AI-Native Supply Chain
Planning: What It Really Means
Beyond chatbots, dashboards, and bolted-on AI
Webinar starts in
Most "AI in Planning" Is
Not Actually AI-Native
There is a significant difference between AI bolted onto a legacy planning tool and intelligence that is woven into how decisions get made. Most organisations are still on the wrong side of that line.
AI as a reporting layer
Dashboards and charts generated by AI but disconnected from the planning workflow itself.
Chatbots as "AI planning"
Generic copilots that can answer questions but cannot surface what changed, why, or what to do next.
Static forecasts, slow exceptions
Planners spending hours chasing exceptions that AI could have already ranked, explained, and prioritised.
What AI-native actually means
Intelligence embedded in the workflow: surfacing what changed, explaining why, prioritising what matters, and recommending what to do next.
What You Will Walk Away With
Practical, grounded insights from two practitioners who have built and deployed AI planning systems, not consultants theorising about them.
What AI-Native Planning Actually Means
A clear definition separating genuine AI-native systems from AI add-ons. Why the distinction matters for your technology decisions and your team.
The Five Ways AI Should Be Embedded in Planning
Forecasting, confidence scoring, exception prioritisation, root-cause surfacing, and decision support. Each one explained with real examples.
Automating Friction, Not Judgement
Why the goal is not to replace planners but to remove the low-value friction that prevents them from making better decisions faster.
The Talent and Skills Shift This Demands
What supply chain planners, S&OP managers, and directors need to learn, unlearn, and develop to thrive alongside AI-native planning tools.
Evaluating AI Planning Tools: Questions to Ask
A practical framework for assessing whether a vendor is truly AI-native or using the term loosely. What to look for and what to probe.
Your Starting Point: What to Do This Week
Concrete next steps whether you are evaluating tools, upskilling your team, or redesigning your planning process around AI capabilities.
Built For These Roles
If you sit at the intersection of supply chain planning, technology decisions, or team capability, this session is for you.
Supply Chain Directors
Leading planning transformations and needing a clear view of what AI-native means for your function's operating model.
S&OP / IBP Managers
Running consensus planning cycles and looking to reduce ambiguity, speed up exception handling, and improve decision quality.
Demand & Supply Planners
Working daily with forecasts, exceptions, and data. You will see directly how AI-native systems change your day-to-day work.
Inventory & Procurement Leaders
Optimising stock positions and sourcing decisions, and wanting to understand how AI can improve the signals you act on.
Digital & Transformation Leads
Evaluating planning technology investments and needing a rigorous framework for separating genuine AI capability from marketing.
SCM Professionals Upskilling
Ambitious planners and analysts building future-ready skills and wanting to understand where AI is taking the profession.
One Hour. Zero Padding.
A focused, practitioner-led session structured to give you maximum insight in minimum time.
Welcome & Context Setting
Introductions, framing the problem, and the opening provocation on what "AI planning" usually means versus what it should mean.
Defining AI-Native Planning
A precise definition. The five functions where AI must be embedded, not bolted on. Why generic copilots fall short.
AI in Practice: Forecasting, Exceptions & Decisions
How AI generates forecasts with confidence scores, surfaces exceptions ranked by impact, identifies root causes, and presents decision options. Live examples from Plantryx.
The Planner's New Role: Automating Friction
What changes for planners when AI removes ambiguity. The talent and skills shift this demands. How SCMDOJO is preparing supply chain teams for this transition.
Evaluating AI Planning Tools: The Right Questions
A practical checklist for supply chain leaders. How to tell an AI-native system from a dressed-up legacy tool.
Live Q&A — 25 Minutes
Open questions to both speakers on AI-native planning, technology selection, team upskilling, and anything else on your mind.
Six Reasons to Show Up
This is a practitioner conversation, not a vendor pitch. No slides with stock-photo robots. Just real insight from people who build and run AI planning systems.
Two Practitioners, Not Theorists
Dr. Ahmed brings 12 years of operational supply chain experience. Majd Kharfan brings hands-on AI planning system development. Both speak from what they have built and seen.
A Precise Definition You Can Use
Leave with a clear, working definition of AI-native planning that helps you evaluate vendors, brief your team, and make better technology decisions.
Grounded in Real Planning Problems
Every point is anchored in forecasting, exception management, S&OP, and inventory decisions. No generic AI talk.
25 Minutes of Direct Q&A
Both speakers available for your questions. Bring your real planning challenges and technology questions.
Talent and Upskilling Perspective
Understand what this means for your team's roles, skills, and how to prepare planners to work alongside AI-native tools.
Free, with No Sales Pitch
This is a knowledge session. No upselling during the webinar, no obligatory product demo. Just a useful hour for supply chain professionals.
"AI should reduce planner ambiguity, not just generate more output. The goal is to automate friction, not judgement."
Majd Kharfan, Co-Founder, Plantryx
Two Practitioners Who Build the Future of Planning
One of the world's most followed supply chain voices with a community of 300,000+ practitioners. Founder of SCMDOJO, the world's largest independent supply chain learning platform, serving clients including LEGO, Novartis, JLR, and LVMH. Formerly 12 years at Eaton Corporation managing S&OP, procurement, and logistics for a $700M division. Ph.D. from Lancaster University, Visiting Professor at Heriot-Watt and Aston Universities.
A supply chain, product, and data science leader focused on rethinking how companies plan. His background spans demand planning, inventory optimisation, S&OP, advanced analytics, and machine learning across retail, CPG, and supply chain environments. Particularly passionate about building AI-native planning systems that help teams make better forecasting, inventory, and supply decisions — moving beyond spreadsheet-heavy processes toward a more intelligent and adaptive way of operating.
Register Now.
It Is Free.
Wednesday, 6 May 2026 · 9:00 AM CT / 3:00 PM UK · Online · 1 Hour
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