AI for Operations & Supply Chain

Course Duration: Two Days

Duration (Hrs) 10 Hours/Hours

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Programme Overview

A two-day programme for operations, manufacturing and supply-chain professionals, covering how AI is transforming planning, procurement, production, logistics and distribution. It addresses demand forecasting, production planning, quality control, supplier risk and end-to-end supply-chain visibility with AI. The hands-on work uses anonymised operational data and realistic planning, forecasting and execution scenarios. The programme suits manufacturing, retail, energy, government logistics and industrial operations.

Learning Objectives

By the end of this programme, participants will be able to:

  • Describe how AI is reshaping operations and supply-chain functions across planning, execution and optimisation.
  • Use AI tools for demand forecasting, inventory optimisation, supplier analysis and operational reporting.
  • Apply AI to production planning, quality control and logistics optimisation.
  • Evaluate AI-based supply-chain and operations vendors for technical fit, data handling and sovereignty.
  • Recognise operations-specific AI risks, including over-reliance on forecasting, cascading effects and single points of failure.
  • Apply SDAIA, the PDPL and sector requirements to AI use in operations.

Programme Content & Modules

Day 1 : The operations landscape and AI in practice
Module1: AI and the Modern Operations Function

How AI is reshaping operations, manufacturing and supply chains. Demand sensing, digital twins of operations, predictive maintenance and autonomous logistics. Where AI has matured in the sector and where it is still emerging. The Saudi industrial and supply-chain context.

Module2: AI Tools in Operations & Supply-Chain Practice

Practical work with AI tools for demand forecasting, inventory analysis, supplier assessment, production planning and operations reporting. Prompt engineering for operational accuracy. A tour of AI-enhanced ERP, SCM, MES and Sales & Operations Planning (S&OP) platforms.

Day 2: AI-supported operations and responsible practice
Module 3: AI-Supported Planning, Forecasting & Resilience

Using AI for scenario planning, resilience analysis and supply-risk assessment. Combining AI output with operational judgement. A group exercise on a realistic planning or disruption scenario supported by AI.

Module 4: Responsible AI in Operations

Governance of operational and supplier data. Cascade risk when AI drives multi-step operational decisions. Transparency of suppliers’ AI. Alignment with SDAIA and sector regulation. Data-sovereignty considerations for critical supply chains. Applied capstone project: each participant designs an AI-adoption plan for one of their operations.

Suggested Duration

Two training days.

Target Audience & Prerequisites

Target audience: Operations managers, production planners, supply-chain planners, procurement specialists, logistics managers, warehouse and distribution leads, manufacturing engineers and members of S&OP teams in manufacturing, energy, retail, government and industrial logistics.

Prerequisites: Practical experience in operations or supply chain. Basic spreadsheet literacy. No prior background in AI or programming is required. A laptop is required for the hands-on sessions.

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