AI Compliance and Ethics
Ensure ethical AI governance you can explain to your board. Our solution delivers AI risk & compliance controls for responsible AI compliance.
- Translate AI initiatives into policies and compliance frameworks AI recognize.
- See where AI is used, how risky each system is, and who is accountable.
- Design oversight for AI regulatory ethics that keeps humans in control.
- Built for regulated mid-market organizations, not just tech-first startups.
AI Governance Dashboard
Audit-ReadyAI Risk Is Now a Governance Problem, Not Just an IT Problem
Boards and regulators expect clarity on where AI is used and how it's controlled.
The Governance Reality
AI is being piloted or used in workflows without always clear oversight. Compliance teams often learn about AI projects late—when deployment is imminent or when issues arise.
Regulators and boards now expect clarity on:
- Where AI is used
- How it is controlled
- How it aligns with existing risk frameworks
Compliance, risk, and ethics teams need more than high-level AI policies—they need operationalized governance.
Sound Familiar?
- We don't have a single inventory of AI systems, copilots, or agents.
- Policies mention 'AI' but don't translate into actual controls and workflows.
- We hear about AI projects late, when deployment is imminent or issues arise.
- We're not sure how to classify AI use cases by risk and required oversight.
- We worry about bias, explainability, and accountability, but lack a concrete program.
Kriv AI focuses on making AI governable within your existing compliance reality.
Who We Help in Compliance, Risk & Ethics
From Chief Compliance Officers to General Counsel and technology leaders.
Compliance & Risk Leaders
- Chief Compliance Officer, Chief Risk Officer, Heads of Governance.
- Own policies, frameworks, and risk appetite.
- Need AI programs that align with existing governance, not bypass it.
Privacy, Legal & Ethics
- Chief Privacy Officer, General Counsel, Ethics & Integrity leads.
- Concerned with data protection, fairness, bias, and reputational risk.
- Need clear documentation of AI use, boundaries, and accountability.
Technology Leaders Supporting Governance
- CIO, CTO, CDO, Heads of Data & Analytics.
- Implement the technical controls and monitoring.
- Need governance models that are realistic to implement and maintain.
Our engagements typically involve both compliance/legal and technology from the start.
How Kriv AI Supports Compliance & Ethics Teams
Our solutions designed with governance as a first-class concern.
AI Readiness & Governance Assessment
Assess AI maturity, data readiness, and governance gaps; create a roadmap that compliance and technology can align on.
Learn moreAI Governance & Compliance-as-a-Service
Define policies, risk classifications, controls, and review processes for AI across your organization.
Learn moreMLOps & Governance-as-a-Service
Operationalize governance: ensure AI systems are monitored, logged, and managed with clear ownership.
Learn moreAgentic AI & Automation
Ensure AI agents and automations operate within explicit policies and guardrails, with human-in-the-loop where required.
Learn moreLLM Fine-Tuning & Custom Models
Design deployments that keep sensitive data in compliant environments and respect your risk posture.
Learn moreWhat "Governed AI" Means in Practice
Core governance elements that make AI explainable and controllable.
Inventory & Classification
- Maintain a living inventory of AI systems, copilots, and agents.
- Classify by risk level, data sensitivity, and business impact.
Policies & Controls
- Translate high-level AI principles into concrete technical and process controls.
- Align with frameworks similar to NIST AI RMF, but adapted to your context.
Reviews & Approvals
- Define when and how AI use cases need review (before launch, periodic, after incidents).
- Embed compliance and risk review into the AI lifecycle.
Documentation & Reporting
- Create documentation that supports internal audit, regulators, and board updates.
- Capture decisions, exceptions, and mitigations in a structured way.
Example Governance & Ethics Use Cases
Practical governance applications for compliance and ethics teams.
AI System Inventory & Risk Register
Create and maintain an inventory of AI systems with risk levels, owners, and controls.
View use caseAI Use Case Review & Approval Process
Design workflows for new AI use case proposals, review, and sign-off involving compliance and technology.
View use caseBias & Fairness Review Support
Support periodic bias/fairness checks with structured processes and reporting, working alongside your teams.
View use caseAI Policy & Standard Implementation
Turn your AI principles or codes of conduct into operational standards, templates, and checklists.
View use caseIncident & Escalation Pathways for AI
Define how issues with AI systems are detected, escalated, investigated, and resolved.
View use caseBoard-Ready AI Governance Reporting
Prepare recurring governance summaries that leadership and boards can understand.
View use caseEthics, Not Just Bare-Minimum Compliance
Legal compliance is necessary—but not always sufficient for trust.
Beyond Checkbox Compliance
Legal compliance is necessary but not always sufficient. What's legally permissible may still harm trust, reputation, or stakeholders.
Ethical considerations like bias, fairness, transparency, and appropriate use are central to building and maintaining trust in AI.
Some use cases may be technically feasible and legally permissible—but still not ethically acceptable for your organization or the people you serve.
Our Ethics Approach
- Explicit criteria for use cases we recommend against or refuse to support.
- Guidance on incorporating ethics review into AI decision-making.
- Support for articulating your own AI ethics stance to staff and partners.
- Alignment with your existing ethics, DEI, and risk policies.
How a Governance-Focused Engagement Works
A structured approach that respects your existing frameworks.
Discovery & Framework Mapping
- Review your existing policies, risk frameworks, and AI initiatives.
- Map your current posture against AI governance best practices.
Governance Design & Pilot
- Co-design governance structures: roles, processes, artefacts, and reporting.
- Pilot governance on a subset of AI systems, refine based on feedback.
Rollout Across the AI Portfolio
- Extend governance patterns and controls across AI use cases, departments, and systems.
- Enable teams with templates, checklists, and playbooks.
Ongoing Support & Improvement
- Provide ongoing advisory, reviews, and updates as regulations and AI footprints evolve.
- Adjust risk classifications and controls as new use cases emerge.
What Compliance & Ethics Leaders Aim to Achieve
Tangible outcomes that matter to governance leaders.
Visibility & Control
Know where AI is used, how it behaves, and who is accountable.
Defensible Governance
Have documented processes and decisions that stand up to internal and external scrutiny.
Reduced Friction with Technology Teams
Move from 'no-by-default' to collaborative, risk-aware enablement.
Clear Story for Leadership & Regulators
Be able to explain your AI risk posture and governance program in plain language.
Resources for Compliance, Risk & Ethics Teams
Insights, guides, and answers relevant to governance leaders.
Building Practical AI Governance Programs with Existing Risk Frameworks
How compliance leaders are integrating AI oversight into their existing governance structures.
View resourceFrom AI Policy to Practice: Turning Principles into Controls
A guide to operationalizing your AI principles into actionable governance.
View resourceCommon Questions Compliance Teams Ask About AI
Answers to the questions we hear most from compliance, risk, and legal leaders.
View resourceNeed AI that your compliance team can live with?
We help compliance, risk, and ethics leaders turn AI risk into a structured governance program—without freezing innovation.