Prelude

The global economic landscape is currently navigating a period of profound structural realignment, characterised by the aggressive internationalisation of Chinese small and medium-sized enterprises (SMEs). This movement, colloquially termed “ChuHai” (出海) or “Going to Sea,” has transitioned from a tactical response to domestic market saturation into a foundational strategic imperative for the survival and long-term viability of the Chinese private sector.

As we approach the late 2020s, the ChuHai phenomenon is no longer merely about exporting low-cost commodities; it represents a sophisticated evolution toward brand excellence, localised operational capacity, and the deployment of advanced technological ecosystems across emerging and developed markets alike.

This report provides an exhaustive analysis of the drivers, magnitude, and regional complexities of this trend, while identifying high-potential market opportunities for new ventures seeking to support this massive wave of globalisation.

The structural drivers of overseas expansion: The involution crisis

At the core of the current surge in Chinese SME internationalisation is the phenomenon of “involution” (内卷, nei juan). This term describes a state of hyper-competition where excessive effort and resources are expended for diminishing returns, often leading to a race-to-the-bottom in pricing and profit margins. The structural roots of this crisis are multi-dimensional, involving fiscal pressures, demographic shifts, and the collapse of the traditional growth engines that fueled China’s rise over the previous three decades.

The exhaustion of the real estate sector, which historically accounted for 20 per cent to 30 per cent of China’s GDP and 27 per cent of all bank loans, has created a massive vacuum in the domestic economy. The bursting of property bubbles has not only eroded household wealth and suppressed consumer demand but has also stripped local governments of their primary source of fiscal revenue: land financing.

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By late 2025, local government debt had escalated to an estimated US$18.9 trillion, forcing these entities to pivot toward manufacturing and high-tech sectors as alternative drivers of GDP growth. This pivot has resulted in a deluge of government subsidies, tax incentives, and low-interest loans directed toward state-favoured industries, including electric vehicles (EVs), solar equipment, and semiconductors.

The unintended consequence of this state-led investment has been a chronic oversupply and massive overcapacity. When domestic demand failed to keep pace with the state-subsidised production surge, firms were forced into brutal price wars to survive. In the EV sector, for example, dominant players have used financial leverage to pursue predatory pricing strategies intended to eliminate smaller competitors.

By late 2025, industrial profits in several manufacturing segments saw year-on-year declines as sharp as 13.1 per cent, effectively erasing previous growth and creating a “growth without profits” trap. For many SMEs, the domestic market has become a zero-sum game, making international expansion the only viable pathway for maintaining operational solvency and achieving sustainable margins.

Market size and profiling: The 2026-2028 surge

The magnitude of the Chinese SME overseas surge is reflected in the record-breaking metrics of outward direct investment (ODI) and the volume of private enterprises engaging in global trade. By the end of 2025, the number of private Chinese enterprises with actual import and export activity reached approximately 613,000, accounting for the vast majority of the country’s 700,000 active trade entities.

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For the 2026-2028 cycle, the “ChuHai” market is expected to expand by approximately 175,000 SMEs annually. This “New Wave” is characterised by a transition from “Made in China” (volume export) to “Operated by China” (localised presence).

SME internationalisation profile (2026-2028)

Strategic expansion priorities

Chinese SMEs are no longer pursuing simple volume; their expansion is now “capability-led,” focusing on the following strategic pillars:

• Market expansion: Escaping domestic deflation and price wars to capture margins that are often double what is achievable domestically.
• Technology licensing and IP: Shifting toward licensing proprietary technology to local partners to overcome regulatory barriers and secure data exclusivity in sensitive sectors like biomedicine and AI.
• Global R&D and talent: Establishing overseas innovation centres to access bilingual leadership and local technical talent, bridging the cultural gap between HQ and the market.
• Manufacturing outsourcing and nearshoring: Relocating production capacity to regions like Mexico (nearshoring) or Vietnam to bypass US and EU tariffs and shorten delivery cycles from weeks to days.

The role of the accelerator state: Policy support and institutional frameworks

The internationalisation of Chinese SMEs is a core component of the national industrial strategy. The government has evolved into an “accelerator state,” moving toward a multi-layered system designed to fast-track the growth of high-tech SMEs in strategic sectors.

The Little Giants initiative

The “Little Giants” program focuses on “specialised, refined, special, and new” SMEs within key industrial chains. For the 2024-2026 period, the program prioritises the “six foundations”: core basic parts, core basic components, key software, advanced basic processes, key basic materials, and industrial technology foundations.

