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Inside Singapore’s AI Bootcamp to Retrain 35,000 Bankers: Reshaping Asia’s Financial Future

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When Kelvin Chiang presented his team’s agentic AI models to Singapore’s Monetary Authority, he knew he was demonstrating something unprecedented. What used to consume an entire workday for a private banker—compiling wealth reports, validating sources of funds, drafting compliance documents—now takes just 10 minutes. But before Bank of Singapore could deploy these tools across its wealth management division, Chiang’s data scientists had to walk regulators through every safeguard, every failsafe, and every human oversight mechanism designed to prevent the system from “hallucinating” false information.

The regulators didn’t push back. They embraced it.

That collaborative spirit between government and industry defines Singapore’s radically different approach to the AI transformation sweeping global banking. While financial institutions in the United States and Europe announce mass layoffs—Goldman Sachs warning of more job cuts as AI takes hold—Singapore is executing the world’s most ambitious banking workforce retraining program. DBS Bank, OCBC, and United Overseas Bank are retraining all 35,000 of their domestic employees over the next two years, a government-backed initiative that represents not just a skills upgrade, but a fundamental reimagining of what it means to work in financial services.

The Revolutionary Scale of Singapore’s AI Training Initiative

The numbers tell only part of the story. Singapore’s three banking giants are investing hundreds of millions in a training infrastructure that reaches from entry-level tellers to senior executives. But unlike generic technology upskilling programs that plague many organizations, this bootcamp targets specific, measurable competencies needed to work alongside autonomous AI systems.

Violet Chung, a senior partner at McKinsey & Company, identifies what makes this initiative unique: “The government is doing something about it because they realize that this capability and this change is actually infusing potentially a lot of fear.” That acknowledgment of worker anxiety—combined with proactive solutions rather than platitudes—sets Singapore apart from Western approaches that often prioritize shareholder returns over workforce stability.

The Monetary Authority of Singapore (MAS) isn’t just cheerleading from the sidelines. Deputy Chairman Chee Hong Tat, who also serves as Minister for National Development, has made workforce resilience a regulatory expectation. The message to banks is clear: deploy AI aggressively, but ensure your people evolve with the technology. Singapore’s National Jobs Council, working through the Institute of Banking and Finance, offers banks up to 90% salary support for mid-career staff reskilling—an unprecedented level of public investment in private sector workforce development.

Understanding Agentic AI: The Technology Driving the Transformation

To grasp why 35,000 bankers need retraining, you must first understand what agentic AI does differently than the chatbots and recommendation engines that preceded it.

Traditional AI systems respond to prompts. Ask a question, get an answer. Agentic AI, by contrast, pursues goals autonomously. According to research from Deloitte, these systems can plan multi-step workflows, coordinate actions across platforms, and adapt their strategies in real-time based on changing circumstances—all without constant human intervention.

Consider OCBC’s implementation. Kenneth Zhu, the 36-year-old executive director of data science and AI, oversees a lab where 400 AI models make six million decisions every single day. These aren’t simple calculations. The models flag suspicious transactions, score credit risk, filter false positives in anti-money laundering systems, and even draft preliminary reports that once consumed hours of compliance officers’ time.

At DBS Bank, an internal AI assistant now handles more than one million prompts monthly. The bank has deployed role-specific tools that reduce call handling time by up to 20%—not by replacing customer service staff, but by handling the tedious documentation and data retrieval that used to interrupt human conversations. Customer service officers now spend their time actually serving customers, while AI manages the administrative burden.

The source of wealth verification process at Bank of Singapore exemplifies agentic AI’s potential. Relationship managers previously spent up to 10 days manually reviewing hundreds of pages of client documents—financial statements, tax notices, property valuations, corporate filings—to write compliance reports. The new SOWA (Source of Wealth Assistant) system completes this same analysis in one hour, cross-referencing Bank of Singapore’s extensive database and OCBC’s parent company records to validate information plausibility.

Bloomberg Intelligence forecasts that DBS will generate up to S$1.6 billion ($1.2 billion) in additional pretax profit through AI-derived cost savings—roughly a 17% boost. These aren’t theoretical projections. DBS CEO Tan Su Shan reports the bank already achieved S$750 million in AI-driven economic value in 2024, with expectations exceeding S$1 billion in 2026.

Inside the Bootcamp: How 35,000 Bankers Are Actually Learning AI

The phrase “AI bootcamp” might conjure images of programmers teaching SQL queries. Singapore’s program looks nothing like that.

The curriculum divides into three tiers, each calibrated to job function and AI exposure level:

Tier 1: AI Literacy for Everyone (All 35,000 employees)

  • Understanding what AI can and cannot do
  • Recognizing AI-generated content and potential hallucinations
  • Data privacy and security in AI contexts
  • Ethical considerations when deploying automated decision-making
  • Prompt engineering basics for interacting with AI assistants

Tier 2: AI Collaboration Skills (Frontline and Middle Management)

  • Working with AI co-pilots for customer service
  • Interpreting AI-generated insights and recommendations
  • Overriding AI decisions when human judgment is required
  • Monitoring AI system performance and reporting anomalies
  • Translating customer needs into AI-friendly inputs

Tier 3: AI Development and Governance (Technical Teams and Senior Leaders)

  • Model risk management frameworks
  • Building and validating AI use cases
  • Implementing responsible AI principles (fairness, explainability, accountability)
  • Regulatory compliance for AI systems
  • Strategic AI investment and ROI measurement

The Institute of Banking and Finance Singapore doesn’t just offer online modules. Through its Technology in Finance Immersion Programme, the organization partners with banks to create hands-on learning experiences. Participants work on actual banking challenges, developing practical skills rather than theoretical knowledge.

Dr. Jochen Wirtz, vice-dean of MBA programs at National University of Singapore, emphasizes the urgency: “Banks would be completely stupid now to load up on employees who they will then have to let go again in three or four years. You’re much better off freezing now, trying to retrain whatever you can.”

That philosophy explains why DBS has frozen hiring for AI-vulnerable positions while simultaneously training 13,000 existing employees—more than 10,000 of whom have already completed initial certification. Rather than the classic “hire-and-fire” cycle that characterizes American banking, Singapore pursues “freeze-and-train.”

The Human Reality: Fear, Adaptation, and Unexpected Opportunities

Not everyone welcomes their AI co-worker with open arms.

Bank tellers watching their branch traffic decline, back-office analysts seeing AI handle tasks they spent years mastering, relationship managers uncertain how to add value when machines draft perfect emails—the anxiety is real and justified. Singapore’s approach acknowledges these concerns rather than dismissing them.

Walter Theseira, associate professor of economics at Singapore University of Social Sciences, notes that banks are managing workforce transitions through “natural attrition rather than forced redundancies.” When employees retire, change roles internally, or move to other companies, banks increasingly choose not to backfill those positions. This gradual adjustment—combined with the creation of new AI-adjacent roles—softens the disruption.

