Artificial intelligence research capabilities and impact

What we're working on

UQ AI researchers and domain experts are co-designing innovative AI solutions to tackle complex global problems together with our industry and government partners.

From health and medicine to business, agriculture, mining, energy and defence, our research impact on industry, society and government is broad and diverse.

Find out more about our key capabilities:

• AI strategy and governance
• Human-centred AI
• Scalable and sustainable AI
• Data-centric AI

Capabilities

• Responsible AI design:
  Translating ethical principles like fairness, accountability and transparency into technical and organisational practices by developing explainable, auditable and bias-aware AI systems informed by insights from business, policy and technology.

• AI for organisational innovation:
  Exploring how AI can enhance knowledge work, drive innovation and boost operational efficiency across diverse organisational contexts while navigating regulatory, ethical and compliance challenges in dynamic environments.

• AI for business opportunity and growth:
  Investigating how AI can support organisations in identifying business opportunities, enhancing decision-making and building agile, data-driven business models. This includes insights, tools and frameworks for leveraging AI in competitive strategy, customer insights and rapid experimentation.

• Skills intelligence and talent management:
  Analysing AI-driven shifts toward skills-based workforce strategies and exploring the socio-technical dynamics of talent management through international collaboration.

Impact

• Case study with the University of Agder highlighted risks of AI-driven decision-making in welfare through analysis of the discredited Dutch SyRI system.
• International case study exploring how AI transforms talent management by shifting from credential-based to skills-based strategies, highlighting both benefits and ethical tensions.
• International case study of leading organizations across industries showing how autonomous AI tools can be leveraged and integrated in human driven product innovation processes.

Capabilities

• AI for human empowerment:
  Designing intelligent systems that prioritise human needs, growth and agency by supporting learning, workforce transformation and human–AI collaboration, while ensuring transparency, fairness and accountability through conceptual, algorithmic and empirical research.

• Participatory and inclusive AI research:
  Using critical, creative and participatory methods to understand the social impacts of automation and advance inclusive AI systems grounded in community realities, promoting societal well-being, justice and citizen rights.

• Ethical AI for public good:
  Developing AI systems that serve the public interest by supporting education, healthcare and public services, while ensuring transparency, fairness and alignment with human values through interdisciplinary research and innovation. 

• AI and misinformation detection:
  Investigating AI techniques for identifying and controlling misinformation in online networks, while examining its dual-use potential in both generating and combating false content.

Impact

• GenAI-powered educational technologies like RiPPLE enhance learning by supporting over 80,000 students with co-created content, peer review and personalised learning, backed by global research in explainable AI and student modelling.

Capabilities

• Efficient AI systems and infrastructure:
  Creating intelligent systems that balance model performance with resource efficiency by applying energy-efficient AI, edge computing, federated learning, and domain adaptation across fields like bioinformatics, agriculture, and medical imaging.

• Emerging technologies for future-proof AI:
  Investigating advanced technologies—including GenAI, LLMs, computer vision and quantum AI—to develop robust, adaptable and scalable AI solutions for long-term societal impact.

• AI for scientific and environmental advancement:
  Developing AI approaches that contribute to scientific discovery and promote environmental sustainability through innovative, interdisciplinary research. 

Impact

• Neurodesk empowers clinicians and researchers with secure, customisable AI tools for medical imaging, accelerating research and improving patient outcomes without requiring technical expertise.
• AI-powered wheat canopy analysis used over 50,000 images to accelerate breeding decisions by enhancing trait extraction and segmentation across growth stages and environments.

Capabilities

• Data-centric AI foundations:
  Enhancing AI performance requires shifting from model-centric optimisation to strategic data curation that prioritises quality, consistency and relevance, while actively addressing real-world challenges such as data scarcity, annotation errors, noise and bias.

• Advanced data management:
  Advancing robust, transparent and socially responsible AI systems requires research in scalable and target-driven multimodal data lake management and preparation techniques, underpinned by strong expertise in data governance, privacy preservation and information security to ensure trustworthy data practices.

• Diverse data modalities:
  By working with semantically structured data, time series, multimedia and spatio-temporal datasets, AI systems can become more adaptive, scalable and better aligned with complex operational realities. 

• Ethical and trustworthy AI:
  Ensuring AI systems are built on reliable foundations involves tackling misinformation and data bias, while promoting transparency and trust throughout data pipelines and decision-making processes. 

Impact

• Scalable machine learning with data-centric AI — developed a system to discover, enrich and select multimodal data for targeted tasks, enabling faster, scalable and cost-effective preparation that supports adaptive, data-efficient enterprise AI aligned with real-world needs.
• In partnership with Health and Wellbeing Queensland, we are advancing causal AI for diabetes prevention by developing active learning algorithms that enable high-quality inference from limited, ethically sourced observational data—achieving up to 11% accuracy improvements while minimising data acquisition costs.

AI research at UQ has global impact

See more UQ AI strengths and impact.