Citi: Exploring AI's Role in Global Trade Transformation
Global trade is being rewired by tariff shifts, AI adoption and a decisive move toward multipolar, regional supply networks. Citi's latest Global Perspectives & Solutions (Citi GPS) report, Supply Chain Financing - Durable Global Trade in the Age of AI, finds businesses stayed resilient, adapting policy-by-policy while keeping a tight focus on diversification and working capital.
The analysis blends Citi's Global Supply Chain Pressure Index, daily payment flows from its US$5tn Services business and survey data from multinationals and SMEs. The headline: disruption is now baseline, yet trade is holding steady and getting smarter.
Tariffs up, pressures muted
Despite US tariffs rising to roughly 16.8% from 2.4% before the change in US administration, Citi's Index shows supply chain pressures remain close to pre-pandemic levels. Companies absorbed the shock with better inventory discipline, supplier spreads and accelerated nearshoring.
Trade routes are reshuffling. South Asia and ASEAN gained strongly, with a 44% jump in shipments from North and East Asia. Latin America deepened its role across Asia- and North America-linked supply chains, with exports to South Asia and ASEAN up 82%-the largest increase globally.
The US broadened its import base: shipments from South Asia and ASEAN rose 50%, and Latin America 43%, both above the 32% growth from North and East Asia. As Shahmir Khaliq, Head of Services at Citi, notes: "Global trade and geopolitics are closely intertwined, with export growth from North and East Asia shifting towards more emerging economies in efforts to diversify customers."
AI is reshaping trade finance execution
"AI-powered intelligent document processing enables exceptionally high accuracy rates and reduces processing to just minutes," says Adoniro Cestari, Global Head of Trade and Working Capital at Citi. "Through a pilot of blockchain-based conditional trade payments, we have seen the potential for an evolution from standard paper-based guarantees to near 24/7 digital execution and automated settlement."
Faster, cleaner execution lowers exception rates and improves liquidity timing. For treasury teams, that means tighter DSO/DPO control, sharper cash forecasting and fewer working-capital surprises.
AI infrastructure is a capex supercycle
The report flags a once-in-a-generation wave of data center investment, with Citi Research estimating US$7.75tn in AI-related capex by 2030. Trade finance sits at the core of this buildout-supply chain finance, pre-shipment financing and structured receivables are bridging long cash conversion cycles across construction, equipment and energy loads.
Adoption is accelerating: 36% of large corporates now use AI tools in trade and working capital, up 18% from 2025. The goal is simple-release trapped liquidity, compress cycle times and expand supplier reach without compromising risk standards.
Working capital is now strategy
Input costs are the top concern for 64% of companies. On average, 6.3% of working capital is currently funding tariff costs-real money stuck in transit instead of fueling growth.
Firms are acting. Inventory finance, structured receivables and dynamic discounting are moving from projects to policy. In Citi's survey of 710 large corporations, 65% are actively diversifying supply chains away from one or more countries, with Vietnam, Thailand, India and Mexico as leading destinations.
Rationalisation is back: 46% plan to reduce inventory to unlock liquidity, up from 16% in 2023. Meanwhile, China's share of US imports fell to 8% by late 2025, from more than 20% in 2018.
As Cestari puts it: "Disruption is no longer a bug in global trade - it's a feature. Having absorbed a pandemic, conflicts and now a highly-fragmented policy environment, global trade is not in retreat - it is evolving, supported by innovation, investment and operational agility."
What finance leaders can do next
- Rebalance suppliers and terms: Expand qualified suppliers in South Asia, ASEAN and Latin America; use multi-banker trade programs to avoid single points of failure.
- Put AI to work in operations: Deploy intelligent document processing to cut turn-times and errors; pilot rule-based, conditional payment structures where counterparties allow.
- Unlock cash now: Scale inventory finance and structured receivables; use dynamic discounting with data-driven pricing to capture yield on surplus cash.
- Tighten tariff exposure: Treat tariff spend as a working-capital line item; run SKU-level contribution analysis to justify price moves or reroutes.
- Prepare for AI capex demand: Build credit limits and risk-sharing structures for data center supply chains (power, equipment, construction, connectivity).
- Instrument the network: Track supply chain pressure signals and payment flow variances weekly; escalate early when cycle times slip.
Further reading
See the full analysis in the Citi GPS report. For hands-on ways to apply automation in treasury, explore AI for Finance.
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