AI Governance for Government

Govern AI with transparency, accountability and confidence.

AI is increasingly being introduced across government operations, service delivery, policy, administration, data analysis, workforce tools and third-party platforms. LogiQAI helps government organisations understand where AI is being used, assess whether governance is keeping pace and establish an ongoing approach to managing AI responsibly.

Responsible AI requires evidence
Can your organisation demonstrate how AI is actually being governed?
01
Visibility Know where AI exists across systems, teams and suppliers.
02
Accountability Understand who owns AI systems, use cases and decisions.
03
Controls Assess whether governance is keeping pace with adoption.
04
Evidence Give leadership a clearer view of maturity, risk and progress.
01 Public Accountability
02 Responsible Adoption
03 Evidence-Based Oversight
04 Continuous Governance
The Governance Challenge

AI can enter government from more directions than expected.

AI governance is no longer limited to a handful of formally approved transformation programmes. Capabilities can appear across existing systems, suppliers, pilots and everyday workforce tools — making organisation-wide visibility increasingly important.

01

Approved Technology Platforms

Existing enterprise platforms can introduce new AI capability through upgrades, product releases and embedded functionality.

02

Third-Party Suppliers

Vendors, cloud services and external providers can introduce AI into government environments through existing commercial relationships.

03

Pilots & Transformation Programmes

Formal innovation initiatives can move quickly from experimentation into operational use.

04

Business-Led Adoption

Individual teams can begin using generative AI, productivity tools or embedded AI features outside centrally managed programmes.

05

Public-Facing Services

AI may increasingly support service delivery, interactions, recommendations, triage, analysis and administrative processes.

The Shift

The question is no longer simply: “Can AI improve this process?”

Government organisations also need to ask whether they can explain how AI is being used, who is accountable for it and whether appropriate oversight exists throughout its lifecycle.

Where Complexity Emerges

Responsible AI requires more than an AI policy.

AI intersects with existing government responsibilities across privacy, security, procurement, risk, information management, assurance, service delivery and public accountability.

01 — AI VISIBILITY

AI can exist beyond the systems leadership already knows about.

Approved platforms, embedded functionality, third-party systems, pilots and business-led experimentation can all increase the size of the AI landscape.

Do you have a reliable view of where AI exists across the organisation?
02

Public Accountability

AI may contribute to recommendations, processes or services that affect individuals and communities.

Is responsibility clear when AI influences an outcome?
03

Sensitive Information

AI can interact with personal, confidential, operational or protected information.

Do you understand what information AI systems are interacting with?
04 — THIRD-PARTY AI

Suppliers can change your AI landscape without introducing a new system.

AI functionality can arrive through existing vendors, cloud platforms, software upgrades and service providers.

Do procurement and vendor governance processes provide enough AI visibility?
05

Consistency at Scale

Different agencies, departments and functions may adopt AI at different speeds and with different controls.

Can governance be applied consistently without unnecessarily slowing innovation?
06

Auditability & Evidence

Policies provide intent. Leadership and assurance teams also need evidence of how governance operates in practice.

Can you demonstrate what AI exists, how it is governed and where action is required?
From Policy to Practice

AI governance needs to work in practice — not only on paper.

Policies and principles are an important foundation. Effective governance also requires operational visibility into how AI is actually being used across the organisation.

LogiQAI helps connect governance intent with evidence.

What AI exists?
Understand AI beyond formally approved systems, including embedded, third-party and emerging use cases.
Who owns it?
Establish clearer accountability across technology, business, data and operational teams.
What controls apply?
Understand whether existing governance, risk, security, privacy and procurement controls remain appropriate.
Where are the gaps?
Identify and prioritise areas where governance maturity needs to improve.
What is changing?
Maintain ongoing visibility as AI tools, capabilities, vendors and use cases evolve.
The LogiQAI Approach

From AI adoption to governed AI.

Build governance as an ongoing organisational capability — starting with visibility and moving toward continuous oversight.

