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EPISODE · Mar 9, 2026 · 21 MIN
[ROUNDUP] Scaling AI in Global Enterprises: Live Trade Compliance Conversations
from Simply Trade · host Global Training Center
Host: Annik Sobing Guests: Jennifer Varney (Volvo Group), Penny Chen (PAX) Recorded at: ICPA Conference, San Antonio, TX Published: March 2026 Length: ~25 minutes Presented by: Global Training Center AI Meets Trade Compliance: From Auto Supply Chains to AI Live from ICPA San Antonio, Annik sits down with Jennifer from Volvo Group and Penny from PAX for an all‑women, International Women’s Day‑timed conversation about how AI is actually being used in trade compliance today—far beyond the buzzwords. They explore the reality of AI inside a massively complex automotive supply chain, how duty drawback is being reimagined with AI, and what trade teams should think about before buying or building any tools. What You’ll Learn in This Episode Session highlights from ICPA Jennifer: Practical implementation of AI to support customs clearance at the enterprise level—how one company uses AI to survive an “ever‑changing and incredibly volatile” trade landscape. Penny: A “beginner‑friendly” intro to general AI tools, how large language models work, and how trade compliance leaders can evaluate AI quality and fit. The automotive reality: 1,000+ policy changes and thousands of parts In just the last year, there have been 1,000+ trade policy changes worldwide, affecting about 5 trillion dollars in spend. Most of the real impact comes from trade barrier changes, not facilitation measures. A single vehicle can have 2,000–3,000 parts sourced from thousands of suppliers globally, some in‑house, some external. New demands around Section 232 (steel/aluminum/copper), forced labor, EUDR, connected vehicle rules, dual‑use, etc. mean OEMs must know their supply base down to raw material origin and processing, sometimes 5–6 tiers deep. Why human-only workflows can’t keep up Many tier‑1 suppliers don’t even have the data OEMs now must report, or consider it proprietary. Trade teams are drowning in documentation, entry creation, and ever‑changing regulatory demands—falling behind risks blocked shipments and massive cost. Jennifer’s view: AI is less about replacing people and more about augmenting limited resources before they’re “buried under all of the legislative changes.” Where AI fits in (and where it doesn’t) Example use case: consolidating multiple documents (PO, invoice, BL, shipping manifest) to build a single 7501—AI reads different formats, extracts the right fields, and populates data so humans review instead of retyping. Penny’s rule of thumb: if it’s a task you’d happily delegate to an intern, it’s a candidate for automation or semi‑automation. AI frees people to focus on high‑value work: audits, wider coverage (5% → 99%), forecasting regulatory changes, and adjusting systems/processes for what’s coming next. Starting your AI journey: practical adoption path Step 1: Use free or existing tools (e.g., Microsoft Copilot) for summaries, data cleaning, and simple tasks. Step 2: When needs get more complex, consider specialized AI tools (like PAX’s AI‑powered duty drawback service), but pair them with solid ROI analysis: cost vs. time savings vs. recovered dollars. Step 3: For large enterprises, begin with defining pain points and a data strategy: Where do you spend the most time? Which activity is eating 90% of your bandwidth? What data will go into AI, and what exactly do you want back out? Overcoming fear and building buy‑in Penny’s take: curiosity is your best ally—if you don’t know how to use AI, start by asking AI how to use AI. Jennifer’s advice: Engage stakeholders early; give them a voice in how the tool is designed and used. Set realistic expectations—even with aggressive automation, maybe only ~30% of workload can be automated today. Focus human effort on strategy and change management, not repetitive admin. Choosing the “right” AI for your team Not every company needs every AI—e.g., if you classify one item a month, a classification platform may not be worth it. For trade leaders, tool selection should be guided by: Where you lose the most time or money. Data type mix (text + structured data). Compliance/guardrail needs and vendor transparency about models and controls. Conferences like ICPA are key: they surface real use cases, connect trade and tech experts, and help teams refine what they actually need. International Women’s Day Spotlight This episode also celebrates International Women’s Day and highlights women leading in trade, tech, and compliance—from OEMs to AI startups. Annik closes with a shoutout to all women in trade who are building, leading, and pushing the industry forward. Credits Host: Annik Sobing Guests: Jennifer (Volvo Group), Penny (PAX) Recorded at: ICPA Conference, San Antonio, TX Listen & Subscribe Simply Trade main page: https://simplytrade.podbean.com Apple Podcasts: https://podcasts.apple.com/us/podcast/simply-trade/id1640329690 Spotify: https://open.spotify.com/show/09m199JO6fuNumbcrHTkGq Amazon Music: https://music.amazon.com/podcasts/8de7d7fa-38e0-41b2-bad3-b8a3c5dc4cda/simply-trade Connect with Simply Trade Podcast page: https://www.globaltrainingcenter.com/simply-trade-podcast LinkedIn: https://www.linkedin.com/showcase/simply-trade-podcast YouTube: https://www.youtube.com/@SimplyTradePod Join the Trade Geeks Community Trade Geeks (by Global Training Center): https://globaltrainingcenter.com/trade-geeks/