The emerging job categories reveal how AI transforms rather than eliminates work:

  • AI Quality Assurance Specialists: Testing AI outputs for accuracy, bias, and regulatory compliance
  • Digital Relationship Managers: Handling complex wealth management with AI-generated insights
  • Automation Process Designers: Identifying workflows suitable for AI augmentation
  • Model Risk Officers: Ensuring AI systems operate within approved parameters
  • Customer Experience Strategists: Designing human-AI interaction patterns

UOB has given all employees access to Microsoft Copilot while deploying more than 300 AI-powered tools across operations. OCBC reports that AI-assisted processes have freed up capacity equivalent to hiring 1,000 additional staff—capacity redirected toward higher-value customer interactions and strategic initiatives rather than eliminated.

One success story circulating in Singapore’s banking community involves a former transaction processor who completed the AI training program and now leads a team designing automated fraud detection workflows. Her deep understanding of payment patterns—knowledge that seemed obsolete when AI took over transaction processing—became invaluable when combined with technical AI literacy. She didn’t lose her job to automation; she gained leverage over it.

Singapore’s Regulatory Philosophy: Partnership Over Policing

What separates Singapore’s approach from virtually every other financial center is how its regulator, the Monetary Authority of Singapore, engages with AI deployment.

In November 2025, MAS released its consultation paper on Guidelines for AI Risk Management—a document that reflects months of collaboration with banks rather than top-down dictates imposed on them. The guidelines focus on proportionate, risk-based oversight rather than prescriptive rules that could stifle innovation.

MAS Deputy Managing Director Ho Hern Shin explained the philosophy: “The proposed Guidelines on AI Risk Management provide financial institutions with clear supervisory expectations to support them in leveraging AI in their operations. These proportionate, risk-based guidelines enable responsible innovation.”

The guidelines address five critical areas:

  1. Governance and Oversight: Board and senior management responsibilities for AI risk culture
  2. AI Risk Management Systems: Clear identification processes and accurate AI inventories
  3. Risk Materiality Assessments: Evaluating AI impact based on complexity and reliance
  4. Life Cycle Controls: Managing AI from development through deployment and monitoring
  5. Capabilities and Capacity: Building organizational competency to work with AI safely

Rather than banning certain AI applications, MAS encourages banks to experiment while maintaining rigorous documentation of safeguards. When Kelvin Chiang presented his agentic AI tools, regulators wanted to understand the thinking process, the oversight mechanisms, and the escalation protocols—not to obstruct deployment, but to ensure responsible implementation.

This collaborative regulatory stance extends to funding. Through the IBF’s programs, Singapore effectively subsidizes workforce transformation, recognizing that individual banks cannot bear the full cost of societal-scale reskilling. PwC research shows organizations offering AI training report 42% higher employee engagement and 38% lower attrition in technical roles—benefits that justify public investment.

MAS Chairman Gan Kim Yong, who also serves as Deputy Prime Minister, framed the imperative at Singapore FinTech Festival: “It is important for us to understand that the job will change and it’s very hard to keep the same job relevant for a long period of time. As jobs evolve, we have to keep the people relevant.”

The ROI Case: Why Massive AI Investment Makes Business Sense

Singapore’s banks aren’t retraining 35,000 workers out of altruism. The business case for AI transformation is overwhelming—provided the workforce can leverage it.

DBS CEO Tan Su Shan described AI adoption as generating a “snowballing effect” of benefits. The bank’s 370 AI use cases, powered by more than 1,500 models, contributed S$750 million in economic value in 2024. She projects this will exceed S$1 billion in 2026, representing a measurable return on years of investment in both technology and people.

The efficiency gains manifest across every banking function:

Customer Service: AI handles routine inquiries, reducing average response time while allowing human agents to focus on complex problems requiring empathy and judgment. DBS’s upgraded Joy chatbot managed 120,000 unique conversations, cutting wait times and boosting satisfaction scores by 23%.

Risk Management: OCBC’s 400 AI models process six million daily decisions related to fraud detection, credit scoring, and compliance monitoring—work that would require thousands of additional staff and still produce inferior results due to human attention limitations.

Wealth Management: AI-powered portfolio analysis and market insights allow relationship managers at private banks to serve more clients at higher quality. What once required a team of analysts now happens in real-time, personalized to each client’s specific situation.

Operations: Back-office processing that once consumed entire departments now runs largely automated, with humans focused on exception handling and quality assurance rather than manual data entry.

According to KPMG research, organizations achieve an average 2.3x return on agentic AI investments within 13 months. Frontier firms leading AI adoption report returns of 2.84x, while laggards struggle at 0.84x—a performance gap that could determine competitive survival.

The transformation isn’t limited to cost savings. DBS now delivers 30 million hyper-personalized insights monthly to 3.5 million customers in Singapore alone, using AI to analyze transaction patterns, life events, and financial behaviors. These “nudges”—reminding customers of favorable exchange rates, suggesting timely financial products, flagging unusual spending—drive engagement and revenue while genuinely helping customers make better decisions.

Global Context: How Singapore’s Model Differs from Western Approaches

The contrast with American and European banking couldn’t be starker.

JPMorgan Chase CEO Jamie Dimon speaks enthusiastically about AI’s opportunities while the bank deploys hundreds of use cases. Yet JPMorgan analysts project global banks could eliminate up to 200,000 jobs within three to five years as AI scales. Goldman Sachs continues warning employees to expect cuts. The narrative centers on efficiency gains and shareholder value, with workforce impact treated as an unfortunate but necessary consequence.

European banks face different pressures. Strict labor protections make large-scale layoffs difficult, but they also complicate rapid workforce transformation. Banks attempt gradual transitions through attrition, but without Singapore’s comprehensive retraining infrastructure, displaced workers often struggle to find equivalent roles.

Singapore’s model succeeds through three unique factors:

1. Government-Industry Alignment The close relationship between MAS, the National Jobs Council, and major banks enables coordinated action impossible in more fragmented markets. When Singapore decides workforce resilience matters, resources flow accordingly.

2. Social Contract Expectations Singapore’s three major banks operate with implicit understanding that their banking licenses come with social responsibilities. Massive layoffs would trigger regulatory and reputational consequences, creating strong incentives for workforce investment.

3. Manageable Scale With 35,000 domestic banking employees across three major institutions, Singapore can execute comprehensive training that would be logistically impossible for American banks with hundreds of thousands of global staff.

Harvard Business Review analysis suggests Singapore’s approach, while difficult to replicate exactly, offers lessons for other nations: establish clear regulatory expectations around workforce transition, provide financial support for retraining, create industry-specific training partnerships, and measure success not just by AI deployment speed but by workforce adaptation rates.

The 2026-2028 Horizon: What Comes Next

As Singapore approaches the halfway point of its two-year retraining initiative, early results suggest the model works—but also highlight emerging challenges.

