The tech layoffs of 2025 were not distributed evenly across the globe. Instead, they were concentrated in specific geographic hubs, revealing a new map of economic vulnerability.

Data from UK-based forex company RationalFX shows that US-headquartered companies accounted for 69.7 per cent of all global tech layoffs, with California and Washington State bearing the brunt.

California: The epicentre of disruption

California remains the heart of the global tech industry, and consequently, its primary casualty. The state recorded 73,499 job cuts in 2025, accounting for roughly 43.08 per cent of all tech layoffs in the US. Silicon Valley’s heavyweights — including Intel, Salesforce, Meta, and HP — were the primary drivers of these redundancies.

Also Read: Big Tech’s efficiency paradox: Record profits, record layoffs

Washington State followed as the second-hardest hit hub, with 42,221 jobs lost. The state’s reliance on Microsoft and Amazon (which together cut nearly 40,000 roles) makes its local economy uniquely sensitive to the strategic shifts of just two corporate boards.

The rise of New York

Interestingly, New York State rapidly climbed the layoff rankings toward the end of the year, recording 26,900 job cuts. The vast majority of these were concentrated in New York City, which now accounts for 15.8 per cent of the US total. IBM was the single most significant contributor to New York’s woes, responsible for 9,000 redundancies in the state alone.

Europe’s fragile tech ambitions

Across the Atlantic, Ireland emerged as Europe’s most affected nation. This was primarily due to Accenture’s global restructuring, which saw 11,000 jobs cut from its Irish operations as part of its AI strategy. Other European players, such as Spain’s Telefónica, also contributed to the regional total by eliminating 7,000 roles late in the year.

However, the most symbolic failure in Europe was Northvolt’s collapse. The Swedish battery manufacturer, once hailed as Europe’s answer to Asian battery dominance, filed for bankruptcy in March 2025. The move left at least 3,000 employees jobless and underscored the difficulty Western firms face in competing with established manufacturing hubs in China, Japan, and South Korea.

The Asian shift

The RationalFX report highlights a stark geopolitical reality: while Europe and the US were shedding roles, battery production and high-end hardware manufacturing remained firmly centred in Asia.

Also Read: When tech titans blink: 2025 exposed the Old Guard’s fragility

As we look toward 2026, the geographic concentration of these layoffs suggests that the “tech hubs” of the past decade may be the most volatile places to work in the next one. The global workforce is being redrawn, and for now, the lines are being written in Silicon Valley and Seattle, but the consequences are being felt from Skellefteå to Bangalore.

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The full report can be accessed here.

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Southeast Asia’s food delivery landscape has entered a paradoxical era. While the total gross merchandise value (GMV) for the region surged by 18 per cent year-on-year to reach a staggering US$22.7 billion in 2025, the individual value of each order is actually shrinking. This shift marks a fundamental change in strategy for the region’s dominant players: Grab, ShopeeFood, and Gojek.

According to the 6th annual “Food Delivery Platforms in Southeast Asia” report by Momentum Works, platforms are now converging on affordability as their primary growth engine. This move is systematically driving average order values (AOVs) lower across every major market.

Also Read: How mobile marketing is powering the next phase of food delivery growth in Southeast Asia

In the early growth phases of the 2020s, platforms relied heavily on massive subsidies to acquire users across all price points. As the industry pivoted toward profitability in the early 2020s, those subsidies were slashed, and user bases narrowed to core, higher-spending segments.

However, the report indicates that growth pressure has returned in 2025, forcing platforms to look beyond their affluent core. The result is a renewed focus on “cost-first” consumers, who were previously priced out of the convenience economy.

The strategy of bundles and “saver” deliveries

The evidence of this convergence is visible in the product roadmaps of every major platform. Grab has aggressively rolled out its “GrabFood for One” and “Shared Saver” initiatives to reduce the entry price for single-person households. In Indonesia, Gojek (through GoFood) and Grab have both lowered the prices.

This isn’t just about vouchers; it’s about structural product changes. By introducing “saver” delivery options, where users accept longer wait times in exchange for lower fees, platforms are able to batch orders more efficiently, effectively lowering the cost-to-serve while capturing price-sensitive demand.

Thailand, the region’s second-largest market with a US$5.1 billion GMV, has seen the highest growth at 22 per cent, mainly driven by these affordability initiatives and the government’s “half-half” co-payment stimulus scheme.

