As artificial intelligence evolves, organisations need to move quickly and responsibly to leverage new opportunities and drive economic growth .
To ensure AI and machine learning technologies are used responsibly, leaders need to actively set and guide robust AI governance and risk management controls and anticipate regulatory developments.
Without the integration of AI governance controls, oversight and accountability, organisations can face regulatory, legal, reputational and financial consequences.
KPMG’s Trusted AI Framework provides an integrated approach to the responsible and ethical design, development, procurement and use of AI technologies, so leaders can mitigate risks, foster trust and maximise long-term value.
What CEOs are saying about artificial intelligence
* Statistics for Australian CEOs from the KPMG Global CEO Outlook 2024
AI and risk management
-
1
AI algorithmic bias and fairness
Systemic bias can be embedded in AI-automated decision-making.
-
2
Algorithmic complexity and uncertainty
Increasingly complex AI algorithms can lead to unpredictable or non-intuitive behaviour.
-
3
AI data provenance and integrity
For performance and fairness, visibility over the entire data pipeline is critical.
-
4
Data security and personal privacy
Data-hungry AI systems can expose sensitive information to privacy breaches.
-
5
Explainability
Stakeholders won’t trust AI-driven decisions if they don’t understand how decisions are made.
-
6
Human–AI collaboration and augmentation
To create the best use cases for AI integration, collaboration with human experts is key.
-
7
AI regulatory compliance and anticipation
Organisations need to proactively anticipate developing AI regulation and integrate compliance efforts seamlessly.
-
8
Third-party reliance
Third-party provider AI disclosure needs to be reliable, trustworthy and consistent.
Artificial intelligence regulation in Australia
AI regulation is rapidly evolving. Australia is developing a risk-based approach, starting with the Voluntary AI Safety Standard and associated mandatory guardrails, which were released in September 2024.
The international standard ISO/IEC 42001:2023 focuses on an organisation’s AI management system. The European Union’s Artificial Intelligence Act is also now in force.
C-suite AI leadership
Boards and C-suites are advocating for responsible AI integration, to help balance its benefits with ethical considerations and mitigate risks such as privacy breaches and misuse. As leaders make strategic AI investment choices aimed at building a competitive advantage, they must also shift their approach to AI governance to meet the maturity and complexity of their AI strategy.
Key elements of effective AI governance
- Leadership and accountability built into the organisational structure.
- Principles, policies and standards developed around the design and use of AI technologies.
- Risk management and processes to ensure AI technologies are safely and responsibly used.
- Data governance framework to ensure the quality, security and ethical use of data throughout the AI lifecycle.
- Cross-functional collaboration to address the multifaceted challenges associated with AI.
- Supporting infrastructure across data sources, technology platforms, and related systems.
- Culture, training and awareness to ensure all stakeholders have the knowledge and skills to use AI effectively and ethically.
- Continuous evaluation and improvements for sustainable and responsible AI deployment.
A roadmap for Trusted AI governance
Create even better business outcomes with responsible and ethical AI governance.
Download report (PDF 2.24MB)Why choose KPMG to support your AI solutions?
We help our clients navigate increasingly complex landscapes and better manage the challenges and opportunities across AI.
Our interdisciplinary team draws on expertise across the different divisions of KPMG in Australia and globally.
We provide support to:
- accelerate the adoption and integration of AI technologies to innovate, improve efficiency and provide better services
- embed AI systems into operations for a competitive edge
- address emerging and established AI risks.
