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Centres of Excellence and Industry Councils

Each unit has its own space: a front page, its own menu and pages for overview, team, programmes, insights, gallery and contact.

Centre of Excellence

AI Start-up Incubator

An AIAA Centre of Excellence being established to help promising AI ventures build responsibly.

Selected
Overview

Why the centre is being established, the six objectives it works to and its current status.

Inception and program design
Stage
Initial leadership team appointed
Team
In development
Programs
Not yet open
Venture intake
Full detail below
AI
Core
Adil Khan, Chair
Adil Khan, Chair
Special Council, Venture Practice Lead, LUNA Strategic Consulting

Leads the AI Start-up Incubator.

01 / 03
Overview

Purpose and objectives

AIAA's AI Start-up Incubator is being established as an industry-connected Centre of Excellence to help promising AI and AI-enabled ventures move from credible ideas and research to responsible, commercially viable solutions. It will bring together founders, researchers, experienced business leaders, industry mentors, enterprise partners and capital networks, with responsible AI and sound governance embedded from the outset.

The Incubator is currently in its inception stage. AIAA has appointed an initial team to shape its operating model, partnerships and first programs. No ventures or projects have yet commenced.

01Accelerate the development of high-quality Australasian AI and AI-enabled ventures addressing genuine market and community needs.
02Embed responsible AI, sound governance and AIAA standards of practice from the earliest practical stage.
03Connect founders with Industry Councils, enterprise customers, research partners, experienced mentors and potential pilot pathways.
04Build commercial, operational, governance and investment readiness through structured support and evidence-based milestones.
05Build investment readiness through structured mentoring and governance support.
06Share de-identified insights and practical learning with the AIAA community, while protecting confidentiality and intellectual property.
Stage
Inception and program design
Team
Initial leadership team appointed
Programs
In development
Venture intake
Not yet open
Projects
No current projects
Partnerships
Foundation discussions commencing
Illustrative: multidisciplinary teams working on applied AI problems
Illustrative: multidisciplinary teams working on applied AI problems
Illustrative: applied AI build and testing work
Illustrative: applied AI build and testing work
Illustrative: mentoring with experienced industry practitioners
Illustrative: mentoring with experienced industry practitioners
Illustrative: venture showcase setting
Illustrative: venture showcase setting
AIAA Operating Console
Industry Councils

Industry Councils

Industry forums convened by leaders to advance responsible, practical AI adoption.

Industry Council

Mining and Resources Industry Council

AIAA's industry forum for responsible, high-value business AI adoption across the resources value chain.

Patrick Hanna, Chair
Patrick Hanna, Chair
Senior Principal Mining, Catalyst International & Practice Leader, Indonesia

Leads the Mining and Resources Industry Council Industry Council.

01 / 04
Overview

Purpose and objectives

AIAA's Mining and Resources Industry Council is being developed to help the industry turn AI capability into practical business value. Its purpose is to bring together industry leaders, practitioners, researchers and technology specialists to strengthen responsible adoption across exploration, mining, processing, resource logistics and supporting services.

The Council will focus on better business decisions, operational performance, workforce capability and responsible resource management, with safety, sound governance and human accountability central to its work. It is currently at inception stage. Its work plan, appointments, partners, budgets and launch dates remain subject to confirmation.

01Identify high-value AI opportunities across the mining and resources value chain, grounded in real industry needs.
02Promote responsible adoption with safety, data protection, operational assurance and human accountability built in.
03Connect operators, METS businesses, researchers and specialists to share expertise and explore practical collaboration.
04Strengthen business cases, adoption readiness and measurement of operational and commercial outcomes.
05Build workforce capability and retain valuable industry knowledge through education, mentoring and professional development.
06Share practical guidance and verified learning through AIAA's professional community and Knowledge Repository.
Council establishment
In development
Proposed operating model
Industry led
Core focus
Responsible adoption
Development agenda
Programmes being shaped
Illustrative: open-pit operations
Illustrative: open-pit operations
Illustrative: autonomous haulage on a pit road
Illustrative: autonomous haulage on a pit road
Illustrative: remote operating centre
Illustrative: remote operating centre
Illustrative: mineral processing operations
Illustrative: mineral processing operations
Capability in action · Pilot

Agentic AI in mining's critical work

AIAA's Executive Team is pilot testing the adoption of agentic AI through application development for pit optimisation. The work explores AI-augmented pit optimisation and predictive maintenance in the field.

Patrick Hanna, ELT, AIAA member and Executive Council, AusIMM, and Usman Qureshi, AIAA member, working together on the pilot.

Mining professional reviewing pit optimisation data at an open-pit operation
Pilot testing
From development to deployment: AI-augmented pit optimisation and predictive maintenance in the field.
Live development screens showing mining topographic analysis
Live development

Live development: multi-screen agentic workflows, topographic analysis and team review.

Remote collaborative review of the agentic AI mining application
Team review

Collaborative review during development of the mining application.

01
Application
Pit optimisation
02
Workflow
Topographic analysis and scheduling
03
Assurance
Human oversight at every decision point