A move toward mass adoption

The logic behind driving AOVs lower is to transform food delivery from an occasional luxury into an everyday habit for the mass market. Momentum Works estimates that between 8.5 million and 9.5 million food delivery orders are now fulfilled daily across Southeast Asia. To keep this number growing, platforms must unlock segments of the population that previously viewed US$5 to US$10 meals as too expensive.

However, this “race to the bottom” creates a challenging environment for merchants. While the report notes that order frequency is increasing as subscriptions and vouchers normalise repeat ordering, the downward pressure on pricing means restaurants must operate with extreme efficiency. Medium-sized merchants, in particular, are finding themselves squeezed as platforms use their vast datasets to influence pricing and promotional positioning.

The global benchmark

The shadow of China’s delivery market looms large over these developments. Meituan and Alibaba have spent over US$11 billion on subsidies during their domestic delivery wars, creating a market where more than 30 per cent of orders are now beverages. Southeast Asian platforms are selectively adopting China-inspired tactics, such as affordable bundled meals and prepaid vouchers, to defend their market share against potential entry by new, hyper-efficient competitors like Meituan’s Keeta.

Also Read: Understanding the economics of food delivery platforms

As 2026 approaches, the success of a platform will no longer be measured by how much it can charge per order, but by how many millions of low-margin orders it can orchestrate through its ecosystem without breaking the unit economics of its delivery fleet.

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As businesses across Asia look to the future, generative AI (GenAI) rapidly emerges as a powerful driver of growth and innovation. Adobe’s 2025 AI and Digital Trends Asia snapshot offers a detailed examination of how regional organisations adopt GenAI and the challenges they face in turning promise into performance. More importantly, the report provides key recommendations for companies capitalising on GenAI’s transformative potential.

According to Adobe, Asian organisations see a broader return on investment from GenAI adoption than their counterparts in the wider Asia Pacific and Japan (JAPAC) region. Senior executives cite benefits such as freeing up resources for strategic initiatives (55 per cent) and boosting revenue through more effective marketing (53 per cent).

Additionally, businesses are applying GenAI across diverse functions, including optimising customer journeys (16 per cent), content creation (14 per cent), and customer support (14 per cent).

Despite these encouraging signs, a significant disconnect remains. Only six per cent of organisations in Asia report having GenAI solutions that deliver measurable ROI, a figure that is half the global average. This gap highlights a central challenge: while businesses recognise GenAI’s capabilities, they struggle to translate initial gains into sustained, quantifiable outcomes.

The foundation for GenAI success

A central theme in Adobe’s recommendations is the critical need for unified data. Fragmented data is one of the most significant barriers preventing organisations from achieving real-time personalisation and maximising GenAI’s effectiveness.

According to the report, 88 per cent of practitioners cite fragmented data as a key issue, while 42 per cent of senior executives acknowledge that disparate data siloes hinder AI’s full potential.

Also Read: From ADP to Bitcoin: How US economic indicators are shaping global financial landscapes

Privacy and security concerns compound these difficulties. With 43 per cent of executives identifying these concerns as top obstacles, many organisations hesitate to integrate customer data across functions. However, unifying data is not only about technological integration; it also requires addressing governance, compliance, and ethical considerations to build trust internally and with customers.

Recognising these challenges, 61 per cent of senior executives indicate that data integration and real-time insights will heavily influence their technology investment decisions over the next 12 to 24 months. Establishing a unified data foundation enables organisations to personalise customer experiences dynamically, optimise resource allocation, and ultimately derive measurable ROI from GenAI.

Adobe emphasises that effective GenAI adoption requires cross-functional collaboration. Ownership of the customer journey is often divided among marketing (33 per cent), customer success (17 per cent), customer experience (16 per cent), and IT (11 per cent). Without seamless coordination between these departments, GenAI initiatives risk becoming disjointed and inefficient.

By fostering collaboration, organisations can pool expertise, align objectives, and ensure that GenAI applications are integrated into broader business strategies. This cooperative approach is essential for addressing the complex, multi-faceted nature of GenAI projects, which often span data management, customer engagement, product development, and operational efficiency.

