AI is becoming embedded across banking, insurance, superannuation and financial services. LogiQAI helps organisations understand where AI is being used, assess whether governance is keeping pace and establish an ongoing approach to managing AI risk.
AI capabilities are increasingly appearing across operations, customer experiences, technology environments, analytics, risk functions and third-party platforms. The challenge is no longer simply whether an organisation has an AI policy. It is whether governance can keep pace with how AI is actually being adopted.
AI adoption can extend beyond centrally approved platforms, including embedded capabilities, third-party systems and business-led experimentation.
Can you see enough of your AI landscape to govern it?AI can cross technology, risk, legal, privacy, security and individual business functions.
Is ownership clear when AI-related decisions or risks emerge?AI capabilities can sit within vendors, platforms and services already used across the organisation.
Do existing third-party controls provide sufficient visibility?AI can interact with organisational, customer and sensitive information in new and increasingly complex ways.
Are your existing controls keeping pace with AI-enabled workflows?A governance model designed around a handful of use cases may struggle as adoption expands across the organisation.
Can your governance approach scale with AI?Boards and executives need meaningful visibility into AI exposure, governance maturity and priority areas for action.
Can leadership see and understand the AI governance picture?Across financial services, AI is increasingly becoming an enterprise governance, risk and resilience issue — not simply a technology initiative.
For APRA-regulated organisations in particular, the focus on responsible AI adoption, governance, risk management, operational resilience and leadership oversight is becoming increasingly important.
Banks, insurers, superannuation trustees and other financial institutions may already have sophisticated risk frameworks, controls and governance structures.
AI introduces a different question: whether those existing structures provide enough visibility, accountability and assurance as AI adoption expands.
“Do we have the visibility, governance and evidence to manage AI appropriately?”
Whether you are establishing formal AI governance or strengthening an existing programme, LogiQAI provides a structured path from visibility through to ongoing maturity.
Understand where AI exists and how it is being used.
Establish governance maturity and identify material gaps.
Turn findings into clear governance and remediation priorities.
Strengthen the structures, processes and controls around AI.
Maintain visibility as tools, systems and use cases evolve.
Measure progress and continuously improve governance capability.
LogiQAI aligns its governance approach to the NIST AI Risk Management Framework, helping organisations translate recognised AI risk-management principles into practical governance activity.
Establish accountability, policies, roles and organisational structures around AI.
Understand AI systems, use cases, context, dependencies and potential impacts.
Assess and track AI-related risk, control effectiveness and governance maturity.
Prioritise risks, implement appropriate responses and continuously improve.
Build a clearer, more defensible picture of AI adoption, governance maturity, accountability and areas requiring attention.
Understand where AI exists and where greater organisational visibility may be required.
Assess current governance structures against recognised AI risk-management practices.
Understand whether responsibility for AI oversight and decision-making is clearly defined.
Identify areas where existing controls may need to evolve alongside AI adoption.
Focus remediation effort on the areas most important to improving governance maturity.
Maintain visibility as new tools, AI capabilities, vendors and use cases emerge.
Effective AI governance requires collaboration across technology, risk, security, data, privacy and executive leadership.
Evidence-based oversight of AI adoption, risk and governance maturity.
Greater visibility into AI-related exposure, controls and accountability.
Understand AI adoption across the broader technology environment.
Gain greater visibility into information, security and third-party AI risk.
Create governance that supports responsible innovation rather than slowing it down.
Understand how AI is being adopted and where governance requirements may arise.
Financial institutions need to manage AI risk while still capturing the opportunity AI creates. Effective governance shouldn't simply introduce more barriers. It should provide enough visibility, accountability and confidence for teams to innovate responsibly while giving leadership greater assurance around how AI is being used.
Start from your current level of governance maturity and choose the level of ongoing support your organisation requires.
Establish the foundations for safer AI adoption.
Understand your AI landscape, assess governance maturity, identify priority gaps and establish an actionable baseline for improvement.
Explore Silver →Mature your AI governance with continuous oversight.
Move beyond point-in-time assessment with ongoing monitoring, maturity measurement and specialist governance support.
Explore Gold →Embed AI governance across your organisation.
Establish an embedded governance partnership with continuous assurance, specialist advisory and executive and board-level reporting.
Explore Platinum →Discover your AI landscape. Assess your governance maturity. Build an ongoing approach to managing AI risk across your organisation.
Book an AI Governance Assessment →
