Agency as a Service (AaaS)
Agency as a Service reframes AI adoption as outsourcing organisational judgement, decision rights, and accountability.
Category: AI Governance | Year:
AI Governance Research | Strategen AI
Evidence-based research on AI governance frameworks, policies, risk controls and oversight structures for Australian boards and executive teams.
What this research covers
AI governance refers to the policies, decision rights, risk controls and accountability structures that determine how AI is approved, deployed, monitored and escalated within an organisation. At its core, AI governance answers three questions: who is responsible when AI causes harm, what information do boards need to oversee AI risk, and how does an organisation demonstrate accountability to regulators and stakeholders? Unlike general IT governance, AI governance must address challenges unique to machine-learning systems — model opacity, data provenance, emergent behaviour, third-party model dependency and ongoing model drift.
Why this matters for Australian organisations
The Australian regulatory environment is evolving rapidly. The government's voluntary AI Safety Standard, the Privacy Act reforms, sector-specific guidance from APRA and ASIC, and the spillover effects of the EU AI Act are collectively raising the bar for governance maturity. Organisations that treat AI governance as discretionary risk regulatory liability, reputational damage and board-level accountability failures as AI adoption scales. Strategen AI's research examines how governance frameworks translate from regulatory intent into boardroom practice — with particular attention to the gap between written policies and actual accountability on the ground.
The APIG framework connection
In the APIG framework, governance is the fourth dimension — the accountability and oversight structures that ensure Actors, Practices and Infrastructure operate as intended. Effective AI governance operates across four components: a policy framework covering use-case approval, data use, transparency and accountability; a risk register tracking AI-specific risks; a decision rights matrix; and board reporting that provides directors with timely visibility into AI risk posture.
Research papers in this hub
From People–Process–Technology to Distributed Agency: Rethinking AI Transformation in the Age of Agentic Systems
Agentic AI exhausts PPT by redistributing agency across humans, systems, practices, infrastructure and governance.
Category: AI Transformation Frameworks, Sociotechnical AI Governance | Year:
“I Did Not Know” Is Not a Defence: Why ASIC Has Already Put AI Inside Directors’ Duties
ASIC has twice told directors that AI sits inside their existing duties under the Corporations Act. RI Advice provides the legal template. By mid-2026, foreseeability and industry standards have crystallised. "I did not know" is no longer a defence — it is evidence of a governance failure.
Category: Corporate Governance, AI Governance & Directors Duties | Year:
Resource Optimisation AI: Governance and Trade-offs in Energy, Water & Food Systems
Explores how AI’s optimisation of energy, water, and food demands new governance for equitable sustainability.
Category: AI Governance & Ethics | Year:
AI-Enabled Fraud in Australian Organisations
AI-enabled fraud in Noosa exposes governance gaps and drives a roadmap for resilient, accountable public-sector AI.
Category: AI Governance, AI Risk, Assurance & Cyber-Resilience | Year:
Related research hubs
Advisory services informed by this research
- AI Governance Consulting — Strategen AI applies this research through structured advisory engagements with Australian organisations.
- Board AI Assurance — Strategen AI applies this research through structured advisory engagements with Australian organisations.
- Managed AI Governance Office — Strategen AI applies this research through structured advisory engagements with Australian organisations.