To bridge the gap between GenAI potential and measurable outcomes, Adobe recommends appointing a dedicated champion to oversee GenAI initiatives. This individual plays a pivotal role in uniting strategies, aligning cross-functional teams, and focusing on clear business objectives.

A GenAI champion provides leadership and accountability, ensuring that data unification, collaboration, and adoption strategies are executed cohesively. With centralised oversight, organisations can navigate the complexities of GenAI adoption more effectively, accelerating progress and mitigating the risk of stalled or fragmented initiatives.

Also Read: US-based RadNet acquires Singapore AI startup See-Mode to strengthen diagnostic capabilities

Adobe also advocates for early adoption of GenAI combined with a test-and-learn approach. Early adopters position themselves to gain first-mover advantages, refine their use cases through iterative learning, and build organisational expertise.

A test-and-learn mindset allows businesses to experiment with GenAI applications across various domains, evaluate outcomes, and adjust strategies accordingly. This agile approach not only minimises risk but also fosters a culture of continuous improvement, enabling organisations to adapt to evolving customer needs and market dynamics.

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Image Credit: Andrew Neel on Unsplash

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The artificial intelligence (AI) sector has surged into an era of unprecedented acceleration, marked by meteoric growth in usage and investment while grappling with staggering costs and intense international competition.

What initially emerged as scattered developments has morphed into a sophisticated, high-stakes ecosystem. Traditional monetisation strategies are being reinvented in real time, often at the expense of massive cash burn.

Layered on top of this is a growing geopolitical rivalry, particularly between the US and China, which is shaping the global AI landscape.

The speed of AI adoption and user engagement is now eclipsing the early internet boom, with machines advancing faster than human capabilities. This exponential growth is vividly reflected in skyrocketing capital expenditure (CapEx) trends that show no sign of plateauing.

Also Read: AI power shift: How geopolitics and innovation are rewriting global rules

Startups are fuelling the pace with aggressive product rollouts, capital raises, and innovation, while tech behemoths are reallocating their cash flows to artificial intelligence to maintain market dominance and ward off new entrants.

Capital and infrastructure surge powers AI boom

Massive user uptake: OpenAI’s ChatGPT exemplifies AI’s mainstream adoption, growing its weekly active users by over 200 per cent year-on-year to hit 350 million by December 2024. Since its launch, ChatGPT has seen an eightfold increase to 800 million users in just seventeen months.

Soaring CapEx among Big Tech: The so-called “Big Six” US tech firms (Apple, NVIDIA, Microsoft, Alphabet, Amazon (AWS), and Meta Platforms) pushed their collective CapEx up by more than 63 per cent year-on-year, totalling US$212 billion in 2024. This increase is largely driven by demand for AI model training and deployment infrastructure.

Data centres as AI factories: Data centre spending has surged to US$455 billion globally in 2024, with projections pointing to continued acceleration. These facilities are becoming “AI factories” as hyperscalers and AI-first companies invest billions to scale computational capacity.

Ecosystem expansion: The NVIDIA AI ecosystem has seen exponential growth: 6 million developers (up 2.4 times), 27,000 startups (up 3.9 times), and 4,000 GPU-enabled applications (up 2.4 times) by 2025.

Monetisation: A multi-pronged strategy

Consumer subscriptions lead the way: Flagship AI models such as ChatGPT, xAI’s Grok, Google’s Gemini, Anthropic’s Claude, and Perplexity are monetising primarily through subscription models for individual users.

API and generative search monetisation: Anthropic’s revenue soared more than 20 times to US$2 billion annually in eighteen months. Meanwhile, xAI’s generative search offerings are set to achieve significant revenue growth by 2025.

Enterprise-driven growth: Companies are embracing AI for top-line growth. Glean, which provides enterprise search and AI agents, grew its annual recurring revenue (ARR) more than 10 times to US$100 million within two years.

Integrated AI platforms: Incumbents are embedding AI across entire product suites. Microsoft’s AI division surpassed a US$13 billion annual revenue run rate in 2024, marking a 175 per cent increase. Its Copilot tool is being widely deployed across services. Meanwhile, TikTok has rolled out Symphony, a suite of AI-powered advertising tools.

Specialised AI software flourishes

Industry-specific AI applications are gaining traction:

Software engineering: Anysphere Cursor AI’s ARR surged from US$1 million to US$300 million in just over two years.

Legal services: Harvey hit US$75 million in ARR by April 2025.