01

Discover

Identify where AI exists across systems, teams and suppliers.

02

Assess

Establish current governance maturity and identify gaps.

03

Prioritise

Focus effort on the governance issues requiring action.

04

Govern

Strengthen accountability, policies, controls and oversight.

05

Monitor

Maintain visibility as AI use and technology evolve.

06

Mature

Track progress and continuously strengthen governance.

NIST AI RMF Aligned

A recognised framework. Applied to the public sector.

LogiQAI aligns its governance approach to the NIST AI Risk Management Framework, helping organisations translate recognised AI risk-management principles into practical governance activity.

GOVERN
Establish clear accountability, policies, roles and organisational oversight around AI.
MAP
Understand AI systems, use cases, context, users, dependencies and potential impacts.
MEASURE
Assess AI-related risk, control effectiveness and governance maturity.
MANAGE
Prioritise risk, implement appropriate responses and continuously improve.
Evidence, Not Assumptions

Build a clearer picture of how AI is being governed.

Through discovery, maturity assessment and ongoing monitoring, LogiQAI helps government organisations understand both their current AI environment and how governance is evolving over time.

01

AI Use & Exposure

Understand where AI exists across departments, systems, services and third-party environments.

02

Ownership & Accountability

Identify whether responsibility for AI systems, use cases and decisions is clearly defined.

03

Information Interaction

Understand where AI may interact with personal, sensitive or protected information.

04

Governance Maturity

Assess whether existing governance arrangements are keeping pace with AI adoption.

05

Control & Assurance Gaps

Identify areas where risk, privacy, cyber, procurement or assurance controls may need to evolve.

06

Ongoing Change

Maintain visibility as new tools, suppliers, platforms and use cases emerge.

Whole-of-Organisation Oversight

AI governance crosses organisational boundaries.

Responsible adoption requires collaboration between leadership, technology, security, risk, privacy, procurement, data, assurance and the teams responsible for service delivery.

AI
Governance
Executive Leadership CIO & Technology CISO & Security Risk & Assurance Privacy & Legal Procurement Data & AI Policy Service Delivery Internal Audit
Responsible Public Sector Innovation

Governance should enable responsible AI — not prevent progress.

Government organisations need to innovate while maintaining public trust and appropriate oversight. Effective AI governance should provide enough visibility, accountability, evidence and confidence for teams to explore AI opportunities responsibly — without creating unnecessary friction around every use case.

Continuous Governance

Your AI environment does not stand still.

New software features appear. Suppliers introduce AI capabilities. Existing platforms evolve. Pilots move into operational environments. Different teams adopt AI at different speeds.

A maturity assessment creates an important baseline. Ongoing visibility helps organisations understand what has changed and whether governance remains effective.

AI Governance Environment Ongoing Visibility
Technology
New AI functionality introduced

Existing enterprise software gains additional AI capability.

Supplier
Third-party capability changes

A vendor introduces or modifies AI-enabled functionality.

Use Case
New internal AI adoption

A team begins using AI in a new operational workflow.

Governance
Oversight needs to evolve

Controls, ownership and reporting are reassessed as the environment changes.

Choose Your Governance Journey

Establish. Mature. Embed.

Choose the level of AI governance support that best reflects your current maturity and the level of ongoing oversight required.

01 — Establish

Silver

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 →
02 — Mature

Gold

Mature your AI governance with continuous oversight.

Move beyond point-in-time assessment with ongoing monitoring, maturity measurement and specialist governance support.

Explore Gold →
03 — Embed

Platinum

Embed AI governance across your organisation.

Establish an embedded governance partnership with continuous assurance, specialist advisory and executive-level reporting.

Explore Platinum →
Start Your AI Governance Journey

Govern AI with greater confidence.

Discover your AI landscape. Assess your governance maturity. Build an ongoing approach to responsible AI adoption across your organisation.

Book an AI Governance Assessment →