AI Governance Lighthouse Case Study Series

Since HTI’s AI Corporate Governance Program (AIGCP) began in September 2022, we have engaged with over 1000 organisations and individuals across Australia. A consistent request from business leaders has been to hear from their peers across diverse organisations who are in the process of tackling the challenge of AI governance. In response, HTI launched its Lighthouse Case Study Series, as part of the AICGP, to highlight the insights generated and challenges faced by organisations on the frontier of human-centred AI development and deployment. 

HTI’s Lighthouse Case Study Series shines a light on organisations that are actively exploring different approaches to human-centred AI governance. HTI’s Lighthouse Case Study Series will initially feature three leading organisations – Telstra, KPMG Australia, and UTS.

Case Study #1 – Telstra

The first case study explores how Telstra is currently using AI, its approach to AI governance, the governance structures it has set up that support decision-making, and the complementary support provided to date. Important insights include:

  • When assessing the strategic value of AI, organisations should consider the problem they are trying to solve and whether AI is the right tool to solve that problem.
  • Effective data governance is critical to AI governance. 
  • Robust system architecture is essential to operationalise governance controls.
  • A rapidly evolving technology landscape requires continuous improvement.
     

Read the Telstra case study (PDF, 4.5MB)

Case Study #2 – KPMG Australia

The second case study features KPMG Australia (KPMG) and its development and use of an internal Generative AI agent, KymChat. This case study explores how KPMG developed KymChat, how it is being used, and how KPMG is approaching the governance of this Generative AI tool. Important insights include:

  • The responsible AI guardrails and controls need to be specific to the system and context for deployment. One way to identify these is through careful experimentation with, and gradual deployment of, AI systems.
  • High quality data is critical for achieving the best results with Generative AI. Organisations will need to consider uplifting their existing data governance processes.
  • The development, deployment and governance of AI systems is more likely to succeed where an organisation takes both a bottom-up and top-down approach.
     

Read the KPMG case study (PDF, 5.1MB)

Case Study #3 – University of Technology Sydney

This case study explores how University of Technology Sydney (UTS) is using AI, the role of stakeholder engagement, and the policies, procedures and governance structures developed to manage the risks and secure the benefits of AI systems. The key governance insights include:

  • Stakeholder engagement is an important and valuable process that can improve policies, build stakeholder trust, and increase the confidence of decision-makers in relation to the adoption and use of AI systems.
  • Putting in place clear policies and procedures to govern the adoption and use of AI systems allows for better and easier decision-making by senior leadership. 

  • Successful AI governance requires an interdisciplinary approach, and it is essential that staff with different backgrounds and expertise have an opportunity to come together to discuss issues and approve solutions.

Read the UTS case study (PDF, 6.6MB)

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.