AI Strategy and Governance

UQ researchers are generating insights, frameworks, and tools that deepen understanding of AI’s strategic, ethical, and organisational dimensions to support responsible and effective AI adoption. Their work enables organisations—from startups to large enterprises—to design, implement and leverage AI systems that are secure, trustworthy, and aligned with societal values, while also empowering them to compete, innovate, and seize emerging opportunities in rapidly evolving markets.

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 organizations 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 organisations across industries showing how autonomous AI tools can be leveraged and integrated in human driven product innovation processes.