Capital support is significant, with guidelines aiming to inject up to CNY 6 million (approximately US$830,000) per firm over a three-year cycle. By late 2025, the program had cultivated over 13,000 national-level Little Giants, with cities like Shenzhen housing over 1,000 such firms.

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The 15th five-year plan and the 2030 horizon

The strategic roadmap for the next phase (2026-2030) outlines a shift from growth driven by scale to growth driven by quality. Key objectives include:

• Technological self-reliance: Accelerating breakthroughs in brain-computer interfaces, quantum technology, and semiconductor supply chains.
• Digital economy expansion: Increasing the share of core digital industries to 12.5 per cent of overall GDP.
• Support for global scale: Explicitly encouraging internet platforms, AI companies, and professional services to expand and form partnerships overseas.

Geographic realignment: Emerging corridors and the global South

As regulatory scrutiny intensifies in the US and EU, Chinese SMEs are diversifying toward regions with lower regulatory friction.

ASEAN: The hub-and-spoke model

ASEAN is the critical region for restructuring Chinese supply chains, with FDI inflows reaching US$226 billion in 2024. For Chinese SMEs, ASEAN offers a mobile-first consumer base aligned with Chinese digital strengths. Vietnam, Malaysia, Indonesia, and Thailand have become central hubs for manufacturing and customer service.

The Middle East: The Gulf blue ocean

The Middle East—particularly the GCC states—is a priority destination for Chinese capital. In 2024, the region received US$39 billion in BRI investments, a 102 per cent increase YoY. Saudi Arabia alone drew US$19 billion. Chinese firms view the Gulf as a “blue ocean” due to high policy flexibility and security.

Latin America: Mexico and the nearshoring shift

In Latin America, the focus is shifting toward Mexico as a gateway to the North American market. Chinese brands now account for 57 per cent of cars imported into Mexico as of early 2025. The “Trump Corollary” to the Monroe Doctrine creates headwinds, but the USMCA framework provides a significant duty-free advantage for Chinese SMEs that can successfully localise manufacturing in the region.

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The technological architecture of ChuHai: AI and agentic trade

The year 2025 has been identified as China’s “AI Agent Year,” marking the deployment of autonomous systems to manage global operations.

Agentic workflows in cross-border operations

Next-generation AI agents are being integrated into platforms like WeChat (OpenClaw framework) to solve operational challenges. SMEs use “AI Agent Orchestration” to automate end-to-end marketing, content generation, and performance loops. In logistics, “Control Tower Agents” optimise delivery routes and reorder workflows, reducing routine task handling by 60-80 per cent.

The service ecosystem opportunity: Identifying business niches

The Chinese SME expansion has outpaced its supporting service ecosystem, creating massive gaps in talent, compliance, and localisation.

The talent gap: A staggering bottleneck

The number one bottleneck for Chinese companies going global is talent acquisition. In 2025, there was a talent gap of 4 million people in the cross-border e-commerce sector alone.

• Startup opportunity: AI-powered executive search for “bridge leaders” and Employer of Record (EOR) services to manage regional talent networks.

Compliance and regulatory readiness (C-as-a-service)

Compliance requirements for outbound firms surged by 250 per cent in 2025.

• Startup opportunity: Global payroll, HR compliance SaaS, and Data Sovereignty solutions to manage the web of local tax and privacy laws.

Localisation and ecosystem integration

Success is tied to the ability to “go in”—truly entering the local culture—rather than just “going out”.

• Startup opportunity: Cross-border traffic marketing, AI-native SEO (GEO), and market entry incubators for the Global South.

Also Read: The scale layer nobody budgeted for: How AI agents unlock growth for Asian businesses

Strategic conclusions and recommendations

The expansion of Chinese SMEs overseas is a structural trend that will define global commerce through 2030. Driven by the exhaustion of domestic profits and supported by a multi-billion-dollar state accelerator, this wave is moving toward higher-value sectors and deeper regional integration.

For new ventures, the most promising path is to become a “strategic enabler” for this outbound surge. The transition from “Made in China” to “Brands from China” represents the next great shift in the global economy. Those who can provide the cultural, regulatory, and technological bridges will be positioned at the heart of the world’s most dynamic trade corridor. The path forward lies in combining AI-native “intelligence” with the “empathy” required for deep cultural localisation.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

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This is about freight. Specifically, why freight, logistics, and supply chain, an industry so gloriously unglamorous that people fall asleep mid-sentence just describing it, is turning into one of the most interesting places to build a company in Asia right now.

I know. Bear with me.

