AI transforms compliance and risk management challenges

In Short:
– Regulatory compliance and risk management are evolving, with AI helping to centralise and democratise risk identification.
– The interconnected risk landscape requires real-time oversight, which AI can facilitate while keeping company data secure.

Australian businesses are facing an increasingly complex risk landscape, with regulatory demands, cyber threats and supply chain vulnerabilities putting greater pressure on organisations to strengthen how they identify and manage risk.

Adam Bowles, Country Director for ANZ at OneAdvanced, says artificial intelligence is emerging as a key tool in modernising risk management and making it easier for organisations to respond to risks in real time.

Australia has played a significant role in the development of modern risk management standards, including the ISO 31000 framework.

But as businesses become more interconnected and global events create risks that can quickly spread across markets, traditional approaches are facing new challenges.

Cybersecurity threats and vulnerabilities across third-party supply chains are among the issues confronting Australian organisations, with developments overseas capable of creating operational and financial consequences locally.

Bowles says businesses are increasingly looking to “democratise” risk management by giving employees across an organisation the ability to identify, document and report potential risks, rather than relying solely on dedicated risk specialists.

For leadership teams, this requires a consistent and real-time view of risks and the controls being used to manage them.

Fragmented systems and manual processes can make it difficult to maintain that visibility across an organisation.

AI could help address that challenge by bringing risk information into a more centralised and accessible framework.

According to Bowles, AI can allow employees to document risks and develop mitigation strategies using natural language, while helping structure information against established frameworks such as ISO standards.

A “human in the loop” approach can also allow AI to assist employees in identifying potential controls and organising risk information, while keeping human oversight at the centre of the process.

Data security remains a critical consideration, particularly as businesses assess how AI can be incorporated into sensitive compliance and risk workflows.

Bowles says privately hosted language models can provide organisations with greater control over their data, with company information kept separate from public AI models and not used to train those systems.

As regulatory and operational pressures continue to evolve, the integration of AI into risk management could give Australian businesses new ways to identify threats, coordinate responses and maintain greater visibility across their operations.