the biggest challenge has been moving from Proof of Concept to production at scale. While building a working prototype is often fast, enterprise-wide deployment introduces human and structural complexities that go far beyond the technology itself. Through our work with over 100 enterprises, three recurring friction points emerged:

1. Organizational readiness: AI cannot simply be “plugged in” to existing workflows. Successful deployment requires rethinking processes, ownership, and decision-making. Without this, even strong solutions struggle to take root.
2. Stakeholder alignment: Many projects stall due to gaps between executive intent, technical teams, and frontline operators. Without buy-in from middle management and clear operational ownership, momentum fades after the pilot phase
3. Measuring production impact: While pilots demonstrate technical feasibility, translating results into clear cost savings or revenue impact—aligned to existing business OKRs—is often harder, making it difficult to secure long-term investment for scaling.

Ultimately, we learned that the real work begins after the PoC. Moving from pilot to production is less a technical challenge and more an organizational one. Enterprises that succeed are those that treat AI as an operating model shift—not just a software deployment—and invest as much in change management and execution readiness as they do in the technology itself.

AI adoption as an organisational challenge

e27: What is one lesson about applying AI in real-world settings that leaders or founders often underestimate

Kai Yong: One lesson leaders and founders consistently underestimate is that deploying AI is primarily a people and operating-model challenge—not a technical one. Many organizations assume that once the tools are in place, adoption will follow. In reality, most AI initiatives stall because teams are not aligned on ownership, workflows, or decision-making. Without clear executive sponsorship, cross-functional accountability, and practical integration into daily operations, even strong AI solutions end up sitting unused. Another overlooked factor is employee perception. When AI is introduced without clear communication, it is often viewed as a threat rather than an enabler. This slows adoption, degrades data quality, and limits feedback—ultimately reducing the effectiveness of the system itself.

At GenAI Fund, we address this by starting with leadership alignment through Working Backwards workshops, building team readiness via AI Readiness bootcamps, and driving behavior change through hands-on Proofs of Concept in our GenAI Open Innovation programs. Practical exposure to real use cases helps demystify AI and builds internal confidence far more effectively than theoretical training. The leaders who succeed with AI in real-world settings are those who invest as much in change management, ownership, and execution readiness as they do in models and infrastructure.

Practical guidance for early AI adoption

e27: Based on your experience, what is one practical recommendation you would give to organisations that are just starting to explore or scale AI?

Kai Yong: Based on our experience supporting enterprise AI adoption across Southeast Asia, one practical recommendation for organizations starting or scaling AI is to focus early on two things: organizational readiness and fast, outcome-driven execution tied to business KPIs.

1. Start with people and operating readiness—not technology. Most AI initiatives fail not because of model performance, but because teams are not aligned on ownership, data access, or decision-making. Enterprises should establish clear executive sponsorship, cross-functional ownership (business + IT), and transparent communication with employees. When teams understand that AI is meant to augment their work rather than replace them, data quality improves and adoption accelerates.
2. Drive quick wins linked directly to cost savings or revenue growth—and map them to existing OKRs. Rather than launching broad transformation programs, enterprises should start with narrowly scoped use cases that can demonstrate measurable impact within 60–90 days—such as reducing manual processing costs, improving conversion rates, or accelerating sales cycles. Anchoring pilots to existing organizational OKRs ensures accountability, unlocks budget, and prevents teams from getting stuck in “pilot purgatory.” In practice, organizations that combine readiness with fast, metric-driven execution move significantly faster from experimentation to production—turning AI from isolated projects into a scalable business capability.

Also read: AI Pulse Exclusive: How Explico is building AI teachers can actually rely on

Accelerating enterprise AI deployment timelines

e27: Over the next 12 months, how do you expect your organisation’s use of AI, or the role of AI in your industry, to evolve?

Kai Yong: Over the next 12 months, we expect a fundamental acceleration in how enterprises move from AI exploration to real deployment. Historically, large organizations take 3–5 years to progress from initial awareness to production-scale AI adoption. At GenAI Fund, our goal is to compress this cycle into a single year by using AI itself to orchestrate the transformation journey.

Our 2026 strategy focuses on accelerating three critical stages:

Awareness: Moving enterprises beyond surface-level AI curiosity through leadership alignment initiatives, masterclasses, and “Working Backwards” workshops—helping executive teams translate operational challenges into prioritized AI use cases tied directly to business outcomes.

Pilot: Leveraging our GenAI Open Innovation model coupled with our AI matchmaking platform to reduce solution sourcing and validation from weeks to minutes, enabling enterprises to rapidly identify qualified AI providers and launch structured pilots within weeks rather than months.

Scale: Transitioning successful Proofs of Concept into production through our FastTrack AI Accelerator, supported by hyperscalers and hands-on execution sprints—providing technical guidance, deployment support, and commercialization pathways to drive enterprise-wide adoption. By integrating these stages into a single operating model, we expect enterprises to move faster from intent to impact.

Rather than simply helping companies “adopt” AI, our platform and programs are designed to help them operationalize AI at speed—turning fragmented experimentation into measurable business outcomes and building AI-native capabilities within one fiscal year.

Building toward GenAI Open Innovation Summit 2026 (GOI Summit 2026)

e27: Anything else you want to share with the audience?

Kai Yong: One final thing we’d love to share is what we’re building toward in 2026. Later this year, we’ll be launching GOI Summit 2026 as our flagship enterprise AI conference—bringing together enterprises, AI startups, hyperscalers, governments, and investors from across the region. Our ambition is to create a regional “big bang” moment that positions Southeast Asia as the fastest AI adoption market globally. GOI Summit is not a standalone event—it’s the culmination of a year-long program designed to drive real adoption.

Leading up to the summit, we are running a series of initiatives including monthly GenAI Builders Meetups, GenAI Open Innovation programs with enterprises, and our scaling accelerator with hyperscaler support to help startups move from pilots to production.

Together, these form our “Road to GOI Summit,” continuously matching enterprises with AI builders, validating use cases, and pushing real deployments throughout the year. At the summit itself, we expect over 5,000 attendees, including more than 100 CIOs from large enterprises, thousands of enterprise executives, and 1,000 AI startups globally. Our goal is to facilitate 500 curated enterprise–startup matchmaking sessions and catalyze at least 100 new AI Proofs of Concept directly from the event, alongside showcasing 100+ real enterprise AI case studies.

More broadly, we see Southeast Asia at a unique inflection point. With rapidly digitizing enterprises, growing AI talent, and increasing urgency to stay competitive, the region has the opportunity to leapfrog into global leadership in applied AI. GOI Summit 2026—and everything leading up to it—is our way of accelerating that future by turning AI ambition into measurable execution.

Enterprise AI adoption at scale

This conversation highlights the accelerating shift from AI experimentation to real enterprise deployment across Southeast Asia. As organisations move beyond pilots toward operational integration, the focus increasingly turns to execution readiness, ecosystem collaboration, and measurable business outcomes. Initiatives that combine investment, transformation expertise, and ecosystem building may play a key role in shaping how AI adoption scales across the region.

For more interviews, analysis, and real-world perspectives on how organisations across the region are applying AI in practice, subscribe to our newsletter. You can also explore more AI stories here.

—

Enjoyed this read? Don’t miss out on the next insight. Join our WhatsApp channel for real-time drops.

The e27 team produced this article

We can share your story at e27 too! Engage the Southeast Asian tech ecosystem by bringing your story to the world. You can reach out to us here to get started.

Featured Image Credit: GenAI Fund

The post AI Pulse Exclusive: How GenAI Fund is accelerating enterprise AI adoption across Southeast Asia appeared first on e27.