DBS has already reduced approximately 4,000 temporary and contract positions over three years, while UOB and OCBC report no AI-related layoffs of permanent staff. The banking sector is discovering that AI changes job composition more than job quantity, at least in the medium term.

The next wave of transformation will test whether current training adequately prepares employees. Gartner forecasts that by 2028, agentic AI will enable 15% of daily work decisions to be made autonomously—up from essentially zero in 2024. As AI agents gain more autonomy, the human role shifts from executor to orchestrator, requiring even higher-order skills.

MAS is already considering how to hold senior executives personally accountable for AI risk management, recognizing that autonomous systems create novel governance challenges. The proposed framework would mirror the Monetary Authority’s approach to conduct risk, where individuals bear clear responsibility for failures.

Singapore is also grappling with an unexpected challenge: Singlish, the local English creole, creates complications for AI natural language processing. Models trained on standard English struggle with Singapore’s unique linguistic patterns, requiring localized AI development—which in turn demands more sophisticated training for local AI specialists.

The broader implications extend beyond banking. If Singapore succeeds in demonstrating that massive AI deployment can coexist with workforce stability through strategic retraining, it provides a template for other industries and nations facing similar disruptions.

McKinsey estimates that AI could put $170 billion in global banking profits at risk for institutions that fail to adapt, while pioneers could gain a 4% advantage in return on tangible equity—a massive performance gap. Singapore’s banks, with their AI-literate workforce, position themselves firmly in the pioneer category.

Lessons for the Global Banking Industry

Singapore’s AI bootcamp experiment offers actionable insights for financial institutions worldwide:

Start with Culture, Not Technology: The most sophisticated AI fails if employees resist or misuse it. Comprehensive training that addresses fears and demonstrates value creates buy-in impossible to achieve through top-down mandates.

Partner with Government: Workforce transformation at this scale exceeds individual firms’ capacity. Public-private partnerships can distribute costs while ensuring industry-wide capability building.

Measure What Matters: Singapore tracks not just AI deployment metrics but workforce adaptation rates, employee satisfaction with AI tools, and the emergence of new hybrid roles. These human-centric measures predict long-term success better than pure technology KPIs.

Reimagine Rather Than Replace: The most successful AI implementations augment human capabilities rather than substituting for them. Relationship managers with AI insights outperform both pure humans and pure machines.

Invest in Adjacent Capabilities: AI literacy alone isn’t enough. Workers need complementary skills—critical thinking, emotional intelligence, creative problem-solving—that AI cannot replicate but can amplify.

Create New Career Paths: As traditional roles evolve, new opportunities in AI quality assurance, model risk management, and human-AI experience design create advancement paths for ambitious employees.

Accept Gradual Transition: Singapore’s two-year timeline, with flexibility for individual banks to move faster or slower based on their readiness, acknowledges that workforce transformation cannot be rushed without creating unnecessary disruption.

The Verdict: A Model Worth Watching

As the financial world watches Singapore’s unprecedented experiment, the stakes extend far beyond one nation’s banking sector. The question isn’t whether AI will transform banking—that transformation is already underway. The question is whether that transformation must inevitably create massive worker displacement, or whether strategic intervention can enable human adaptation at the pace of technological change.

Singapore bets on the latter possibility. By retraining all 35,000 domestic banking employees, by creating robust public-private partnerships, by developing comprehensive curricula that address both technical skills and existential anxieties, the city-state attempts to prove that the future of work doesn’t have to be a zero-sum battle between humans and machines.

Early returns suggest the model works. Banks report measurable productivity gains without mass layoffs. Employees initially resistant to AI training increasingly embrace it as they discover enhanced rather than diminished job prospects. Regulators fine-tune an approach that enables innovation while maintaining safety.

Yet challenges remain. Can retraining keep pace with accelerating AI capabilities? Will the job categories being created prove as numerous and lucrative as those being transformed? What happens to workers who cannot or will not adapt, despite comprehensive support?

These questions lack definitive answers. What Singapore demonstrates beyond doubt is that workforce transformation of this magnitude is possible—that major financial institutions can deploy cutting-edge AI aggressively while simultaneously investing in their people’s futures.

When historians eventually assess the AI revolution’s impact on work, Singapore’s banking sector bootcamp may be remembered as either a successful proof of concept that other nations and industries replicated, or as an admirable but ultimately isolated experiment that proved impossible to scale beyond a small, tightly integrated economy.

The next two years will tell us which.


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AI

The Price of Algorithmic War: How AI Became the New Dynamite in the Middle East

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The Iran conflict has turned frontier AI models into contested weapons of state — and the financial and human fallout is only beginning to register.

In the first eleven days of the U.S.-Israeli offensive against Iran, which began on February 28, 2026, American and Israeli forces executed roughly 5,500 strikes on Iranian targets. That is an operational tempo that would have required months in any previous conflict — made possible, in significant part, by artificial intelligence. In the first eleven days of the conflict, America achieved an astonishing 5,500 strikes, using AI on a large-scale battlefield for the first time at this scale. The National The same week those bombs fell, a legal and commercial crisis erupted in Silicon Valley with consequences that will define the AI industry for years. Both events are part of the same story.

We are living through the moment when AI ceased being a future-war thought experiment and became an operational reality — embedded in targeting pipelines, shaping intelligence assessments, and now at the center of a constitutional showdown between a frontier AI company and the United States government. Alfred Nobel, who invented dynamite and then spent the remainder of his life in tortured ambivalence about it, would have recognized the pattern immediately.

The Kill Chain, Accelerated

The joint U.S. and Israeli offensive on Iran revealed how algorithm-based targeting and data-driven intelligence are reforming the mechanics of warfare. In the first twelve hours alone, U.S. and Israeli forces reportedly carried out nearly 900 strikes on Iranian targets — an operational tempo that would have taken days or even weeks in earlier conflicts. Interesting Engineering

At the technological center of this acceleration sits a system most Americans have never heard of: Project Maven. Anthropic’s Claude has become a crucial component of Palantir’s Maven intelligence analysis program, which was also used in the U.S. operation to capture Venezuelan President Nicolás Maduro. Claude is used to help military analysts sort through intelligence and does not directly provide targeting advice, according to a person with knowledge of Anthropic’s work with the Defense Department. NBC News This is a distinction with genuine moral weight — between decision-support and decision-making — but one that is becoming harder to sustain at the speed at which modern targeting now operates.

Critics warn that this trend could compress decision timelines to levels where human judgment is marginalized, ushering in an era of warfare conducted at what has been described as “faster than the speed of thought.” This shortening interval raises fears that human experts may end up merely approving recommendations generated by algorithms. In an environment dictated by speed and automation, the space for hesitation, dissent, or moral restraint may be shrinking just as quickly. Interesting Engineering

The U.S. military’s posture has been notably sanguine about these concerns. Admiral Brad Cooper, head of U.S. Central Command, confirmed that AI is helping soldiers process troves of data, stressing that humans make final targeting decisions — but critics note the gap between that principle and verifiable practice remains wide. Al Jazeera

The Financial Architecture of AI Warfare

The economic dimensions of this transformation are substantial and largely unreported in their full complexity. Understanding them requires holding three separate financial narratives simultaneously.

