A Delay in Taiwan Shouldn't Become a Missed Commitment in California.
The most expensive decisions in AMD’s supply chain are triggered by data your systems don’t control.
AMD is shipping MI450 GPUs to OpenAI and Meta starting H2 2026. The production, procurement, and fulfillment decisions behind those commitments depend on signals from external partners. Those signals should trigger automated actions. Today, they trigger emails and manual work.
See What This Looks Like for AMD
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EPYC Scale Needs EPYC Intelligence
Challenge 1
TSMC shipped. Your production planning team is still waiting on confirmation.
The data your planning team needs to make production decisions originates outside AMD, across dozens of external partners. It arrives through emails and manual updates, and by the time it shows up, your team has already made production decisions on estimates. When it flows automatically, those estimates become confirmed supply data.
Challenge 2
OpenAI asks where their hardware is. Your team starts digging.
When a customer needs order status, someone on your team searches across partner systems to piece the answer together manually. While they dig, the customer waits. The data that would power an automated response already exists across your external partners. It’s just not connected yet.
Challenge 3
Export controls changed overnight. Your team spent days tracing what was already in transit.
When the U.S. tightened export licensing on the MI308 in April 2025, AMD had inventory in production, commitments signed, and components in motion across multiple partners. The financial exposure reached $800M, and your team traced it manually across partner systems for days. With that data aggregated in real time, the same assessment takes minutes.
Challenge 4
More MI450 orders. Same team.
Right now, your team is the automation layer. Every order AMD fulfills generates coordination across external partners, from supplier confirmations and exception handling to status updates and schedule adjustments. Your team processes all of it manually. As MI450 volume ramps for OpenAI and Meta, that coordination multiplies while your team stays the same size.
From Signals to Decisions
The Automations AMD Can’t Build from Internal Data Alone
Auto-Adjust
A Component Delay at TSMC Automatically Adjusts Your Production Schedule.
When a component is delayed, your production schedule adjusts automatically. The system flags affected production runs, recalculates lead times, and surfaces at-risk POs to procurement. Every step runs on confirmed data from your external partners, flowing into your planning and ERP systems in real time.
A comparable global electronics distributor already runs this way across thousands of suppliers. Part-number ETAs accurate to the hour feed directly into their ERP planning engine, and manual supplier coordination dropped 70%.
Sam, the AI agent for supplier operations, onboards new suppliers in days and handles routine PO status requests. Your procurement team focuses on sourcing decisions.
Results from a comparable global electronics distributor:
- 70% reduction in manual supplier coordination
- 1% inventory reduction through better inbound data
- 60% fewer expedited shipments
- 20% lower safety stock
Answered Before Asked
OpenAI Logs In and Sees Exactly Where Their Hardware Is.
A signal changes, a notification fires, and the customer sees their order status in real time. No one on your team had to look anything up. The answer updates as conditions change across every stage of fulfillment. Delays surface proactively, so the customer adjusts their buildout schedule early. When they do reach out with a question, an AI agent handles it with a verified answer, 24/7.
Coca-Cola runs this way today, with response times dropping from 90 minutes to seconds. Kimberly-Clark saw a 90% reduction in status-related email volume, and Veritiv posted double-digit NPS increases for two consecutive years.
Cassie, the AI agent for customer operations, powers the automated notifications and handles routine inquiries.
Results from companies running automated customer operations:
- Response times from 90 minutes to seconds (Coca-Cola)
- 90% reduction in status-related email volume (Kimberly-Clark)
- Double-digit NPS increases for two consecutive years (Veritiv)
- 1-minute average response time post-implementation (Ingredion)
Flagged in Minutes
A Rule Changes. Every Affected Order Is Flagged in Minutes.
When a regulation shifts or a disruption hits, Polly, the AI agent for exception management, assesses your entire partner network automatically. Affected orders are flagged and the right people are notified within minutes. That speed is possible because the same external signals your team uses for daily procurement and production are already structured and connected. The MI308 export licensing event and its $800M exposure is exactly the kind of scenario where minutes matter.