Few people want to work in logistics — that’s the point

When I tell people I run a logistics company, one of two things happens. Either their eyes glaze over, or they say something polite and immediately change the subject.

Logistics has an image problem. It’s not the industry you dream about at university. It doesn’t attract the same talent pipelines, the same VC attention, or the same media coverage as the sexier corners of tech. Nobody is writing breathless Substack posts about customs clearance and freight.

And yet, quietly, something is happening.

The global 4PL market is projected to grow at 8.1 per cent CAGR from 2025 to 2032, according to research commissioned by Wayfindr citing Market. In e-commerce specifically, that growth rate accelerates to 12 per cent CAGR over the same period, driven by surging cross-border trade, supply chain complexity, and the relentless expansion of direct-to-consumer brands into new markets.

E-commerce is eating retail across every market. Manufacturing is rapidly diversifying across Southeast Asia as brands shift supply chains out of China. And the technology layer that connects all of this, the visibility, the coordination, the data, has barely been built.

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The problem is not shipping, it is complexity

Here is what most people get wrong about logistics as a startup opportunity. They think the opportunity is in moving things faster. A better courier. A smarter warehouse. A cheaper freight rate.

That is not the problem.

The real problem is that scaling an e-commerce brand across multiple countries, with manufacturing in Vietnam or China, selling into the US, UK, and Europe simultaneously, involves dozens of moving parts, dozens of providers, and nobody whose job it is to be accountable for all of it at once.

A brand owner running a US$20 million e-commerce business should be thinking about product, marketing, and growth. Instead, they spend half their week chasing updates from a freight forwarder here, arguing with a warehouse over there about a stock discrepancy, and trying to figure out why their landed costs keep changing.

That is not a shipping problem. That is an orchestration problem. And orchestration is exactly where tech has enormous room to run.

Vietnam is not a trend — it is a structural shift

I spend a lot of time in Southeast Asia. A big segment of our team operates out of Vietnam, and what we see on the ground is not a passing wave. It is a genuine realignment of global manufacturing.

Brands that were 100 per cent China-reliant five years ago are now actively splitting production. Vietnam, Indonesia, Taiwan, and Thailand are absorbing that shift under the China+ strategy. And with it comes a whole new layer of complexity: new suppliers, new compliance requirements, new last-mile challenges, and new currency risk.

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The market data reflects this reality. APAC is the fastest-growing region for 4PL adoption globally, projected at 10.8 per cent CAGR through 2032, growing from a US$19.7 billion market today to US$44.7 billion by 2032. That growth is being driven directly by the manufacturing shift, the rise of cross-border e-commerce, and the urgent need for smarter supply chain infrastructure across the region.

For the brands navigating this, the operational burden has never been higher. For the companies building technology and services to help them do it, the opportunity has never been larger.

The startup opportunity in Southeast Asia’s logistics sector is not just local. It is the infrastructure layer for global commerce.

The boring industries have the best defensibility

Here is something I learned coming from the oil and gas world before logistics: the industries that look boring from the outside are often the ones with the deepest moats.

An operator who genuinely understands how freight consolidation works out of Guangzhou, how Vietnamese customs changes every year, and how to design a landed-cost model that holds across six destination markets, that knowledge does not transfer easily. The complexity is the barrier. And the complexity, at the moment, is only increasing.

Tariff changes. Carbon reporting requirements. Cross-border regulatory divergence. Every one of these adds another layer that brands need help navigating, and another reason to build toward a model where one intelligent, tech-enabled partner is accountable for all of it.

This is what the fourth-party logistics model, 4PL, exists to do. And it is a model that is still, genuinely, in its infancy in Asia.

What is a 4PL?

A fourth-party logistics provider, or 4PL, is an independent, non-asset-owning partner that designs, manages, and optimises your entire supply chain, coordinating freight forwarders, warehouses, carriers, and technology under one roof. Think of it less like a supplier and more like a control tower: one point of accountability for everything that moves.

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The unsexy bet is often the right one

I started building in logistics because I saw a problem I could not stop thinking about. Not because it was fashionable. Not because investors were excited. Frankly, most of them were not.

We bootstrapped to eight figures without a cent of external funding, which I mention not to brag but to make a point: the fundamentals of the problem were strong enough that we did not need anyone to believe in the vision before the market proved it. The demand was real. The inefficiency was real. The gap was real.

The next decade of e-commerce growth in Asia is going to be built on infrastructure. Not just digital infrastructure, but the physical and operational infrastructure that moves real products from real factories to real customers. The companies that build the intelligence layer on top of that, the platforms, the visibility tools, the coordination systems, those are the companies that will be quietly, unglamorously, extraordinarily valuable.