The direct contract market is the most visible layer. Over the past year, the U.S. Department of Defense signed agreements worth up to $200 million each with several major AI companies, including Anthropic, OpenAI, and Google. CNBC These are not trivial sums in isolation, but they represent the seed capital of a much larger transformation. The military AI market is projected to reach $28.67 billion by 2030, as the speed of military decision-making begins to surpass human cognitive capacity. Emirates 24|7

The collateral economic disruption is less discussed but potentially far larger. On March 1, Iranian drone strikes took out three Amazon Web Services facilities in the Middle East — two in the UAE and one in Bahrain — in what appear to be the first publicly confirmed military attacks on a hyperscale cloud provider. The strikes devastated cloud availability across the region, affecting banks, online payment platforms, and ride-hailing services, with some effects felt by AWS users worldwide. The Motley Fool The IRGC cited the data centers’ support for U.S. military and intelligence networks as justification. This represents a strategic escalation that no risk-management framework in the technology sector adequately anticipated: cloud infrastructure as a legitimate military target.

The reputational and legal costs of AI’s battlefield role may ultimately dwarf both. Anthropic’s court filings stated that the Pentagon’s supply-chain designation could cut the company’s 2026 revenue by several billion dollars and harm its reputation with enterprise clients. A single partner with a multi-million-dollar contract has already switched from Claude to a competing system, eliminating a potential revenue pipeline worth more than $100 million. Negotiations with financial institutions worth approximately $180 million combined have also been disrupted. Itp

The Anthropic-Pentagon Fracture: A Defining Test

The dispute between Anthropic and the U.S. Department of Defense is not merely a contract negotiation gone wrong. It is the first high-profile case in which a frontier AI company drew a public ethical line — and then watched the government attempt to destroy it for doing so.

The sequence of events is now well-documented. The administration’s decisions capped an acrimonious dispute over whether Anthropic could prohibit its tools from being used in mass surveillance of American citizens or to power autonomous weapon systems, as part of a military contract worth up to $200 million. Anthropic said it had tried in good faith to reach an agreement, making clear it supported all lawful uses of AI for national security aside from two narrow exceptions. NPR

When Anthropic held its position, the response was unprecedented in the annals of U.S. technology policy. Defense Secretary Pete Hegseth declared Anthropic a supply chain risk in a statement so broad that it can only be seen as a power play aimed at destroying the company. Shortly thereafter, OpenAI announced it had reached its own deal with the Pentagon, claiming it had secured all the safety terms that Anthropic sought, plus additional guardrails. Council on Foreign Relations

In an extraordinary move, the Pentagon designated Anthropic a supply chain risk — a label historically only applied to foreign adversaries. The designation would require defense vendors and contractors to certify that they don’t use the company’s models in their work with the Pentagon. CNBC That this was applied to a U.S.-headquartered company, founded by former employees of a U.S. nonprofit, and valued at $380 billion, represents a remarkable inversion of the logic the designation was designed to serve.

Meanwhile, Washington was attacking an American frontier AI leader while Chinese labs were on a tear. In the past month alone, five major Chinese models dropped: Alibaba’s Qwen 3.5, Zhipu AI’s GLM-5, MiniMax’s M2.5, ByteDance’s Doubao 2.0, and Moonshot’s Kimi K2.5. Council on Foreign Relations The geopolitical irony is not subtle: in punishing a safety-focused American AI company, the administration may have handed Beijing its most useful competitive gift of the year.

The Human Cost: Social Ramifications No Algorithm Can Compute

Against the financial ledger, the humanitarian accounting is staggering and still incomplete.

The Iranian Red Crescent Society reported that the U.S.-Israeli bombardment campaign damaged nearly 20,000 civilian buildings and 77 healthcare facilities. Strikes also hit oil depots, several street markets, sports venues, schools, and a water desalination plant, according to Iranian officials. Al Jazeera

The case that has attracted the most scrutiny is the bombing of the Shajareh Tayyebeh elementary school in Minab, southern Iran. A strike on the school in the early hours of February 28 killed more than 170 people, most of them children. More than 120 Democratic members of Congress wrote to Defense Secretary Hegseth demanding answers, citing preliminary findings that outdated intelligence may have been to blame for selecting the target. NBC News

The potential connection to AI decision-support systems is explored with forensic precision by experts at the Bulletin of the Atomic Scientists. One analysis notes that the mistargeting could have stemmed from an AI system with access to old intelligence — satellite data that predated the conversion of an IRGC compound into an active school — and that such temporal reasoning failures are a known weakness of large language models. Even with humans nominally “in the loop,” people frequently defer to algorithmic outputs without careful independent examination. Bulletin of the Atomic Scientists

The social fallout extends well beyond individual atrocities. Israel’s Lavender AI-powered database, used to analyze surveillance data and identify potential targets in Gaza, was wrong at least 10 percent of the time, resulting in thousands of civilian casualties. A recent study found that AI models from OpenAI, Anthropic, and Google opted to use nuclear weapons in simulated war games in 95 percent of cases. Rest of World The simulation result does not predict real-world behavior, but it reveals how strategic reasoning models can default toward extreme outcomes under pressure — a finding that ought to unsettle anyone who imagines that algorithmic warfare is inherently more precise than the human kind.

The corrosion of accountability is perhaps the most insidious long-term social effect. “There is no evidence that AI lowers civilian deaths or wrongful targeting decisions — and it may be that the opposite is true,” says Craig Jones, a political geographer at Newcastle University who researches military targeting. Nature Yet the speed and opacity of AI-assisted operations makes it exponentially harder to assign responsibility when things go wrong. Algorithms do not face courts-martial.

Governance: The International Gap

Rapid technological development is outpacing slow international discussions. Academics and legal experts meeting in Geneva in March 2026 to discuss lethal autonomous weapons systems found themselves studying a technology already being used at scale in active conflicts. Nature The gap between the pace of deployment and the pace of governance has never been wider.

The Middle East and North Africa are arguably the most conflict-ridden and militarized regions in the world, with four out of eleven “extreme conflicts” identified in 2024 by the Armed Conflict Location and Event Data organization occurring there. The region has become a testing ground for AI warfare whose lessons — and whose errors — will shape every future conflict. War on the Rocks

The legal framework governing AI in warfare remains, generously described, aspirational. The U.S. military’s stated commitment to keeping “humans in the loop” is a principle that has no internationally binding enforcement mechanism, no agreed definition of what meaningful human control actually entails, and no independent auditing process. One expert observed that the biggest danger with AI is when humans treat it as an all-purpose solution rather than something that can speed up specific processes — and that this habit of over-reliance is particularly lethal in a military context. The National

AI as the New Dynamite: Nobel’s Unresolved Legacy

When Alfred Nobel invented dynamite in 1867, he believed — genuinely — that a weapon so devastatingly efficient would make war unthinkably costly and therefore rare. He was catastrophically wrong. The Franco-Prussian War, the First World War, and the entire industrial-era atrocity that followed proved that more powerful weapons do not deter wars; they escalate them, and they increase civilian mortality relative to combatant casualties.

