Who is AI training for supply chain professionals designed for?

Demand planners, supply planners, S&OP/IBP leads, planning managers, supply chain directors, and inventory or capacity planning teams attend most often. We plan the cohort with you, so the signal packs and scenarios used in class match the products and channels your team plans.

How is this different from procurement or logistics training?

This program covers demand, supply, inventory, and capacity planning, S&OP/IBP, and resilience, the flow-balancing work planners own. Procurement's sourcing, RFx, and category work sit in a separate program, and freight execution, customs, and shipment communication sit in our logistics program. The buyers and the daily work differ enough to keep the three apart.

Does the training cover forecasting-model tuning or inventory optimization?

Building or tuning a forecasting model is a data-science and software project. This course covers the drafting, synthesis, and communication work around your planning cycle, and stays explicit about where those systems fit.

How many hours, and over how many days?

Two days, roughly 13 hours, cover the core program, and the calendar decides whether that happens onsite or as live online sessions. Most planning teams split that time into half-day blocks timed around their monthly cycle, so the calendar keeps moving.

Can the syllabus use our own planning templates and calendar?

Yes. A short discovery call covers your S&OP/IBP calendar plus your pre-read and scenario templates. Sanitized signal inputs shape the exercises. We use what we learn to adapt every exercise to your calendar. The cases in the room end up looking like your actual Monday morning.

How do you quote this?

Group size, delivery format, customization depth, and location set the number, so describe your planning team and cycle for a plan built around your program rather than a fixed package.

What do participants keep after the training?

Participants keep the signal-pack, scenario, S&OP pre-read, and disruption-brief templates built during the sessions, plus the 90-day rollout plan. A follow-up or advanced session can be booked later as the team's usage matures.

How is sensitive commercial data handled during the training?

The figures were built for the course, or fully anonymized where an exercise came from a real dataset. One module covers classification directly: supplier prices, cost structures, and demand data, which tools may hold them, and what KVKK and GDPR require. The verify-before-you-decide habit runs through every exercise in the program.

AI Training · Supply Chain

AI Training for Supply Chain Professionals

Every planning cycle starts the same way: sales numbers, order and POS extracts, supplier updates, and market notes, all landing in different formats from different systems, with a deadline that doesn't move. Reconciling that mess usually eats the time a planner should be spending on what the numbers actually mean.

This program teaches demand, supply, and S&OP/IBP planners to turn that scatter into a decision-ready pack, stress-test scenarios, and write a disruption brief fast when something breaks. The forecast call and the plan stay exactly where they belong: with the planner.

modules: 6
hours: 12

Some of the 500+ brands we've worked with

Selected brands we’ve worked with across industries.

See all references

Monday morning starts with the exception list: three SKUs short, a supplier that missed a ship date, a demand spike nobody forecasted, and a pre-read due before the S&OP call at eleven. The planner assembling it pulls numbers from four systems that don't talk to each other, and by the time the numbers are clean there's no time left to think about what they mean. Get the pre-read wrong and the room defends a plan built on a bad number, then blames the planner two months later when the stockout shows up. AI can turn that scattered pile into a source-traceable draft fast, but only if the planner knows exactly what to check before a number enters the plan.

AI training for supply chain professionals turns those same scattered signals into a traceable pre-read, stress-tested scenarios, and an S&OP/IBP narrative — the forecast call and trade-off stay with the planner. Procurement's sourcing work and logistics' freight execution sit in separate programs, with the full set under AI training.

The exception list won't wait for the pre-read to be ready

Sales, order, supplier, and market data land from different systems in different formats — AI folds the mess into one traceable pack.

A generated summary nobody has challenged is worse than none

AI works as a sparring partner here — surfacing outliers and contradictions before a number reaches the room.

Building the deck can eat more of the cycle than the planning does

Building the pre-read often eats more hours than the planning itself — AI drafts faster, the planner still owns what it means.