So yes. Freight. Supply chain. Logistics.

I promise it’s more interesting than it sounds.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The post Why the most boring industry in the world is quietly becoming a startup goldmine appeared first on e27.

I know what you’re thinking (pun intended). But this is not a sensational fantasy about mind reading. It is an extrapolation from real advances in AI, brain-computer interfaces (BCIs), and neuroscience. As systems for decoding neural signals and translating thought-related activity into digital output continue to improve, the question is no longer just what they can do on their own, but whether they could one day be networked, and to what extent. Although BCIs are no longer a novel concept, if such devices could communicate directly with one another, they might give rise to technological telepathy.

From private thought to usable input

Thoughts have historically remained private by default, becoming shareable only when forced through speech, writing, gesture, or code, each of which introduces delay, tension, and translation between intention and expression. Technological telepathy becomes consequential not because machines can literally read minds in a science-fiction sense, but because computing is progressively collapsing that gap, as BCIs, silent-speech systems, neural decoding models, and generative AI converge into a communications stack in which cognition itself becomes a usable input, suggesting that future networks may connect minds rather than merely devices or identities.

A longer lineage of brain-machine translation

This trajectory does not originate with ATR, AlterEgo, Neuralink, or the current “AI summer,” but extends through a longer history of rendering the brain legible to machines, beginning with Hans Berger’s EEG and its demonstration of non-invasive neural capture, continuing through José Delgado’s stimulation experiments, Alvin Lucier’s ”Music for Solo Performer” and its use of EEG for artistic control, Eberhard Fetz’s work on learned modulation of neural firing, and Jacques Vidal’s articulation of “brain-computer communication,” later made publicly tangible through BrainGate’s cursor control for paralysed patients and Kevin Warwick’s experiments in technological telepathy, all of which situate this internet of minds as a continuation rather than a rupture.

Institutional drivers and military interest

This history cuts across neuroscience, engineering, military funding, performance art, and public spectacle, with DARPA embedded as part of the field’s institutional structure, particularly through programs such as N3 that target high-performance neural interfaces for human-machine teaming, active cyber defence systems, and control of unmanned aerial vehicles, although no credible public evidence supports operational BCI-to-BCI communication in military or covert use.

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Science fiction as conceptual groundwork

Science fiction anticipated the conceptual and social implications well before technical feasibility, as seen in Alfred Bester’s “The Demolished Man“ and its treatment of telepathy and social order, William Gibson’s “Neuromancer“ and “Johnny Mnemonic“ and their linking of neural systems to networked computation, Iain M. Banks’s neural lace, Ramez Naam’s infrastructural treatment of networked cognition, and Isaac Asimov’s “Foundation,“ alongside concepts such as hive mind theory and consciousness field theory, which framed expectations even as technological telepathy itself remains grounded in engineering rather than speculative human abilities.

What technological telepathy actually is

In practical terms, technological telepathy does not involve full extraction of continuous private thought, but instead consists of narrower capabilities such as decoding constrained visual categories from brain activity during sleep, reconstructing partial features of perceived or imagined images, or inferring silently articulated words from neuromuscular signals in the face and jaw, which are distinct but collectively indicate that communication technologies are moving upstream toward earlier stages of cognition.

In practical terms, current and near-term systems rely on specific device classes rather than abstract “mind reading,” including implanted electrode arrays that record neural firing directly from the cortex, non-invasive headsets based on EEG or functional imaging that capture aggregate brain activity, endovascular interfaces that access signals via blood vessels, and wearable EMG sensors placed on the face or jaw to detect subvocal speech, all of which produce partial, task-specific signals that must be decoded and interpreted through software, meaning that what is transmitted is not raw thought but a constrained, device-mediated representation of selected aspects of cognition.

The layered communication stack

A clearer understanding emerges when treated as a layered system, beginning with capture through electrodes, imaging systems, or wearable sensors that detect neural or neuromuscular activity, followed by decoding via machine-learning models that map signals to probable words, intentions, percepts, or categories, then mediation through software that filters noise, ranks interpretations, predicts continuations, corrects errors, and structures ambiguous biological signals into coherent output, and finally transmission to devices, other individuals, or networks, with AI functioning as the intermediary that translates between biological activity and digital meaning rather than enabling direct thought transfer.

From data to the “internet of minds”

Within this architecture, cognition-related data becomes processable in ways analogous to other network data while remaining qualitatively closer to thought itself, introducing the possibility that privacy breaches occur prior to completed expression, and implying that the dominant model will resemble cognitively mediated client-server communication rather than direct peer-to-peer telepathy.