The parallel to AI is not decorative. The argument for AI in warfare — that algorithmic precision reduces collateral damage, that faster targeting shortens conflicts, that autonomous systems absorb military risk that would otherwise fall on human soldiers — is structurally identical to Nobel’s argument for dynamite. It is the rationalization of a dual-use technology by those with an interest in its proliferation.

Drone technology in the Middle East has already shifted from manual control toward full autonomy, with “kamikaze” drones utilizing computer vision to strike targets independently if communications are severed. As AI becomes more integrated into militaries, the advancements will become even more pronounced with “unpredictable, risky, and lethal consequences,” according to Steve Feldstein, a senior fellow at the Carnegie Endowment for International Peace. Rest of World

The Anthropic dispute, whatever its ultimate legal resolution, has surfaced a question that Silicon Valley has been able to defer until now: can a technology company that builds frontier AI models — systems capable of synthesizing intelligence, generating targeting assessments, and running strategic simulations — genuinely control how those systems are used once deployed by a state? As OpenAI’s own FAQ acknowledged when asked what would happen if the government violated its contract terms: “As with any contract, we could terminate it.” The entire edifice of AI safety in warfare, for now, rests on the contractual leverage of companies that have already agreed to participate. Council on Foreign Relations

Nobel at least had the decency to endow prizes. The AI industry is still working out what it owes.

Policy Recommendations

A minimally adequate governance framework for AI in warfare would need to accomplish several things. Independent verification of “human in the loop” claims — not merely the assertion of it — is the essential starting point. Mandatory after-action reporting on AI involvement in any strike that results in civilian casualties would create accountability where none currently exists. International agreement on a baseline error-rate threshold — above which AI targeting systems may not be used without additional human review — would translate abstract humanitarian law into operational reality.

The technology companies themselves bear responsibility that no contract clause can fully discharge. Researchers from OpenAI, Google DeepMind, and other labs submitted a court filing supporting Anthropic’s position, arguing that restrictions on domestic surveillance and autonomous weapons are reasonable until stronger legal safeguards are established. ColombiaOne That the most capable AI builders in the world believe their own technology is not yet reliable enough for autonomous lethal use is information that should be at the center of every policy debate — not buried in court filings.


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Analysis

US-China Paris Talks 2026: Behind the Trade Truce, a World on the Brink

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Bessent and He Lifeng meet at OECD Paris to review the Busan trade truce before Trump’s Beijing summit. Rare earths, Hormuz oil shock, and Section 301 cloud the path ahead.

The 16th arrondissement of Paris is not a place that announces itself. Discreet, residential, its wide avenues lined with haussmann facades, it is the kind of neighbourhood where power moves quietly. On Sunday morning, as French voters elsewhere in the city queued outside polling stations for the first round of local elections, a motorcade slipped through those unassuming streets toward the headquarters of the Organisation for Economic Co-operation and Development. Inside, the world’s two largest economies were attempting something rare in 2026: a structured, professional conversation.

Talks began at 10:05 a.m. local time, with Vice-Premier He Lifeng accompanied by Li Chenggang, China’s foremost international trade negotiator, while Treasury Secretary Scott Bessent arrived flanked by US Trade Representative Jamieson Greer. South China Morning Post Unlike previous encounters in European capitals, the delegations were received not by a host-country official but by OECD Secretary-General Mathias Cormann South China Morning Post — a small detail that spoke volumes. France was absorbed in its own democratic ritual. The world’s most consequential bilateral relationship was, once again, largely on its own.

The Stakes in Paris: More Than a Warm-Up Act

It would be tempting to dismiss the Paris talks as logistical scaffolding for a grander event — namely, President Donald Trump’s planned visit to Beijing at the end of March for a face-to-face with President Xi Jinping. That reading would be a mistake. The discussions are expected to cover US tariff adjustments, Chinese exports of rare earth minerals and magnets, American high-tech export controls, and Chinese purchases of US agricultural commodities CNBC — a cluster of issues that, taken together, constitute the structural skeleton of the bilateral relationship.

Analysts cautioned that with limited preparation time and Washington’s strategic focus consumed by the US-Israeli military campaign against Iran, the prospects for any significant breakthrough — either in Paris or at the Beijing summit — remain constrained. Investing.com As Scott Kennedy, a China economics specialist at the Center for Strategic and International Studies, put it with characteristic precision: “Both sides, I think, have a minimum goal of having a meeting which sort of keeps things together and avoids a rupture and re-escalation of tensions.” Yahoo!

That minimum — preserving the architecture of the relationship, not remodelling it — may, in the current environment, be ambitious enough.

Busan’s Ledger: What Has Been Delivered, and What Has Not

The two delegations were expected to review progress against the commitments enshrined in the October 2025 trade truce brokered by Trump and Xi on the sidelines of the APEC summit in Busan, South Korea. Yahoo! On certain metrics, the scorecard is encouraging. Washington officials, including Bessent himself, have confirmed that China has broadly honoured its agricultural obligations under the deal Business Standard — a meaningful signal at a moment when diplomatic goodwill is scarce.

The soybean numbers are notable. China committed to purchasing 12 million metric tonnes of US soybeans in the 2025 marketing year, with an escalation to 25 million tonnes in 2026 — a procurement schedule that begins with the autumn harvest. Yahoo! For Midwestern farmers and the commodity desks that serve them, these are not abstractions; they are the difference between a profitable season and a foreclosure notice.

But the picture darkens considerably when attention shifts to critical materials. US aerospace manufacturers and semiconductor companies are experiencing acute shortages of rare earth elements, including yttrium — a mineral indispensable in the heat-resistant coatings that protect jet engine components — and China, which controls an estimated 60 percent of global rare earth production, has not yet extended full export access to these sectors. CNBC According to William Chou, a senior fellow at the Hudson Institute, “US priorities will likely be about agricultural purchases by China and greater access to Chinese rare earths in the short term” Business Standard at the Paris talks — a formulation that implies urgency without optimism.

The supply chain implications are already registering. Defence contractors reliant on rare-earth permanent magnets for guidance systems, electric motors in next-generation aircraft, and precision sensors are operating on diminished buffers. The Paris talks, if they yield anything concrete, may need to yield this above all.

A New Irritant: Section 301 Returns

Against this backdrop of incremental compliance and unresolved bottlenecks, the US side has introduced a fresh complication. Treasury Secretary Bessent and USTR Greer are bringing to Paris a new Section 301 trade investigation targeting China and 15 other major trading partners CNBC — a revival of the legal mechanism previously used to justify sweeping tariffs during the first Trump administration. The signal it sends is deliberately mixed: Washington is simultaneously seeking to consolidate the Busan framework and reserving the right to escalate it.

