Logistics and supply chain
AI and automation training for logistics and supply chain
Warehousing, distribution, transport and supply chain teams were automating before the current wave of AI arrived, which means the questions here are more mature and more operational. The training is about running these systems, specifying the next ones, and preparing the workforce that has to work alongside them.
For those who set expectations and review the output.
Built around logistics and supply chain work
3 courses · 20 facilitated hours
Preparing Your Team for Automation
The robot is the easy part. This course is for the managers whose people will work differently once it arrives: what to say and when, which roles change and how, and the skills plan that makes the change fair.
Addresses: Culture & Support, Confidence & Skills
Team Lead, Manager, Director / Head of
Course outlineSafety, Risk and Compliance for Robotic Workcells
The duties that sit with whoever runs the cell: risk assessment, guarding and interlocks, safe systems of work, and the records an inspector will ask to see. Delivered against your own site.
Addresses: Responsible Use, Culture & Support
Team Lead, Manager, Director / Head of
Course outlineSpecifying a Robotics Deployment
The document that decides whether a deployment succeeds is written before anyone quotes for it. Covers requirements, integrator selection, acceptance testing, and the clauses people wish they had insisted on.
Addresses: Tools & Access, Responsible Use
Manager, Director / Head of
Course outlineWhat this sector brings into the room
- The automation already exists and nobody owns it
- Sortation, conveyors, AMRs and goods-to-person systems bought over several years, with support arrangements that have quietly lapsed. The operational courses deal with running and troubleshooting what is already installed.
- Preparing people for what is coming
- Announcing automation badly costs more than the automation. The manager course covers what to say, when, and how to move people into the work that remains, without pretending nothing changes.
- Planning data that is not good enough to plan with
- Forecasting and analysis work starts from the state of the data, because a model built on a bad master file produces a confident answer that is wrong in an expensive direction.
Also runs for any sector
These work the same way whoever is in the room. They are still delivered on your own material, so they are no less specific to you - the sector simply is not what changes them.
Leading an AI-Ready Team
For the managers who decide whether adoption sticks. Focuses on setting expectations, removing blockers, and building the team habits that survive after the training ends.
Addresses: Culture & Support, Daily Practice
Team Lead, Manager, Director / Head of
Course outlineRunning an AI Champions Network
Champions programmes fail politely: volunteers are named, nothing changes. This is for the manager who owns the network - choosing the right people, giving them time and permission, and keeping it alive after month two.
Addresses: Culture & Support, Daily Practice
Team Lead, Manager, Director / Head of
Course outlineWhich of these does your organisation actually need?
The readiness assessment scores each person across five dimensions and maps the gaps onto this catalogue, by department and by role. Five minutes per person, and it answers the question with a measurement rather than a guess.