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Philosophical constraints on “pure thought”

Philosophical objections of Neuralink-like research, such as Slavoj Žižek’s 2020 talk at the University of Winnipeg, emphasise that conceptual thought does not exist independently of language, challenging the notion that “pure thought” can be transmitted without distortion and reframing linguistic imperfection as intrinsic to meaning rather than an obstacle to be eliminated.

Technical limits and partial decoding

Technical constraints remain substantial, particularly in the form of invasiveness, as high-performance BCIs often depend on implants placed in or near the brain, introducing surgical risk, long-term maintenance, and questions of removal and bodily autonomy, while less invasive approaches such as wearables or endovascular interfaces shift these tradeoffs without removing them, as illustrated by ATR and Yukiyasu Kamitani’s lab, whose dream decoding studies demonstrated category-level prediction of dream content under tightly constrained conditions rather than full reconstruction, thereby establishing partial permeability of internally generated experience without generalisability.

Silent speech and the boundary of intent

Alternative approaches, such as AlterEgo, focus on silent speech, relying on intentional subvocalisation and neuromuscular detection to create a clearer boundary between private thought and transmitted output, although current limitations in surface EMG prevent reliable decoding of inner-speech phonetic content, reinforcing that existing systems detect controlled signals rather than unrestricted cognition.

The fragility of intentionality boundaries

This boundary of intent, while conceptually important, remains technically and institutionally fragile, as systems may expand the definition of “intended” signals through software updates, model retraining, or error correction, and as movement toward decoding imagery, semantic content, and prelinguistic intention further complicates distinctions between thinking, rehearsing, and transmitting, with proposed safeguards such as learned cognitive protocols or mental “keys” likely to erode under pressures for efficiency and usability.

From research frontier to platform economy

The transition from research to commercialisation, evident in companies such as Neuralink, Synchron, and Paradromics, reframes neurotechnology as infrastructure rather than experiment, introducing business models that range from high-cost clinical hardware reimbursed through healthcare systems to platform-based software and institutional deployment in workplaces, defence settings, or insurer-managed care, and elevating neural data as a potentially valuable resource due to its proximity to intention before action, preference before declaration, and friction before expression.

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Expression as a hybrid artifact

In this context, expression becomes a joint product, as systems infer, correct, rank, and autocomplete outputs derived from incomplete signals, producing hybrid artefacts that blur the boundary between user intention and machine contribution, thereby shifting the problem from privacy alone to questions of authorship and authenticity, since output may already reflect negotiation between human cognition and computational prediction.

Why consent is insufficient

Consent, traditionally understood as sufficient ethical grounding, becomes inadequate when users do not stand outside the systems shaping their expression, requiring structural governance mechanisms such as purpose limitation, auditable mediation, rights of refusal, prohibitions on employer coercion, protected clinical boundaries, and legal remedies when machine output is misattributed to the user as fully self-authored.

Feedback loops and cognitive adaptation

Feedback dynamics further complicate the system, as users adapt to decoder behaviour, anticipate system completions, and potentially reshape their own cognitive patterns to improve legibility and control, creating a feedback loop in which thought is partially oriented toward machine interpretability and generating ambiguity in responsibility when outputs reflect inferred rather than explicitly intended meaning.

Assistive promise and differential cognitive citizenship

While assistive applications for paralysis, severe motor impairment, or speech loss remain one of the strongest justifications, variability in neural and neuromuscular signals introduces differential cognitive citizenship, in which some individuals are more easily legible to systems than others due to anatomy, fatigue, stress, medication, injury, learning history, or neurotype, producing structured inequalities in performance, correction burden, and access.

Regulation, geography, and legibility inequality

These inequalities intersect with broader regulatory and geopolitical conditions, as jurisdictions that prioritise speed, scale, or strategic advantage may normalise less reliable systems more quickly, while Chile’s neurorights turn and the OECD’s neurotechnology governance work represent efforts to establish rights-based and standards-based constraints before large-scale commercialisation hardens, highlighting that cognitive interfaces will be shaped by states, healthcare systems, defence institutions, and major technology firms with divergent regulatory approaches.

Ownership, control, and contested infrastructure

Cognitive infrastructure is therefore unlikely to be uniformly owned, with centralisation more likely in hardware, clinical deployment, and large-scale inference systems, while mediation layers, user-facing software, and potentially open models remain more contestable, shifting the central political question from ownership of discrete thought-data to governance of the channel through which thought becomes public, legible, and actionable.

