Democratising governance: supporting every employee with responsible and secure AI

Governance has traditionally been the domain of specialists: risk teams, compliance professionals, legal advisers and senior executives have been responsible for interpreting frameworks, assessing exposure, documenting controls and ensuring that organisations meet their obligations. That model is becoming increasingly difficult to sustain.

The pace at which organisations operate means risks can arise anywhere, from a frontline employee identifying a supplier issue to a project manager noticing a control failure, or a team adopting new technology without fully understanding its implications.

At the same time, artificial intelligence is creating an opportunity to make governance more accessible. Responsible AI can help employees identify, articulate and escalate risks without requiring every person in an organisation to become a risk management specialist.

The goal should not be to hand governance over to AI, however: it should be to give more people the tools to participate effectively in governance while retaining clear human accountability.

Governance cannot remain a specialist activity

Effective risk management depends on information reaching the right people quickly. However, traditional processes can create barriers to this. An employee who notices a potential risk may be asked to categorise it, assess likelihood and consequence, identify relevant controls, or describe it using terminology aligned with an enterprise risk framework. For someone who does not work in governance every day, this can be daunting. The result may be that emerging risks are poorly documented, inconsistently recorded, or never raised at all.

This is increasingly out of step with modern approaches to risk management. ISO 31000, for example, is designed to help organisations integrate risk management into governance, strategy, planning, reporting, values and culture, rather than treating it as an isolated function. AI can help bridge the gap between specialist frameworks and everyday business language.

An employee could describe an issue in plain English and receive assistance in structuring it as a risk, identifying potential consequences, considering relevant controls or determining who may need to be involved. AI can also help organisations apply more consistent terminology and processes across teams.

This does not remove the risk professional. Instead, it allows their expertise to be directed towards validation, oversight, complex assessments, emerging threats and strategic decision-making rather than correcting basic administrative errors.

AI literacy is becoming a governance requirement

Democratising governance requires more than simply giving employees access to AI. Employees need to understand where AI can assist them, where its limitations lie, what information can be entered into a system and when human judgement is required.

The Australian Government is increasingly reflecting this approach in its own AI governance. The Digital Transformation Agency’s updated Policy for the responsible use of AI in government, which took effect in December 2025, strengthens requirements for AI accountability, use-case registers, impact assessments and staff capability. Foundational AI training is therefore becoming mandatory across Australian Government services.

Responsible AI requires visible guardrails

Organisations also need to distinguish between employees experimenting with publicly available AI tools and those using AI embedded within a governed enterprise environment.

This is where smaller, private language models can offer a very different approach to general-purpose public large language models. Rather than sending information to a public AI service, organisations can use purpose-built models operating within a closed, controlled environment, with organisational context built into the system. Where these models are locally hosted and designed not to retain customer information or use it to train the underlying model, sensitive governance and risk data can remain within clearly defined boundaries.

This distinction matters in governance; an AI system designed specifically around an organisation’s risk framework, terminology, controls and processes can provide employees with more relevant guidance while reducing the risks of entering sensitive business information into general-purpose public AI platforms.

The Office of the Australian Information Commissioner recommends that organisations undertake due diligence when selecting AI products, consider privacy and security risks, embed human oversight and avoid entering personal or sensitive information into publicly available generative AI tools. Organisations therefore need to consider not only what an AI system can do, but also how and where it operates, what information it can access, whether data is retained or used for model training, and what controls exist around that data.

Approved tools, appropriate access controls, clearly defined data boundaries, audit trails, human review and defined accountability for decisions should all form part of the governance framework. Employees also need mechanisms to raise concerns when AI generates questionable recommendations or behaves unexpectedly.

From gatekeeping to enablement

The real opportunity is to change the role technology plays in governance. Historically, governance systems have been designed primarily for the professionals administering them. AI creates the potential to build systems around the people who encounter risks in their daily work.

This could mean helping an employee turn an observation into a clearly articulated risk, suggesting questions they should consider, identifying existing controls, or prompting them when additional information is required. It can make governance easier to participate in without lowering standards.

There must still be boundaries, though. AI should support, rather than replace, professional judgement, and organisations must remain accountable for the decisions they make and the systems they deploy. However, making governance more accessible should not be mistaken for weakening it. When employees have secure, responsible tools that help them recognise and communicate risk, governance becomes less dependent on a small group of specialists discovering problems after the fact. This is the real potential of AI in governance: not automating accountability but enabling more people to contribute to it.

Top image credit: iStock.com/putilich