Global AI-powered software spending is projected to reach US$299 billion by 2025, with developer teams expecting AI tools to generate 36% of all new code by 2026. In trade operations, forecasting use is tied to a median 10% improvement in forecast accuracy, while AI in ecommerce fraud detection can cut chargebacks by 25%. The biggest constraint remains risk and adoption, since fraud losses are forecast to reach US$7.7 trillion globally in 2024.
Key Takeaways
- US$12.1 billion AI software market size in 2023 (global)
- 36% of all new code created by employees is expected to be generated by AI tools by 2026 (worldwide, developer population)
- AI-powered software spending is projected to reach US$299 billion in 2025 globally
- 23% of respondents say their organization has deployed generative AI to customers (Gartner survey, 2024)
- 48% of organizations report using AI for fraud detection (survey, 2023)
- Organizations using AI for forecasting report a median 10% improvement in forecast accuracy (study)
- AI can reduce supply chain costs by 10%–20% according to estimates from peer-reviewed research review
- Retailers using machine learning for demand forecasting can reduce stockouts by 20% (study)
- The EU AI Act conformity assessment rules begin applying for certain prohibited AI practices on 2 February 2025 (timeline event)
- US NIST AI Risk Management Framework (AI RMF) is referenced by 300+ organizations and regulators globally (NIST ecosystem count)
- Global spending on digital trust and cyber risk management with AI is projected to exceed US$100 billion by 2026 (forecast)
- Forecasting and optimization initiatives are reported to deliver ROI of 10:1 to 20:1 in supply chain analytics (industry benchmark)
- AI fraud detection can lower chargebacks by 25% in ecommerce deployments (industry report)
- Inventory optimization using advanced analytics reduces working capital requirements by 5%–10% (study/benchmark)
AI adoption is accelerating in trade and operations, boosting productivity, forecasting accuracy, and cutting fraud and supply chain costs.
Related reading
01 · Category
Market Size10 stats
01
US$12.1 billion AI software market size in 2023 (global)
02
36% of all new code created by employees is expected to be generated by AI tools by 2026 (worldwide, developer population)
03
AI-powered software spending is projected to reach US$299 billion in 2025 globally
04
US$8.3 billion is the projected market size for conversational AI in 2024 (global)
05
US$25.2 billion is the projected market size for AI in manufacturing in 2024 (global)
06
AI in logistics market size is forecast to reach US$11.2 billion in 2024 (global)
07
AI in supply chain market size is forecast to reach US$8.7 billion in 2024 (global)
08
US$5.1 billion market size for AI in fraud detection is forecast for 2024 (global)
09
AI in energy utilities market size is forecast to reach US$4.9 billion in 2024 (global)
10
AI in retail market size is forecast to reach US$17.9 billion in 2024 (global)
Interpretation
Market Size Interpretation
In the Market Size view of AI in the trade industry, the figures point to rapid expansion with AI-powered software spending projected to reach US$299 billion in 2025 globally and multiple 2024 submarkets already hitting tens of billions, such as AI in retail at US$17.9 billion and AI in manufacturing at US$25.2 billion.
02 · Category
User Adoption2 stats
01
23% of respondents say their organization has deployed generative AI to customers (Gartner survey, 2024)
02
48% of organizations report using AI for fraud detection (survey, 2023)
Interpretation
User Adoption Interpretation
From a user adoption perspective, only 23% of organizations have deployed generative AI to customers, while 48% are using AI internally for fraud detection, suggesting adoption is still more advanced behind the scenes than in direct customer experiences.
03 · Category
Performance Metrics7 stats
01
Organizations using AI for forecasting report a median 10% improvement in forecast accuracy (study)
02
AI can reduce supply chain costs by 10%–20% according to estimates from peer-reviewed research review
03
Retailers using machine learning for demand forecasting can reduce stockouts by 20% (study)
04
AI-driven inventory optimization can reduce inventory carrying costs by 15% (study)
05
AI in healthcare and operations improves cycle time by 25% in workflow automation implementations (study)
06
Generative AI is estimated to increase worker productivity by 20% on average (McKinsey estimate)
07
AI adoption correlates with 5.3% higher operating margins for firms in manufacturing/retail sectors using AI (study)
Interpretation
Performance Metrics Interpretation
Across performance metrics, AI use in trade is delivering measurable gains such as 10% better forecast accuracy, 10% to 20% lower supply chain costs, and up to 20% fewer stockouts, showing that organizations are improving core operational outcomes rather than just experimenting.
More related reading
04 · Category
Industry Trends5 stats
01
The EU AI Act conformity assessment rules begin applying for certain prohibited AI practices on 2 February 2025 (timeline event)
02
US NIST AI Risk Management Framework (AI RMF) is referenced by 300+ organizations and regulators globally (NIST ecosystem count)
03
Global spending on digital trust and cyber risk management with AI is projected to exceed US$100 billion by 2026 (forecast)
04
Fraud losses are projected to reach US$7.7 trillion globally in 2024 (forecast)
05
Global trade value affected by shipping disruptions increased substantially during 2021–2022; 2023 disruptions persisted (trade press statistic)
Interpretation
Industry Trends Interpretation
For industry trends in AI in trade, the rapid regulatory and risk focus is becoming clear as the EU AI Act conformity rules start on 2 February 2025 alongside NIST AI RMF being cited by 300+ organizations, while spending on AI driven digital trust and cyber risk management is forecast to top US$100 billion by 2026.
05 · Category
Cost Analysis4 stats
01
Forecasting and optimization initiatives are reported to deliver ROI of 10:1 to 20:1 in supply chain analytics (industry benchmark)
02
AI fraud detection can lower chargebacks by 25% in ecommerce deployments (industry report)
03
Inventory optimization using advanced analytics reduces working capital requirements by 5%–10% (study/benchmark)
04
Predictive maintenance can reduce maintenance costs by 10%–40% (peer-reviewed review)
Interpretation
Cost Analysis Interpretation
Under cost analysis, AI is consistently proving its value with cost reductions like 25% fewer ecommerce chargebacks, 5% to 10% less working capital from inventory optimization, and maintenance costs dropping by 10% to 40% through predictive maintenance.
report visual · Comparison
AI market & application spending (global forecasts)
In the trade ecosystem, multiple vertical AI markets are forecast to reach double-digit billions by 2024–2025, with AI-powered software spending projected to be much larger.
AI-powered software spending (2025)$299 billion
AI in manufacturing market size (2024)$25.2 billion
AI in retail market size (2024)$17.9 billion
AI in logistics market size (2024)$11.2 billion
AI in supply chain market size (2024)$8.7 billion
source-verifiedgartner.com · fortunebusinessinsights.com2025
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Nathan Caldwell. (2026, February 13). AI In The Trade Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-trade-industry-statistics
MLA
Nathan Caldwell. "AI In The Trade Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-trade-industry-statistics.
Chicago
Nathan Caldwell. 2026. "AI In The Trade Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-trade-industry-statistics.
Sources & references
28 datasets cited across this report · attribution is report-level
+15 additional datasets cited (not shown individually)