Also Read: Southeast Asia steps up: Complexity, opportunity, and the post-China trade shift

Customer support: Decagon expanded its ARR tenfold in a single year, from US$1 million to US$10 million, reshaping customer service into AI management roles.

The cost of innovation: Burn rates and bottlenecks

Escalating expenses: Training frontier large language models (LLMs) is among the most capital-intensive ventures in history, with compute expenses running into the billions. OpenAI’s 2023 compute spend alone was estimated at US$5 billion.

Monetisation vs profitability: As inference costs per token decline, AI becomes more accessible. However, this brings uncertainty to monetisation models and casts doubt on long-term profitability for model providers.

High-burn dynamics: The prevailing equation in the AI world is “High Revenue + High Burn + High Valuation + High Investment”. Collectively, leading private AI model firms (OpenAI, Anthropic, Perplexity, and xAI) have raised approximately US$95 billion to date, against an estimated combined revenue of just US$11 billion annually as of May 2025.

Energy as a limiting factor: AI’s colossal energy demands are causing data centres to rival traditional heavy industries in consumption. The sector’s growth is increasingly constrained by energy availability, not data or algorithms, with grid strain becoming a critical bottleneck.

The geopolitical chessboard of AI

Open-source disruption: The proliferation of open-source AI is undermining proprietary monetisation strategies by enabling “frontier-level” innovation without billion-dollar budgets. This democratisation could commoditise certain capabilities, posing a threat to incumbents.

China’s rapid AI ascent: China is intensifying its AI efforts in strategically vital areas like battlefield logistics and autonomous systems. By Q2 2025, it had released three open-source LLMs and is closing the performance gap with US models at a remarkable pace, a stark contrast to its late adoption during the internet era.

Strategic tug-of-war: The US and China now view AI as both an economic engine and a geopolitical lever. American policymakers are tightening safeguards around advanced AI models, while China is focusing on original innovation, moving away from its earlier “freerider” approach.

Also Read: Southeast Asia’s AI divide: SleekFlow report warns of widening gap

As Microsoft Vice Chair Brad Smith warned, “this race between the US and China for international influence likely will be won by the fastest first mover.”

Outlook: Innovation unchained, but at a cost

The AI sector represents a collision of hypercapitalism, global ambition, and creative destruction. While consumers benefit from “better, faster, cheaper” solutions and developers gain access to advanced tools, the path to profitability remains fraught with complexity.

The genie is out of the bottle, and the global monetisation race is only just beginning.

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The image was generated using ChatGPT.

Source: “Trends-Artificial Intelligence” by BOND

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Netbank has concluded a Series B round led by Singapore-based Altara Ventures, betting that the next phase of Philippine fintech growth will be won not by the flashiest consumer app, but by the regulated banking plumbing underneath it.

The company did not disclose the size of the round. Existing backers BeeNext, Kaya Founders, January Capital, Oak Drive Ventures, and Boleh Ventures all participated again, a sign that investors are still willing to fund infrastructure plays in a market where compliance, bank integrations, and product rollouts remain painfully slow.

Netbank plans to use the new capital to deepen payments, lending, account, and card capabilities, while investing in automation, risk systems, and engineering.

Also Read: Security implications of embedded finance in non-financial platforms

The Philippines is becoming one of Southeast Asia’s more compelling proving grounds for embedded finance. Digital payments are rising fast, more services are moving into apps, and platforms from lenders to marketplaces increasingly want to offer financial products without becoming banks themselves. Netbank’s pitch is straightforward: let those businesses plug into regulated accounts, payments, cards, and lending through APIs, while Netbank handles the banking layer.

In plain English, it wants to be the bank in the background.

Why this round matters

The timing of the fundraise is notable. Across the region, fintech funding has become harder to secure, and investors have grown less patient with glossy growth stories unsupported by revenue. Netbank is leaning into the opposite message. It said revenue grew 88 per cent year on year in FY2025 and that it was profitable while expanding its accounts, payments and card-issuing products. That is a more credible story than the usual “land grab now, economics later” script.

Founder Gus Poston put it bluntly in the announcement, saying fintechs in the Philippines eventually “hit the same wall” when they need a bank that can move at startup speed. That line gets to the core of the opportunity. Building financial products in the country is not simply a design or distribution challenge; it is an infrastructure problem. Licensing, settlement, compliance and integrations still create friction that younger companies struggle to absorb.