For Chinese negotiators, the juxtaposition is not lost. Beijing has staked considerable domestic political credibility on the proposition that engagement with Washington produces tangible results. A Section 301 investigation, even if procedurally nascent, raises the spectre of a new tariff architecture layered atop the existing one — and complicates the case for continued compliance within China’s own policy bureaucracy.

The Hormuz Variable: When Geopolitics Enters the Room

No diplomatic meeting in March 2026 can be quarantined from the wider strategic environment, and the Paris talks are no exception. The ongoing US-Israeli military campaign against Iran has introduced a variable of potentially severe economic consequence: the partial closure of the Strait of Hormuz, the narrow waterway through which approximately a fifth of the world’s oil passes.

China sources roughly 45 percent of its imported oil through the Strait, making any disruption there a direct threat to its industrial output and energy security. Business Standard After US forces struck Iran’s Kharg Island oil loading facility and Tehran signalled retaliatory intent, President Trump called on other nations to assist in protecting maritime passage through the Strait. CNBC Bessent, for his part, issued a 30-day sanctions waiver to permit the sale of Russian oil currently stranded on tankers at sea CNBC — a pragmatic, if politically contorted, attempt to soften the energy-price spike.

For the Paris talks, the Hormuz dimension introduces a paradox. China has an acute economic interest in stabilising global oil flows and might, in principle, be receptive to coordinating with the United States on maritime security. Yet Beijing’s deep reluctance to be seen as endorsing or facilitating US-led military operations in the Middle East constrains how far it can go. The corridor between shared interest and political optics is narrow.

What Trump Wants in Beijing — and What Xi Can Deliver

With Trump’s Beijing visit now functioning as the near-term endpoint of this diplomatic process, the outlines of a summit package are beginning to take shape. The US president is expected to seek major new Chinese commitments on Boeing aircraft orders and expanded purchases of American liquefied natural gas Yahoo! — both commercially significant and symbolically resonant for domestic audiences. Boeing’s recovery from years of regulatory and reputational turbulence has made its order book a quasi-barometer of US industrial confidence; LNG exports represent a strategic diversification of American energy diplomacy.

For Xi, the calculus involves threading a needle between delivering enough to make the summit worthwhile and conceding so much that it invites criticism at home from nationalist constituencies already sceptical of engagement. China’s state media has consistently characterised the Paris talks as a potential “stabilising anchor” for an increasingly uncertain global economy Republic World — language carefully chosen to frame engagement as prudent statecraft rather than capitulation.

The OECD itself, whose headquarters serves as neutral ground for today’s meeting, cut its global growth forecast earlier this year amid trade fragmentation fears — underscoring that the bilateral relationship between Washington and Beijing carries systemic weight far beyond its two principals. A credible summit, even one short of transformative, would send a signal to investment desks and central banks from Frankfurt to Singapore that the world’s two largest economies retain the institutional capacity to manage their rivalry.

The Road to Beijing, and Beyond

What happens in the 16th arrondissement today will not resolve the structural tensions that define the US-China relationship in this decade. The rare-earth bottleneck is systemic, not administrative. The Section 301 investigation reflects a bipartisan American political consensus that China’s industrial subsidies represent an existential competitive threat. And the Iran war has introduced a geopolitical variable that neither side fully controls.

But the Paris talks serve a purpose that transcends their immediate agenda. They demonstrate, to a watching world, that diplomacy between great powers remains possible even as military operations unfold and supply chains fracture. They keep open the channels through which, eventually, more durable arrangements might be negotiated — whether at a Beijing summit, at the G20 in Johannesburg later this year, or in another European capital where motorcades slip, unannounced, through quiet streets.

The minimum goal, as CSIS’s Kennedy observed, is avoiding rupture. In the spring of 2026, with the Strait of Hormuz partially closed and yttrium shipments stalled, that minimum has acquired the weight of ambition.


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Analysis

How the Middle East Conflict Is Reshaping ASEAN & SAARC Economies

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On November 19, 2023, Houthi militants seized a Bahamian-flagged cargo ship in the Red Sea. That single act of piracy — framed as solidarity with Gaza — triggered the most consequential maritime disruption to global trade since the 2021 Ever Given blockage. Two and a half years later, the Strait of Bab el-Mandeb remains a war zone in all but name, the Suez Canal handles barely a fraction of its former traffic, and the economies of eighteen nations stretching from Sri Lanka to the Philippines are absorbing cascading shocks they did not generate and cannot fully control. This is the story of how a distant conflict has become a near-present economic emergency across ASEAN and SAARC — and what it means for growth, inflation, remittances, and supply chains through 2028.

The Red Sea in Numbers: A Chokepoint Under Siege

The statistics are staggering. According to UNCTAD’s 2025 Maritime Trade Review, tonnage through the Suez Canal stood 70 percent below 2023 levels as recently as May 2025 UNCTAD, and the trajectory of recovery remains deeply uncertain. Container shipping has been devastated: traffic through the canal collapsed by roughly 75 percent during 2024 compared with 2023 averages, with no meaningful recovery through mid-2025 — data from July 2025 showing no recovery in container vessel transit through the canal, and Houthi attacks as recently as August 2025 making recovery unlikely soon Project44. The Suez Canal’s share of global maritime traffic has slipped from roughly 12 percent to below 9 percent — a structural shift that may not fully reverse even if hostilities cease.

The rerouting of vessels around Africa’s Cape of Good Hope adds 10–14 days to Asia–Europe voyages, pushing total transit times to 40–50 days. Freight rates between Shanghai and Rotterdam surged fivefold in 2024 Yqn. Rates between Shanghai and Rotterdam remained significantly higher than before the attacks began — up 80 percent relative to pre-crisis levels as of 2025. Coface UNCTAD notes that ship ton-miles hit a record annual rise of 6 percent in 2024, nearly three times faster than underlying trade volume growth. By May 2025, the Strait of Hormuz — through which 11 percent of global trade and a third of seaborne oil pass — also faced disruption risks. UNCTAD

The Asian Development Bank’s July 2025 Outlook modelled three Middle East scenarios. In its most severe case — a protracted conflict with Strait of Hormuz disruption — oil prices could surge $55 per barrel for four consecutive quarters. Asian Development Bank The Strait of Hormuz, through which roughly one-third of all seaborne oil and over one-fifth of global LNG supply passes (the latter primarily from Qatar), is a chokepoint of existential importance to every oil-importing nation from Dhaka to Manila.

