Companies across industries are fast-tracking artificial intelligence investment to navigate tariff shocks, inflation, and geopolitical uncertainty. Yet most still lack the organizational discipline and data maturity to translate those bets into day-to-day operational advantage. New research from Economist Impact, commissioned by Kinaxis, shows enthusiasm running well ahead of execution capacity, an imbalance increasingly visible as trade tensions reshape supply and production networks.
The push toward AI is partly defensive. As tariff rounds and export controls stretch into a multi-year cycle, manufacturers, retailers, and logistics networks are pursuing automation and intelligent planning to offset rising costs and supply constraints. But the study suggests the majority are still in early stages of adoption, building proofs of concept and automating isolated workflows rather than embedding real-time decisioning across planning, sourcing, fulfillment, and finance.
AI Pilots Surge, But Real-Time Decisioning Still Rare
According to the report, 71% of global companies accelerated AI deployment in direct response to trade and geopolitical shocks. Nearly all respondents, 97%, are testing AI in some form. But only 20% say they can make real-time decisions using AI, and only 22% have a defined enterprise AI strategy. Those with a strategy are more than three times more likely to report measurable returns.
Predictive analytics remains the most mature area, with 52% reporting full integration. Far fewer have pushed into risk domains where AI could meaningfully change resilience: fewer than 15% use AI for supplier monitoring, anomaly detection, or geopolitical tracking. This gap underscores how many companies are using AI to optimize steady-state operations rather than mitigate volatility at the core of today’s trade environment.
Internal alignment is also uneven. While two-thirds of C-suite leaders expect AI to deliver returns within 12 months, fewer than half of junior leaders share that view, a sign that execution demands on the ground are outpacing boardroom optimism.
Regional Divergence in AI Momentum
Regional patterns highlight differences in regulatory environments and risk appetite. Executives in Asia-Pacific (81%) and Europe (78%) report faster acceleration than those in North America (57%). European and Asia-Pacific respondents also report stronger investment momentum, 38% and 31% respectively, compared with 22% in North America.
Even in the fastest-moving markets, adoption depth remains limited. Only 11% of respondents are using AI for scenario modeling, and just 3% for geopolitical tracking, capabilities increasingly expected as organizations diversify suppliers and redesign networks for resilience. Meanwhile, 79% of companies have already passed higher costs to consumers, and more than three-quarters report worsening availability of key components, reinforcing the urgency to shift from experimentation to execution.
Notably, fewer than one in four business leaders expect AI-related risks to rise over the next three years. That confidence contrasts with emerging public-policy scrutiny around model governance and data security. Recent trade press and regulatory reports suggest upcoming compliance requirements, including transparency on AI-driven decisions affecting supply continuity and pricing, that could increase operational complexity for manufacturers and global logistics providers.
Where Competitive Advantage Quietly Shifts Next
As companies scale beyond pilots, advantage may depend on how quickly they shorten the distance between signal and response. Recent earnings calls across semiconductors, automotive, and consumer goods show a similar pattern: firms making headway are not the ones emphasizing AI strategy, but those embedding algorithms into weekly production planning, supplier resets, and multi-node inventory decisions. With tariff cycles persisting and cost-pass-through limits becoming clearer, organizations that treat AI as an operating rhythm, not a feature, will be positioned to convert geopolitical turbulence into tighter working-capital control and more responsive capacity deployment.
