AIGovernance
When AI runs on its own,
keep it from running wild.
Wrong decisions, flawed learning, data leaks, copyright infringement:
we bring the risks that grow with AI adoption under control through systematic governance.
Why AI Governance
Invisible risks
can break an organization
As AI adoption grows, many companies overlook these six risks.
Bias Risk
Bias risk
Skewed training data leads to unfair decisions in hiring, evaluations, loan screening and more.
Example
A hiring AI learns from past résumés
→
Because most past hires were men, it starts to favor male applicants.
Reliability Risk
Reliability risk
Hallucinations and unverified output mislead decisions and can lead to serious consequences.
Example
An AI says “this drug is safe,” but the answer has no basis and is a hallucination →
Risk of misuse in a medical setting
Privacy Risk
Data leak risk
Sending information to cloud AI increasingly risks violating privacy laws.
Example
An employee asks a generative AI to “summarize this contract”
→
Customer details and terms in the contract go to an outside server, risking a leak
Security Risk
Security risk
Abuse through prompt injection attacks and deepfakes is on the rise.
Example
Generative AI is used to create realistic audio and video, and a fake CEO voice is used for impersonation (a deepfake) →
Used for brand damage or fraud
Business Risk
Business impact risk
Over-reliance on AI weakens human judgment and hollows out an organization’s ability to decide.
Example
An AI proposes a wrong price, staff accept it because “the AI said so,” and a dispute with a client follows →
It turns into a legal dispute
Regulatory Risk
Regulatory risk
Copyright infringement and breaches of the EU AI Act: responding to tighter rules worldwide is urgent.
Example
An AI-generated image includes an existing character, risking copyright infringement →
It leads to civil or criminal lawsuits
Gartner AI TRiSM
Four pillars: trust, risk,
security and continuity
Built on Gartner’s AI TRiSM framework, we design AI governance for your whole organization.
01 TRUST
Trust management
We verify the transparency, accountability, fairness and reliability of AI systems to build trust with stakeholders.
02 RISK
Risk management
We systematize monitoring for accuracy decline, security and privacy compliance, and business continuity.
03 SECURITY
Security management
We implement data protection, access control, model integrity and defenses against attacks.
04 MODELOPS
Model operations
We establish continuous model monitoring, lifecycle management and retraining processes to maintain quality.
AI Governance Component
Supporting trust and safety in AI:
two axes and four layers
Two axes, Trust and Risk, work together under a Guideline covering all four layers to deliver AI governance across the organization.
Trust
Ensuring trust
Application
(the front line of AI use and ethical UX)
AI ethics, policy compliance and output quality where AI meets end users, ensuring generative AI apps are fair and transparent.
AI Platform
(model operations / MLOps layer)
Builds a safe MLOps foundation with model explainability, drift monitoring, audit trails and a model registry.
Centralized Data
(data reliability and transparency layer)
Builds a data foundation for trustworthy AI decisions across four areas: lineage, quality, privacy and governance.
Infrastructure
(infrastructure security and redundancy)
Protects the foundation of every layer with multilayered security: zero trust, encryption, observability and GPU isolation.
Risk
Control
AI Governance Support
Accelerate AI adoption
with Trust, Risk and Security
By putting trust, risk and security in place systematically, AI becomes a real competitive advantage for your organization.
✓ Trust, risk and security management
✓ Faster adoption that sticks
✓ Creating new value
Operating rules & structure
Keeps AI reliable and explainable over time
Explainability
- Model explanation policy
- Support for adopting XAI tools
- Visible reasoning behind decisions
Model operations
- Continuous monitoring and decline detection
- Retraining processes
- Lifecycle registry
Policies & data governance
Ensures security and legal compliance across the organization
AI security
- Zero trust / Encryption
- Prompt injection defense
- Access control and audit logs
Privacy / Ethics
- Legal compliance and consent management
- GDPR / Japan’s privacy law (APPI)
- Ethics policies and terms of use
Getting Started
Up and running
in as little as one month
We introduce AI governance reliably and quickly, phase by phase.
PHASE 01
Consultation
A dedicated specialist listens to and discusses your current challenges
PHASE 02
Requirements
Makes current AI use and challenges visible, and sets risk priorities
PHASE 03
Controls
Designs policies, processes and technical controls, with documentation
PHASE 04
Monitoring
Implements monitoring and alerts, and sets up automated reporting
PHASE 05
Improve
Establishes an ongoing improvement cycle, including support as regulations change
Frequently Asked Questions
Yes. We start by reviewing how you use AI today and your challenges, then set risk priorities together.
We design measures tailored to your organization for six risks: bias, reliability (hallucinations), data leaks, security, business impact and regulation.
It is built on Gartner’s AI TRiSM, with four pillars: trust management, risk management, security management and model operations.
Yes. We help with everything from operating guidelines, data upload policies and personal data handling to explainability and model operations.
Yes. With risks such as leaks through work input in mind, we put usage policies and output quality controls in place.
We support GDPR and Japan’s privacy law, legal compliance and consent management, and keep responding to tighter rules worldwide, such as the EU AI Act, during ongoing operation.
You can be up and running in as little as one month. We move through consultation, requirements, control design, monitoring, and operation and improvement.
The future of AI,
accelerated safely
We’ll design a plan
around your environment and needs.
Feel free to get in touch.