The Oil Shock Transmission: How Energy Costs Hit 18 Economies

For most of 2025, Brent crude had traded in the $60–$74/barrel range, offering breathing room to energy-hungry emerging economies. That calculus shifted dramatically in early 2026. With fresh military action involving the United States and Israel targeting Iran, Brent broke above $100/bbl — roughly 70 percent above its 2025 average of $68/bbl — according to OCBC Group Research. European gas (TTF) simultaneously pushed past €50/MWh. OCBC

MUFG Research sensitivity modelling shows that every $10/barrel increase in oil prices worsens Asia’s current account balance by 0.2–0.9 percent of GDP. Thailand is the region’s most exposed economy (current account impact: -0.9% of GDP per $10/bbl), followed by Singapore (-0.7%), South Korea (-0.6%), and the Philippines. Inflationary effects are equally asymmetric: a $10/bbl oil price rise pushes annual headline CPI up by 0.6–0.8 percentage points in Thailand, 0.5–0.7pp in India and the Philippines, and 0.4–0.6pp across Malaysia, Indonesia, and Vietnam. MUFG Research Countries with fuel subsidies — notably Indonesia and Malaysia — absorb part of the pass-through fiscally, but at escalating cost to their budgets.

ASEAN: The Differentiated Exposure

ASEAN nations face wildly varying degrees of vulnerability. The Philippines sources 96 percent of its oil from the Gulf, Vietnam and Thailand approximately 87 percent and 74 percent respectively, while Singapore is more than 70 percent dependent on Middle Eastern crude — with 45 percent of its LNG imports arriving from Qatar alone. The Diplomat

The ADB’s April 2025 Outlook cut Singapore’s 2025 growth forecast to 2.6 percent (from 4.4% in 2024), citing weaker exports driven by global trade uncertainties and weaker external demand. Asian Development Bank The IMF revised ASEAN-5 aggregate growth down further to 4.1 percent in July 2025, versus earlier forecasts of 4.6 percent, with trade-dependent Vietnam (revised to 5.2% in 2025), Thailand (2.8%), and Cambodia most acutely affected. Krungsri

SAARC: The Remittance Fault Line

For the eight SAARC economies, the crisis is doubly coercive: higher energy import bills on one side, threatened remittance flows on the other.

India illustrates the tension most sharply. The country consumes approximately 5.3–5.5 million barrels per day while producing barely 0.6 million domestically, making it nearly 85 percent import-dependent. Petroleum imports already account for 25–30 percent of India’s total import bill, and every $10 oil price increase adds $12–15 billion to the annual cost. IANS News Historically, such episodes have triggered rupee depreciations exceeding 10 percent.

The remittance dimension is equally alarming. India received a record $137 billion in remittances in 2024, retaining its position as the world’s largest recipient. United Nations The 9-million-strong Indian diaspora in Gulf countries contributes nearly 38 percent of India’s total remittance inflows — roughly $51.4 billion from the GCC alone, based on FY2025 inflows of $135.4 billion. These workers are concentrated in oil services, construction, hospitality and retail: precisely the sectors most vulnerable to Gulf economic disruption. Oxford Economics estimates a sustained shock “would worsen India’s external position and could put some pressure on the rupee.” CNBC

Pakistan: Caught in the Crossfire

Pakistan’s total petroleum import bill reached approximately $10.7 billion in FY25, with crude petroleum imports of over $5.7 billion sourced predominantly from Saudi Arabia and the UAE. Its trade deficit has widened to approximately $25 billion during July–February FY26. Domestic fuel prices have already risen by approximately Rs55 ($0.20) per litre, reflecting the war-risk premium embedded in global crude markets. Profit by Pakistan Today

The remittance channel is equally fragile. Pakistan received $34.6 billion in remittances in 2024 — accounting for 9.4 percent of GDP — with Saudi Arabia alone contributing $7.4 billion (25 percent of the total), and the UAE contributing $5.5 billion (18.7 percent). Displacement Tracking Matrix An Insight Securities research note from March 2026 warns that geopolitical tensions involving the US, Israel, and Iran “have taken a hit on the security and stability perception” of Gulf economies, with the effect on Pakistani remittances expected to materialise with a lag. About 55 percent of Pakistan’s remittance inflows come from the Middle East, making the country particularly vulnerable. Arab News PK

For Pakistani exporters, shipping diversions around the Cape of Good Hope are extending transit times to Europe by 15–20 days, while freight rates on key routes could rise by up to 300 percent under war-risk classification. Profit by Pakistan Today

Bangladesh and Sri Lanka: Garments, Tea, and the Weight of Distance

Bangladesh’s vulnerability is concentrated in one devastating statistic: more than 65 percent of its garment exports — representing roughly $47 billion of an approximately $55 billion annual export economy — pass through or proximate to the Red Sea corridor. LinkedIn When Maersk confirmed on March 3, 2026, that it had suspended all new bookings between the Indian subcontinent and the Upper Gulf — covering the UAE, Bahrain, Qatar, Iraq, Kuwait, and Saudi Arabia — it confirmed that the escalating Iran crisis was no longer merely raising risk premiums; it was severing commercial flows entirely. The Daily Star

The garment sector cannot absorb air freight as a substitute: the BGMEA president notes that air freight costs have increased between 25–40 percent for some European buyers due to the Red Sea crisis, and some buyers are renegotiating contracts or diverting orders. The Daily Star As one garment vice president told Nikkei Asia, air freight costs 10–12 times more than sea transport — an instant route to negative margins. Bangladesh cannot afford order diversion at scale.

Sri Lanka’s exposure cuts across multiple arteries simultaneously. With over 1.5 million Sri Lankans (nearly 7 percent of the population) employed in the Gulf region, and the island recording a record $8 billion in remittances in 2025, any large-scale evacuation or Gulf economic contraction would shatter the fiscal stability the government has only recently achieved. Sri Lanka’s tea exports to Iran, Iraq, and the UAE — where the Iranian rial’s collapse has triggered a freeze in new orders — threaten the livelihoods of smallholder farmers across the southern highlands. EconomyNext

The Hormuz Wildcard: A Scenario That Could Rewrite Everything

Much of the analysis above rests on a scenario in which the Strait of Hormuz remains open. Should it be disrupted — even temporarily — the macroeconomic calculus transforms. Approximately 20 percent of global oil consumption transits the Strait daily, along with over one-fifth of the world’s LNG supply. Alternative land pipelines — Saudi Arabia’s East-West Pipeline and the UAE’s Abu Dhabi Crude Oil Pipeline to Fujairah — can offer some help, but their capacity represents barely one quarter of normal Hormuz throughput. MUFG Research

Under the ADB’s most severe scenario — a $55/barrel sustained oil shock — the impact on current account balances across ASEAN and South Asia would be severe. Current account deficits for the Philippines and India could widen above 4.5 percent and 2 percent of GDP respectively if oil prices were to rise above $90/bbl on a sustained basis. MUFG Research Pakistan, with minimal fiscal buffers, would face renewed currency crisis. India’s annual import bill would expand by roughly $82 billion relative to 2025 averages — approximately equal to its entire defence budget.