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Conditions for legitimate development

Legitimate development would require constrained deployment, local processing by default where feasible, strict separation between therapeutic and productivity uses, independent auditing of intent-detection and mediation systems, meaningful user oversight and contestability, and enforceable rights to refuse cognitive monitoring without loss of work, care, insurance, or civic participation, recognising that technological telepathy simultaneously compresses the distance between thought and communication while inserting additional computational mediation between them.

Near-term reality: low-bandwidth cognition

In near-term scenarios, the most achievable outputs remain limited to affective state, emotional valence, stress, calm, urgency, attentional load, and simple assent or refusal rather than full semantic language, although even these low-bandwidth signals may carry operational value in domains such as military coordination, justice, or entertainment.

Conclusion: authorship under mediation

The progression from networks connecting machines to those connecting identities suggests that an internet of minds would connect cognition itself to computation at unprecedented proximity, leaving unresolved the central question of whether thought, once mediated, inferred, and transmitted through such systems, can remain meaningfully one’s own.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The post Technological telepathy: Is an ”internet of minds” possible? appeared first on e27.

Most discussions about cyber insurance in industrial sectors start from the wrong assumption. They treat insurance as a recovery tool that will somehow make a severe OT incident manageable after the fact. That is too comforting and too shallow. OT environments are not ordinary digital estates. Many security guides stress that these systems carry unique performance, reliability, and safety requirements, and that logic executing in OT has a direct effect on the physical world, including potential harm to people, the environment, equipment, and production.

That is why cyber insurance will not save OT in the way some boards hope it might. Any basic guide to cyber insurance describes cover mainly in terms of losses tied to IT systems and networks, along with incident management support. Put plainly, a policy may help pay for response, legal support, forensics, and parts of business interruption. It does not restore process integrity, rebuild operational judgement, or make a compromised plant safe to trust again.

OT is exactly where the limits show up

The limits of insurance become sharper in industrial settings because the real cost of failure is often operational, not merely financial. Unexpected outages in industrial processes are unacceptable, that outages often need to be planned days or weeks in advance, and that high availability requires exhaustive pre deployment testing.OT components often remain in service for 10 to 15 years, sometimes longer, and that change management is more demanding because software and firmware updates can require careful assessment and revalidation.

The insurance market itself has recognised that OT is not yet a fully mature underwriting domain. There is still a comparative lack of understanding and awareness of cyber physical risk, even as the potential for threats to bridge IT and OT is becoming more apparent. It means buyers should not assume the policy market has already solved how to price or absorb the full reality of industrial cyber exposure.

Where does insurance actually matter

It matters as an incentive mechanism.

Cyber insurance should not be viewed as a substitute for strong internal defences, but rather as a means to encourage better risk management practices. Insurance can support cyber risk management by improving quantification, providing access to expertise and crisis services, and encouraging risk reduction through premium pricing. This is the strategist’s lens that matters more. Insurance is most valuable when it changes organisational behaviour before the incident, not when it simply finances some of the damage afterwards.

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That behavioural effect is already visible in underwriting logic. Coalition’s published guidance says insurers typically look for controls such as multi-factor authentication, training, tested backups, identity access management, and data classification before agreeing coverage, and that stronger controls can help firms secure more favourable rates. The market is large enough to influence buyer behaviour, and selective enough to shape which controls become non-negotiable.

The underwriting conversation should be different

The problem is that too many cyber insurance conversations still start with general IT hygiene and stop there. For industrial operators, that is not enough. The more serious opportunity is to use underwriting as a forcing function for a narrower set of OT relevant controls that genuinely reduce consequence.

A complete and accurate asset inventory is critical for managing OT risk, and that inventory data should include vendors, model numbers, firmware, operating systems, and software versions so vulnerabilities can be identified and tracked. It is also explicit that network segmentation and isolation help enforce security policies and control access to sensitive components, and that remote access should be provided only when justified, limited to business need, and supported by stronger safeguards. Tested backups are described as critical to recovery, with verification for reliability and integrity where technically possible. These are not theoretical controls. They are the foundations of whether an industrial site can contain, understand, and recover from a cyber event.

This is where insurance can become useful as a behavioural lever. If insurers and brokers start asking tougher OT questions around definitive asset inventory, segmented network zones, controlled vendor access, restoration testing, and evidence of recovery readiness, they will do more than screen risk. They will change internal priorities. Teams that struggle to win budget for resilience work often find that the conversation changes once underwriting, renewal, deductibles, or coverage conditions enter the room. That is not because insurance is replacing the engineering discipline. It is because insurance creates a commercial consequence for postponing it.

