Overview
Emergency management is under increasing pressure, more frequent natural disasters, more complex incidents, and rising expectations for faster, coordinated response. At the same time, agencies are sitting on more data than ever but often lack the capability to turn that data into timely, actionable decisions.
AI is starting to shift this.
Across ANZ in 2026:
- Many agencies are exploring or piloting AI for operational or planning use cases
- Public expectations for modernised, data-enabled emergency response are rising
- Investment is accelerating in simulation, digital twins, and predictive modelling to improve preparedness and coordination
But adoption is uneven.
Most agencies are still:
- Experimenting in pockets (e.g. reporting, mapping, admin tasks)
- Struggling with data quality, integration, and trust in AI outputs
- Unclear on how to safely apply AI in real operational decision-making
This program cuts through hype.
It focuses on how AI can actually support emergency management workflows from planning and preparedness through to response and recovery without compromising human judgement, safety, or accountability.
This is not a technical course.
It’s a practical, operations-focused program designed to help emergency management professionals:
- Use AI to enhance situational awareness and decision-making
- Reduce administrative burden and free up operational capacity
- Apply AI safely in high-risk, high-pressure environment
Who Should Attend?
Professionals directly involved in emergency preparedness, response and coordination, including: Police, Fire & Rescue, Ambulance and State Emergency Services (SES) | National and state emergency management agencies | Local councils with emergency management and disaster response responsibilities Also relevant for professionals supporting emergency management through planning, coordination and operational support functions, including: Environment and land management | Infrastructure, utilities and transport | Health services (e.g. ambulance, hospital operations, emergency planning) | Government coordination and recovery functions | Public information, media and stakeholder liaison roles (particularly those involved in crisis communication and real-time updates)
Incident Management Team (IMT) roles (e.g. Incident Controllers, Operations, Planning, Logistics)
Duty Officers / State Duty Officers
Operations Managers and Regional Commanders
Intelligence and Situational Awareness Analysts
Emergency management planners and resilience teams
Professionals supporting emergency management
Learning Outcomes
By the end of this course, you will be able to:
Identify high-value, low-risk AI use cases across emergency management
Apply AI to improve situational awareness, including data synthesis, intelligence summaries, and real-time inputs
Use AI to support resource allocation, risk assessment and scenario planning
Critically evaluate AI outputs understanding limitations, hallucinations, bias and reliability risks
Use structured prompting patterns for operational artefacts (sitrep, briefings, logs)
Align AI use to operational command structures, approvals, and information management requirements
Apply ethical, legal and operational guardrails, including privacy, accountability, and human-in-the-loop decision-making
Integrate AI into existing workflows, without disrupting operational command structures
Build a clear, practical action plan to trial AI within their team or function
Online Training
AI in Emergency Management: Decision Support for Preparedness, Response & Recovery
Session details
It’s a practical, operations-focused program designed to help emergency management professionals:
- Use AI to enhance situational awareness and decision-making
- Reduce administrative burden and free up operational capacity
- Apply AI safely in high-risk, high-pressure environment
Practical Takeaways
- A “safe use” checklist for operational teams (what you can/can’t do with AI during incidents)
- A prompt pack for emergency management (sitrep, briefing note, intel summary, stakeholder update)
- A lightweight evaluation rubric (accuracy, timeliness, bias risk, traceability, approval thresholds)
- A 30/60/90-day trial plan (use case, data inputs, guardrails, measures of success)
Some familiarity with topic is recommended
Key Sessions
1. AI now
What AI is, why capability has accelerated, and how machine learning, generative AI and frontier models fit together.
2. Applied AI in emergency management
Preparedness, planning, situational awareness, briefing, coordination, response, recovery and recurring administrative work.
3. Find the work worth improving
Identify the recurring grind and a larger consequential problem. Start where participants already know what good looks like.
4. Build a bounded workflow
Turn one use case into a repeatable workflow using approved AI tools, instructions, sources, examples and tests.
5. Evaluate and improve
Test what the model did well, what failed, what needed checking, and what still requires professional judgement.
6. Contemporary agentic systems
Models, harnesses, context, skills, tools, memory, retrieval, agents and orchestration, explained through practical emergency management examples.
7. Humans and AI
Verification, provenance, failure modes, accountability, judgement and the points where a person must review, approve or decide.
8. Move from workflow to agentic system
Explore the same use case in a more structured agentic workspace and test what changes when the system can hold context, work across files and use tools.
9. Test, share and improve
Compare approaches, evaluate reliability and identify what would need to change before a workflow could be used in practice.
10. Define the next experiment
Translate the prototype into a practical next step for the participant or organisation, with clear boundaries and human oversight.
Meet Your Facilitator
Marcello Sano
Founder and Director, Apter
Marcello is a scientist, educator and AI practitioner with more than 15 years of experience across climate risk, natural hazards, resilience and public-sector decision-making. His work spans government, academia and consulting, including research into machine learning, multi-hazard risk and AI-enabled decision support for emergency response.
Register Today
Join this training for professionals working within the Public Sector
For group or payment enquiries or custom training solutions, please contact [email protected]
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