Silver Linings and Second-Order Winners

Crises reshape competitive landscapes. Vietnam’s electronics and apparel sector recorded export turnover of $4.45 billion in July 2025 — an 8.2 percent increase over June and 21 percent higher than the same month last year — driven partly by supply chain shifts away from China. Asian Development Bank Malaysia and Indonesia, as partial net energy exporters, benefit from elevated crude prices on the revenue side. Singapore, with a FY2025 fiscal surplus of 1.9 percent of GDP, has the deepest fiscal reserves in ASEAN to deploy energy transition support without macroeconomic destabilisation. OCBC

Thailand has launched planning work on its $28 billion Landbridge project — deep-sea ports at Ranong and Chumphon connected by highway and rail — as a potential alternative corridor to the Strait of Malacca. India is accelerating infrastructure at Chabahar Port, a corridor that bypasses Pakistani territory and opens Central Asian trade routes. The “friend-shoring” dynamic identified by the IMF is also accelerating: as Western supply chains reconfigure away from single-region dependence, ASEAN economies — particularly Vietnam and Indonesia — stand to attract manufacturing diversion from China that partially offsets the Middle East trade cost shock. Krungsri

China’s Shadow: The Geopolitical Dimension

No analysis of the Middle East’s economic impact on ASEAN and SAARC is complete without acknowledging Beijing’s role. China, which imports roughly 75 percent of its crude from the Middle East and Africa, has more at stake in Hormuz stability than almost any other economy. Yet Beijing has maintained studied neutrality, positioning itself as potential peacebroker while expanding bilateral energy security arrangements with Gulf states.

Meanwhile, China’s Belt and Road Initiative (BRI) port infrastructure — Gwadar in Pakistan, Hambantota in Sri Lanka, Kyaukpyu in Myanmar — is emerging as a hedging option for economies seeking to reduce Red Sea exposure. The IMF’s Regional Economic Outlook warns that geoeconomic fragmentation — the splitting of global trade into rival blocs — carries a potential output cost, with a persistent spike in global uncertainty producing GDP losses of 2.5 percent after two years in the MENA and adjacent regions, with the impacts more pronounced than elsewhere due to vulnerabilities including higher public debt and weaker institutions. International Monetary Fund

Outlook 2026–2028: GDP Drag Estimates and Divergent Trajectories

Baseline projections remain broadly positive for the region, underpinned by demographic dividends and resilient domestic demand. The World Bank’s October 2025 MENAAP Update projects regional growth reaching 2.8 percent in 2025 and 3.3 percent in 2026. World Bank The IMF’s October 2025 Regional Outlook projects Pakistan’s growth increasing to 3.6 percent in 2026, supported by reform implementation and improving financial conditions. International Monetary Fund ADB’s September 2025 forecasts show Indonesia at 4.9%, Philippines at 5.6%, and Malaysia at 4.3% for 2025. Asian Development Bank

But the scenario distribution has widened materially. In a contained-conflict baseline (oil averaging $75–85/bbl), the GDP drag for oil-importing SAARC economies is estimated at 0.3–0.7 percentage points annually through 2027 — painful but manageable. In a protracted Hormuz-disruption scenario, modelled GDP losses escalate to 1.5–3.0 percentage points for the most energy-dependent economies: Sri Lanka, Philippines, Bangladesh, and Pakistan. Currency pressures in that scenario could trigger sovereign debt rating downgrades for Pakistan (still under IMF programme) and Sri Lanka (still restructuring external debt).

Policy Recommendations for ASEAN and SAARC Governments

The foregoing analysis suggests a multi-track policy agenda structured across three time horizons:

Immediate (0–6 months)

  • Strategic petroleum reserves: Economies with fewer than 30 days of import cover — Bangladesh, Sri Lanka, Pakistan, Philippines — should accelerate bilateral arrangements with GCC suppliers for deferred-payment oil stocking.
  • Freight & insurance backstops: State-owned development banks in India, Indonesia, and Malaysia should establish temporary freight insurance facilities for SME exporters unable to access war-risk cover at commercial rates.
  • Fiscal fuel-price buffers: Governments should resist immediate full pass-through of oil price increases to consumers in 2026 — the inflationary second-round effects of premature deregulation risk destabilising monetary policy just as disinflation was being consolidated.

Medium-Term (6–24 months)

  • Trade corridor diversification: ASEAN and SAARC should jointly accelerate operationalisation of the India-Middle East-Europe Economic Corridor (IMEC) and Chabahar-Central Asia links to reduce exclusive dependence on the Suez/Red Sea routing for European-bound exports.
  • Renewable energy acceleration: Each percentage point of fossil fuel imports replaced by domestic solar, wind, or nuclear capacity is a permanent reduction in geopolitical exposure. ADB Green Climate Fund allocations should be explicitly linked to energy import substitution targets.
  • Remittance formalisation: Bangladesh, Pakistan, and Sri Lanka should extend incentive schemes to maximise remittance capture through official banking channels, maximising their foreign-exchange multiplier effect.

Long-Term (2–5 years)

  • “Asia Premium” hedge architecture: A regional crude futures market, potentially anchored in Singapore, could provide more effective price discovery and hedging access to smaller economies that currently pay a structural premium above Brent.
  • Supply chain friend-shoring with selectivity: ASEAN’s competitive advantage is best served by remaining in the middle of the US-China geopolitical competition rather than choosing sides definitively, attracting Western supply-chain investment without triggering Chinese economic retaliation through rare earth or intermediate input export controls.
  • Multilateral maritime security: ASEAN and SAARC together represent a significant share of the global trade disruption cost. A formal joint diplomatic initiative requesting a UN-mandated naval security corridor for commercial shipping through the Red Sea and Gulf would add multilateral legitimacy to what is currently a US-led Western operation.

Conclusion: The Geography of Exposure

The Middle East conflict has delivered a masterclass in the hidden geography of economic exposure. Countries that share no border with Israel, Hamas, or Iran — countries that have issued no military guarantee and sent no troops — are nonetheless absorbing the full force of an energy price shock, a logistics cost spiral, and a remittance fragility that was structurally built into their growth models over decades.

Even if hostilities ceased tomorrow, the Red Sea crisis — now stretching into its third year as of 2026 — has tested the limits of global logistics. With Red Sea transits down up to 90 percent and Cape of Good Hope routing now the industry standard, companies face 10–14 extra days in transit, higher inventory costs, and sustained freight premiums of 25–35 percent. DocShipper The ceasefire declared in October 2025 barely shifted the dial. Shipping insurers remain risk-averse; carriers have rebuilt vessel schedules around the longer route.

What the crisis has done is clarify something that globalisation’s practitioners long preferred to obscure: deep economic integration produces deep interdependence, and deep interdependence produces deep vulnerability. The eighteen economies of ASEAN and SAARC are not passive bystanders in a conflict 4,000 miles away. They are, in the most material and measurable sense, participants in its economic consequences. The policy leaders who understand that soonest — and build the resilience architecture accordingly — will determine which countries emerge from the coming years stronger, and which emerge diminished.


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