The market can also influence procurement

One of the most underused levers in OT security is procurement pressure. That is where cyber insurance could become more strategically useful over the next few years.

Operators should prioritise products and manufacturers that follow secure by design principles, and highlight issues such as logging, authentication, data protection, secure defaults, and established vulnerability management processes. That matters because insurers cannot underwrite away poor product design, but they can make weak procurement choices more visible and more expensive.

Also Read: Thailand’s cybersecurity boom has a weak core

A strategist should see the implications immediately. If policy terms, engineering standards, and procurement expectations all start pointing in the same direction, the market begins to reward firms that buy more defensible systems in the first place. That is far more valuable than arguing about claims after a major event. It shifts the conversation from “will this be covered” to “should we be accepting this exposure at all”.

What measurable risk reduction is

The weakness in many cyber insurance discussions is that they stop at broad hygiene language. Boards are told to improve resilience, but not how to tell whether risk is genuinely moving. 

In practice, a measurable reduction in OT should look less like policy paperwork and more like observable proof. Can the operator show a current inventory of critical OT assets and software versions? Can it demonstrate that high consequence zones are segmented and that permitted flows are understood? Can it prove that remote access is limited, approved, and capable of being disconnected quickly? Can it show that backups, images, and configuration states are actually restorable? Those are the sorts of measures that shorten recovery, reduce uncertainty, and make underwriting more meaningful. 

The strategist’s conclusion

Cyber insurance will not rescue OT from poor architecture, weak product choices, or years of deferred resilience work. The market itself has acknowledged limits around systemic events and around understanding cyber-physical exposure. But that does not make insurance irrelevant. It makes its real value clearer.

Its best role is to alter incentives.

It can force boards to treat OT risk as financially visible. It can force security teams to translate technical gaps into underwriting consequences. It can force operations leaders to evidence controls that otherwise remain assumed rather than proven. It can force procurement teams to take secure-by-design claims more seriously. Used that way, insurance becomes less a comfort blanket and more a discipline mechanism.

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Editor’s note: e27 aims to foster thought leadership by publishing views from the community. You can also share your perspective by submitting an article, video, podcast, or infographic.

The post Cyber insurance won’t save OT, but it can change behaviour appeared first on e27.

The global humanoid robotics industry is fragmenting into two distinct ecosystems pursuing fundamentally different scaling strategies: China’s deployment-led approach prioritising rapid manufacturing scale and real-world learning, versus North America and Europe’s AI-first methodology betting that foundation models and vision-language systems will determine long-term competitive advantage.

This strategic bifurcation carries profound implications for technology trajectories, supply chain configurations, and ultimately, which regions capture value as the market matures.

Also Read: The humanoid robot economy is no longer science fiction

According to “Humanoid robots 2026” by Roland Berger, these contrasting approaches reflect different resource endowments, institutional capabilities, and strategic philosophies about how complex technologies scale. Neither path guarantees success; each offers distinct advantages and risks. Still, the divergence increasingly shapes ecosystem development, reducing cross-regional interoperability and creating parallel technology stacks unlikely to converge.

The scale differential is striking: China’s estimated 15,000 units produced in 2025 exceed North America’s output by a factor of 30 and dwarf EMEA’s production by more than 150 times. Yet North American companies command nearly equivalent total funding (US$3.8 billion versus US$4.1 billion), reflecting higher capital intensity per company and a greater emphasis on software development, which requires substantial AI infrastructure investment rather than manufacturing capacity.

China’s manufacturing flywheel: scale drives data, data improves AI, AI enables deployment

China’s strategic approach prioritises getting robots into real-world environments quickly, accepting initially limited capabilities in exchange for operational data and manufacturing experience. This deployment-first methodology draws on the nation’s established strengths in hardware manufacturing, rapid iteration cycles, and vertically integrated supply chains that can absorb early-stage demand volatility.

The 39 identified Chinese startup OEMs documented by Roland Berger pursue targeted applications in entertainment, logistics, and basic manufacturing — environments with structured workflows, repetitive tasks, and controlled conditions where current AI capabilities prove sufficient. Rather than waiting for human-level general intelligence, Chinese developers optimise for specific contexts, accumulating deployment experience and operational data whilst building manufacturing infrastructure.

This approach constructs a powerful flywheel: manufacturing scale reduces unit costs, making robots accessible to more deployment environments; deployments generate operational data that improve AI capabilities; improved AI enables robots to handle more complex tasks, expanding the addressable market; market expansion drives additional manufacturing scale. If this flywheel accelerates successfully, China could establish compounding advantages that are difficult for rivals to overcome, despite superior foundational AI research capabilities concentrated in Western institutions.

