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Training and guidance
AI training and adoption guidance for Mary MacKillop Today
AI training and adoption guidance for an Australian not-for-profit, covering productivity opportunities, ethics and security guidance, staff guidelines and platform selection advice.
Workflow evidence
Screenshots from the systems and workflows.
These visuals come from the project portfolio and show the workflow, dashboard or training assets behind the case study.
Problem
The operational problem behind the work.
The organisation needed practical AI guidance that staff could understand and apply, while respecting the ethical, privacy and operational realities of the not-for-profit sector.
Approach
How the system was shaped.
01
Reviewed productivity opportunities for AI across relevant team workflows.
02
Delivered practical training and guidance for staff adoption.
03
Provided ethics and security guidance in plain English.
04
Supported platform selection advice and internal staff guideline development.
Architecture
Components that made the work production-minded.
Productivity opportunities review
Staff AI training and enablement
Ethics and security guidance
Platform selection advice
Internal guideline support for responsible adoption
Outcomes
What changed or became possible.
Practical AI adoption guidance for an Australian NFP
Staff training focused on safe and useful AI habits
Guidance for ethics, security and platform selection
Foundation for the Confident with AI for Not-for-Profits course direction
Responsible AI
Why governance is part of the implementation.
Training centred on responsible use rather than tool hype.
Guidance considered ethics, security and privacy-aware adoption.
Designed for non-technical staff who need confidence and clear boundaries.
Stack
Tools and platforms used.
AI TrainingNFP SectorResponsible AIGuidelinesPlatform Selection
Similar challenge?
Start by assessing the workflow, data and risk.
The AI Readiness Audit is the cleanest first step when you need to decide what to automate, what to avoid, and what should be governed before a production build.