Results from automated monitoring across global manufacturing networks:
- Eliminated almost all of $2.69M in annual costs (Trane Technologies)
- Real-time disruption detection across 200+ countries (FourKites network)
- Minutes to full network assessment
- 98.6% cost reduction at target sites (Trane Technologies)
Scale Without Headcount
Volume Scales. Your Team Doesn’t Have To.
Supplier confirmations, exception handling, status updates, and schedule adjustments run automatically around the clock. Tracy, the AI agent for supply chain coordination, monitors every order and handles exception workflows on live partner signals. Sam automates supplier onboarding and PO status workflows. Your team sets the rules. The agents execute them and escalate only when judgment is required.
Bridgestone Americas deployed this approach and eliminated all manual email coordination with their supply chain partners. First Solar went from hours of daily coordination to zero manual processes across global manufacturing, with Tracy running at 99.7% AI execution accuracy. Church & Dwight saves 25 hours per week on automated responses alone.
Because the automations run on external partner signals, they absorb volume increases without additional headcount. As AMD’s MI450 ramp accelerates, the coordination capacity grows with it.
Results from manufacturers running AI-powered supply chain coordination:
- 99.7% AI execution accuracy (First Solar)
- Zero manual email coordination with partners post-deployment (Bridgestone Americas)
- Hundreds of hours returned to associates annually (Coca-Cola)
- 25 hours per week saved on automated responses (Church & Dwight)
Companies Running This Way Today
Global Electronics Distributor
One of the world’s largest electronics distributors runs $28B in annual revenue across thousands of semiconductor suppliers. Most of their inbound supply moves on supplier-controlled shipments, which means the procurement and planning teams depend on data they don’t generate. Before FourKites, those teams spent hours per supplier piecing together supply data from emails, spreadsheets, and commercial invoices. Today, FourKites captures all of it automatically, matches it against the company’s purchase order backlog, and produces part-number-level ETAs accurate to the hour. Those ETAs feed directly into their ERP planning engine, automating procurement decisions and enabling more confident customer commitments.
“Having a dynamic ETA that is accurate at the hour level… the system is making better decisions that will ultimately reduce cost, increase customer satisfaction and on-time delivery.”
— Director of Global Transportation and Trade Operations
The external signals this distributor automated are the same kind sitting between TSMC and AMD’s production schedules today.
First Solar
First Solar’s manufacturing output grew 12x, and they needed automations that scaled without adding new teams. FourKites provided the external data infrastructure across 100,000 annual truckloads and facilities spanning the US, India, Vietnam, and Malaysia. Manual coordination processes were replaced by automated workflows running at 99.7% AI execution accuracy.
“We’ve fundamentally shifted from reactive to proactive operations across our global manufacturing network, eliminating manual email processes. FourKites also accelerated our cash flow through automatic invoice generation upon delivery.”
— Justin Carder, Lead, Logistics Operations, First Solar
AMD’s team is absorbing MI450 ramp volume on the same timeline.
The Coca-Cola Company
Coca-Cola’s customer operations team was fielding manual order status inquiries with a 90-minute response SLA, and the volume was overwhelming the workforce. FourKites AI agents Tracy and Cassie now automate those inquiry responses, proactively identify data quality issues, and handle routine customer questions at a scale no human team could match. Response times dropped from 90 minutes to seconds, returning hundreds of hours to associates annually while running customer service 24/7 without adding headcount.
“FourKites AI Agent Tracy positions us ahead of the curve as we prepare for a future where customers expect increased and differentiated service capabilities.”
— Patrick McManus, Senior Director Customer Operations, The Coca-Cola Company
When OpenAI or Meta asks AMD where their hardware is, this is what the automated answer looks like.
Trane Technologies
Trane Technologies runs a global manufacturing network moving 150,000 annual shipments across a complex supplier and distribution base. Their team connected real-time partner signals across their supply chain and automated the identification of at-risk situations before deadlines passed. At two sites alone, they eliminated almost all of $2.69M in annual costs through automated monitoring and proactive response. They’ve since applied the same approach across additional facilities.
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AMD Has the Supply Chain Expertise. FourKites Has the External Data Network. Let's Build the Automations.
Every challenge on this page has a common root: data that originates outside AMD, across external partners, that your systems don't capture automatically today. One conversation about what changes when they do.