A supplier miss needs a brief in minutes

A supplier miss needs a fast, clear escalation note — teams that draft these consistently recover faster and keep downstream trust.

The planner's tools already include an AI copilot

Copilots already sit inside the ERP and APS — the missing piece is knowing what to hand them and how to verify what comes back.

01
Where generative AI helps a planning cycle, and where it doesn't
90 minBeginner
What large language models do well inside a planning cycle, and where they distort a forecast or a supplier update. The module is also explicit about what this training deliberately skips.
What large language models can and cannot do inside a planning cycle
Planning versus prediction: what this course does not touch
Recognizing hallucinated numbers and false confidence in a generated narrative
What your ERP or APS exports need before AI can use them
Choosing safe first pilots
02
Demand and supply signal synthesis
120 minIntermediate
Turn scattered sales, order, supplier, and market inputs into one structured, source-traceable pre-read. Practiced so every generated line stays linked back to where the number came from.
Sales, order, and POS extracts, pulled into one structured signal pack
Summarizing supplier and capacity updates without losing the source
Flagging outliers and inconsistent inputs before they reach the forecast review
Market and customer-intelligence notes drafted with clear provenance
A repeatable signal-pack template built for every planning cycle
Keeping planner judgment ahead of any generated summary
03
Planning and scenario narratives
150 minIntermediate
AI drafts and stress-tests demand, supply, capacity, and inventory scenarios, and writes the sensitivity narrative that goes with them. The model challenges assumptions. It does not choose the plan.
Demand, supply, and capacity scenarios, structured for a planning review
Inventory trade-off narratives, service level versus working capital
Writing the base case, then its upside and downside
Using AI as a challenge partner to pressure-test planner assumptions
Comparing scenario outputs without letting AI select the plan
What this is not: an optimization engine for inventory or for network and routing
04
S&OP/IBP decision packs
150 minIntermediate
From agenda to executive narrative to a tracked action list, the full arc of a monthly demand, supply, and reconciliation review, rebuilt with a human sign-off at every step.
The pre-read and agenda, prepared for demand, supply, and reconciliation reviews
Consensus gaps between sales, planning, and finance numbers, caught early
The executive S&OP/IBP narrative, drafted from agreed inputs
Turning decisions into tracked actions with named owners
Plan changes, version-controlled monthly
Same numbers, different audiences
05
Exceptions and resilience playbooks
120 minAdvanced
Disruption briefs, handoffs, and escalation notes, rebuilt as AI-assisted drafting flows, so a supplier miss or capacity shortfall gets a fast, consistent response instead of an improvised one.
A disruption brief drafted the moment a shortfall or delay is flagged
Handoff notes for suppliers and plants, with a clear ask for logistics
Escalation templates that match severity to the right decision-maker
Building a reusable playbook library for recurring disruption types
Capturing after-action learning so playbooks improve each cycle
06
Governance and rollout within clear data boundaries
90 minIntermediate
What counts as sensitive commercial data in a planning context, a verify-before-you-decide discipline for every AI-assisted number, and a 90-day rollout plan built around your actual planning calendar.
Supplier prices and costs, including the demand data behind them
The difference between a consumer AI login and an enterprise one, for planning data
A verify-before-you-decide discipline
A pilot chosen for a measurable planning-cycle time saving
Metrics that track whether planners actually changed their week
A 90-day plan for turning the pilot into standard practice

What you will learn

Build a source-traceable signal pack
Draft and stress-test planning scenarios, with the reasoning made explicit
Prepare the S&OP/IBP pre-read and executive narrative, then track decisions with named owners
A fast, consistent brief the moment a supplier misses
Verify before every decision
Handle supplier prices, costs, demand data, kept confidential under KVKK/GDPR rules
Choose safe first use cases, forecasting and optimization claims left to specialists
Leave with a 90-day rollout plan, backed by pilot metrics

Who should attend

Demand planners and supply planners
S&OP/IBP leads and planning managers
Supply chain directors and heads of planning
Inventory and capacity planning teams
Operations excellence and continuous-improvement teams

Most planning teams time the two days to their own S&OP or demand-review calendar, so the exercises run on a live cycle instead of a made-up case. The syllabus is identical whether you run it onsite or live online.