What this episode covers
Host: Annik SobingGuests: Jennifer Varney (Volvo Group), Penny Chen (PAX)Recorded at: ICPA Conference, San Antonio, TXPublished: March 2026Length: ~25 minutesPresented by: Global Training Center AI Meets Trade Compliance: From Auto Supply Chains to AI Live from ICPA San Antonio, Annik sits down with Jennifer from Volvo Group and Penny from PAX for an all‑women, International Women’s Day‑timed conversation about how AI is actually being used in trade compliance today—far beyond the buzzwords. They explore the reality of AI inside a massively complex automotive supply chain, how duty drawback is being reimagined with AI, and what trade teams should think about before buying or building any tools. What You’ll Learn in This Episode Session highlights from ICPA Jennifer: Practical implementation of AI to support customs clearance at the enterprise level—how one company uses AI to survive an “ever‑changing and incredibly volatile” trade landscape. Penny: A “beginner‑friendly” intro to general AI tools, how large language models work, and how trade compliance leaders can evaluate AI quality and fit. The automotive reality: 1,000+ policy changes and thousands of parts In just the last year, there have been 1,000+ trade policy changes worldwide, affecting about 5 trillion dollars in spend. Most of the real impact comes from trade barrier changes, not facilitation measures. A single vehicle can have 2,000–3,000 parts sourced from thousands of suppliers globally, some in‑house, some external. New demands around Section 232 (steel/aluminum/copper), forced labor, EUDR, connected vehicle rules, dual‑use, etc. mean OEMs must know their supply base down to raw material origin and processing, sometimes 5–6 tiers deep. Why human-only workflows can’t keep up Many tier‑1 suppliers don’t even have the data OEMs now must report, or consider it proprietary. Trade teams are drowning in documentation, entry creation, and ever‑changing regulatory demands—falling behind risks blocked shipments and massive cost. Jennifer’s view: AI is less about replacing people and more about augmenting limited resources before they’re “buried under all of the legislative changes.” Where AI fits in (and where it doesn’t) Example use case: consolidating multiple documents (PO, invoice, BL, shipping manifest) to build a single 7501—AI reads different formats, extracts the right fields, and populates data so humans review instead of retyping. Penny’s rule of thumb: if it’s a task you’d happily delegate to an intern, it’s a candidate for automation or semi‑automation. AI frees people to focus on high‑value work: audits, wider coverage (5% → 99%), forecasting regulatory changes, and adjusting systems/processes for what’s coming next. Starting your AI journey: practical adoption path Step 1: Use free or existing tools (e.g., Microsoft Copilot) for summaries, data cleaning, and simple tasks. Step 2: When needs get more complex, consider specialized AI tools (like PAX’s AI‑powered duty drawback service), but pair them with solid ROI analysis: cost vs. time savings vs. recovered dollars. Step 3: For large enterprises, begin with defining pain points and a data strategy: Where do you spend the most time? Which activity is eating 90% of your bandwidth? What data will go into AI, and what exactly do you want back out? Overcoming fear and building buy‑in Penny’s take: curiosity is your best ally—if you don’t know how to use AI, start by asking AI how to use AI. Jennifer’s advice: Engage stakeholders early; give them a voice in how the tool is designed and used. Set realistic expectations—even with aggressive automation, maybe only ~30% of workload can be automated today. Focus human effort on strategy and change management, not repetitive admin. Choosing the “right” AI for your team Not every company needs every AI—e.g., if you classify one item a month, a classification platform may not
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[ROUNDUP] Scaling AI in Global Enterprises: Live Trade Compliance Conversations
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