The industrial policy dimension reinforces private sector initiatives. China’s “Robot+” strategy, articulated in the 14th Five-Year Plan for Robotics Industry Development, establishes explicit targets for humanoid robot development with governmental support spanning R&D funding, pilot deployment programmes, and procurement preferences. Provincial and municipal governments offer additional incentives (subsidies, tax benefits, and land allocations), creating supportive ecosystem conditions for rapid scaling.

Supply chain integration provides additional advantages. China’s electronics and mechanical manufacturing ecosystems supply components for consumer electronics, automotive, and industrial automation globally. This established base enables humanoid developers to source actuators, sensors, structural components, and compute modules domestically with shorter lead times and tighter integration than developers dependent on cross-border supply chains.

Western AI-first strategy: software advantages create defensible moats

North American and European ecosystems pursue fundamentally different competitive positioning, treating humanoid robotics as an AI problem requiring cutting-edge machine learning capabilities rather than primarily a manufacturing challenge. This software-first approach bets that long-term competitive advantage will emerge from foundation models, vision-language systems, and proprietary training datasets, enabling robust autonomy in unstructured environments, capabilities that manufacturing scale alone cannot replicate.

Also Read: The real battle in humanoid robotics is about data, not hardware

The capital intensity reflects this philosophy. North American companies typically allocate more funding per startup than their Chinese counterparts, consistent with their need for substantial computational resources, AI talent, and extended R&D timescales. Leading Western humanoid developers increasingly position themselves as AI companies that happen to build robots, rather than robotics companies incorporating AI, a subtle but significant strategic distinction.

Western developers emphasise generalisation, creating robots capable of learning new tasks with minimal task-specific programming, over optimisation for predefined workflows. This ambition requires more sophisticated AI architectures, larger training datasets, and longer development timescales before initial deployment. The approach reflects confidence that superior AI capabilities will ultimately overcome China’s manufacturing scale advantages once Western robots demonstrate human-comparable adaptability.

Academic and corporate AI research ecosystems in North America and Europe provide a competitive advantage in foundational capabilities. Universities and research institutions in these regions publish disproportionately in top-tier AI conferences and journals; technology companies operate cutting-edge AI infrastructure; and talent concentrations in hubs like the San Francisco Bay Area, Seattle, Boston, London, and Zurich create network effects that accelerate innovation. These advantages are particularly important for frontier AI development, which requires deep expertise and significant computational resources.

Strategic divergence: How two paths will shape the future of humanoid robotics

The emerging split in the global humanoid robotics industry — a deployment-led, manufacturing-first path in China versus an AI-first, research-driven trajectory in North America and Europe — is more than a strategic curiosity. It is the formation of two distinct ecosystems that will shape how capabilities evolve, where value is captured, and how quickly robots become an ordinary part of economic life.

Each path plays to regional strengths and carries different risk–reward profiles. China’s scale-first model accelerates real-world learning, drives down unit costs, and can produce rapid market adoption in structured applications. The Western AI-centric approach aims for generality and long-term defensibility through advanced models and software expertise, accepting slower initial deployment in exchange for potentially larger payoffs if foundational AI breakthroughs deliver human-comparable adaptation.

Practical implications to watch:

• Supply chains and standards will bifurcate, making interoperability and component sourcing more complex.
• Market segmentation will deepen: high-volume, task-specific deployments versus lower-volume, highly capable generalists.
• Policy and industrial policy will matter: procurement, subsidies, and regulation can amplify regional advantages.
• Investment patterns will reflect these dynamics: capital flows into manufacturing scale in China and compute- and talent-intensive R&D in the West.

Ultimately, the market’s outcome won’t be a simple winner-takes-all. Instead, expect parallel value chains to coexist and compete: one optimised for cost-effective, immediate utility; the other for general-purpose intelligence and adaptability. The most consequential question for industry leaders and policymakers is not which approach is intrinsically superior today, but which ecosystem can convert its early advantages into durable, compounding strengths, through data, standards, talent, and access to markets.

Also Read: Why robotic hands could make or break the humanoid industry

Whichever path proves more successful, the near-term fragmentation will shape product design, regulation, and commercial strategy for years to come. That fragmentation is not merely a technological divergence; it is the unfolding of a geopolitical and industrial contest whose outcomes will determine how and by whom robots are woven into the fabric of everyday life.

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