Netbank is trying to monetise that bottleneck.

The Philippines is fertile ground for embedded banking

Embedded banking in the Philippines is growing as several forces converge.

First, digital payments are now mainstream rather than experimental. Bangko Sentral ng Pilipinas (central bank) data shows digital payments accounted for 52.8 per cent of retail payment transactions by volume in 2023, up sharply from 42.1 per cent in 2022 and just 20.1 per cent in 2018. Once consumers and businesses are already paying digitally, it becomes much easier to layer on accounts, credit, cards, payroll tools, and disbursements inside the same platforms.

Second, the country still has a deep access gap. Formal account ownership has improved, but millions of Filipinos and small businesses remain underserved by traditional banks, especially outside major urban centres. Embedded finance works well in markets like this because it delivers financial services through apps people already use, rather than forcing them to start at a bank branch.

Third, small businesses need capital and better collection tools. The Philippines has a large MSME base, yet access to working capital remains uneven. That creates room for platforms to embed lending, merchant settlement, and cash management services directly into the software used by sellers, gig workers, and service providers.

Also Read: Why embedded finance is critical to Southeast Asia’s digital future

Fourth, regulation has become more enabling. The central bank has aggressively pushed digitisation, while open finance and instant payment rails are making it easier for licensed players to build new products without recreating the stack each time.

Who Netbank is targeting

Netbank sells to businesses that want to embed financial services into their own products. That includes fintech startups, lending platforms, remittance operators, payroll and HR software providers, marketplaces, vertical SaaS companies, and other digital platforms that need regulated accounts, real-time disbursements, collections, cards or credit rails without building bank partnerships from scratch.

Its value proposition is strongest for companies that are growing quickly but do not want the pain of stitching together one provider for payments, another for KYC, another for cards and still another for lending infrastructure. A licensed bank with modular APIs can reduce that complexity.

Netbank said its active partner base expanded substantially in FY2025, but did not disclose the exact number of companies it has partnered with to date. That omission is frustrating, though not unusual for infrastructure startups that prefer to talk in terms of volume and revenue rather than customer counts.

How Netbank makes money

Like other banking-as-a-service and embedded finance providers, Netbank’s revenue model is likely a mix of recurring platform income and transaction-based fees.

That typically includes:

• fees on payment processing, disbursements and collections;
• account-related charges for white-labelled banking products;
• card economics such as interchange and programme fees;
• lending income through origination, servicing or balance-sheet participation; and
• custom integration or enterprise service fees for larger partners.

Because Netbank operates on a banking licence, it can do more than a pure software middleware player. That should give it more ways to monetise each partner relationship, especially as partners expand from payments into cards and credit.

The competitive field is getting busier

Netbank may be unusual in positioning itself as an embedded finance platform running on a banking licence, but it is not building in an empty lane.

In the Philippines, Brankas is one of the best-known names in open finance and API-led banking infrastructure. UBX, the fintech arm of UnionBank, has also built rails for digital financial services and ecosystem partnerships. Large digital banks and financial super-apps, such as Maya, are increasingly building more extensible infrastructure, even if their models differ from Netbank’s.

On the financing side, players including BillEase, UnaCash, Cashalo, and Atome have helped normalise embedded credit inside merchant and checkout flows. They are not direct like-for-like competitors to Netbank’s full-stack banking infrastructure model, but they do shape customer expectations around instant, in-app finance.

That is the broader point: embedded finance in the Philippines is no longer a niche concept. Consumers already encounter it at checkout, in wallets, in salary-linked products and in merchant apps. The next battle is over who supplies the rails.

Where the sector is headed

The space is moving away from simple payment integrations and towards full-stack embedded banking. That means more demand for real-time collections and disbursements, embedded cards, sector-specific credit, cross-border payment rails, and compliance automation that can survive closer regulatory scrutiny.

Also Read: Embedded finance will drive financial growth and sustainability in India

It also means the winners may look less like pure software startups and more like regulated infrastructure businesses with defensible economics.
Altara’s Dave Ng said a regional gap remains in “dependable financial infrastructure”. That is the investment thesis in one sentence. Southeast Asia does not lack fintech ideas; it lacks enough reliable back-end systems to support them at scale.

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