Format: Onsite or live online
Duration: 2 days (about 13 hours, can be split into half-day sessions around your planning calendar)
Group size: Up to 20 participants per group
Language: English or Turkish
Materials: Signal-pack, scenario, S&OP pre-read, and disruption-brief templates
Certificate: Certificate of completion

AI for Procurement Teams6 modules · 12 hoursA category manager's week runs on RFx drafts and bid comparisons that eat hours before a single negotiation starts. This program turns that paperwork into a faster, disciplined workflow, while sourcing decisions stay with the buyer.View training

AI in Logistics6 modules · 13 hoursFreight forwarders, carriers, and 3PLs run their day on shipment notices and customs paperwork, most of it written under a deadline. This program trains your teams to draft and check that text with AI, on your own workflows.View training

Using AI in Business Operations6 modules · 12 hoursAI training for business operations and shared-services teams, built around the SOPs, exception queues, and status reports that already fill their week, with sign-off and escalation staying exactly where they are today.View training

AI Automation with n8n6 modules · 13 hoursAI automation training for ops and marketing teams: build, test, and govern workflows with n8n, keep a person in the loop where it matters, and hold clear data boundaries throughout.View training

Whether it's a monthly S&OP cycle, a weekly demand review, or a resilience playbook you don't have yet, describe your planning cadence and we'll fit the modules, the templates, and the pilot to it.

Two colleagues handing over a reviewed work item between their role stations

Who is AI training for supply chain professionals designed for?
Demand planners, supply planners, S&OP/IBP leads, planning managers, supply chain directors, and inventory or capacity planning teams attend most often. We plan the cohort with you, so the signal packs and scenarios used in class match the products and channels your team plans.
How is this different from procurement or logistics training?
This program covers demand, supply, inventory, and capacity planning, S&OP/IBP, and resilience, the flow-balancing work planners own. Procurement's sourcing, RFx, and category work sit in a separate program, and freight execution, customs, and shipment communication sit in our logistics program. The buyers and the daily work differ enough to keep the three apart.
Does the training cover forecasting-model tuning or inventory optimization?
Building or tuning a forecasting model is a data-science and software project. This course covers the drafting, synthesis, and communication work around your planning cycle, and stays explicit about where those systems fit.
How many hours, and over how many days?
Two days, roughly 13 hours, cover the core program, and the calendar decides whether that happens onsite or as live online sessions. Most planning teams split that time into half-day blocks timed around their monthly cycle, so the calendar keeps moving.
Can the syllabus use our own planning templates and calendar?
Yes. A short discovery call covers your S&OP/IBP calendar plus your pre-read and scenario templates. Sanitized signal inputs shape the exercises. We use what we learn to adapt every exercise to your calendar. The cases in the room end up looking like your actual Monday morning.
How do you quote this?
Group size, delivery format, customization depth, and location set the number, so describe your planning team and cycle for a plan built around your program rather than a fixed package.
What do participants keep after the training?
Participants keep the signal-pack, scenario, S&OP pre-read, and disruption-brief templates built during the sessions, plus the 90-day rollout plan. A follow-up or advanced session can be booked later as the team's usage matures.
How is sensitive commercial data handled during the training?
The figures were built for the course, or fully anonymized where an exercise came from a real dataset. One module covers classification directly: supplier prices, cost structures, and demand data, which tools may hold them, and what KVKK and GDPR require. The verify-before-you-decide habit runs through every exercise in the program.

By team

By industry

By tool

AI Training for Supply Chain Professionals

Why AI for this team?

The exception list won't wait for the pre-read to be ready

A generated summary nobody has challenged is worse than none