Privacy made simple.
 AI made responsible.

Our AI governance consulting and risk advisory practice helps you design, deploy, and manage AI responsibly, aligned with global standards and local regulations.

Why Work With Us As Your
AI Governance Consultants

Most AI governance efforts fail because policies are created in isolation, decision rights are unclear, and enforcement weakens under pressure. Our approach anchors governance in real operational workflows and decision-making, aligning with how AI is actually used, managed, and scaled across the business.

Our Services

 
 
 

AI STRATEGY & GOVERNANCE DESIGN

A structured governance foundation that defines how AI decisions are made, who owns them, and how risk is managed across your organization. Built to support AI adoption and scalability without introducing ambiguity, fragmentation, or unmanaged exposure.

    • A clear governance structure guiding all AI initiatives

    • An AI governance maturity assessment to identify gaps and blind spots

    • Custom governance frameworks including policies, principles, and standards

    • Defined roles, responsibilities, and escalation paths across teams

    • An AI risk classification model tailored to your industry and business

    • A phased AI governance roadmap leadership can approve and execute

    • Ongoing advisory support to simplify complex governance decisions

    • Faster AI adoption without loss of control

    • Clear accountability before problems arise

    • Reduced risk of reactive governance driven by incidents or regulators

    • Alignment between AI investments and business objectives

    • Readiness for emerging AI regulation without last-minute disruption (Bill C-27, EU AI Act, sector-specific mandates)

AI RISK ASSESSMENT & IMPACT ANALYSIS

A comprehensive evaluation by our AI governance consulting & risk advisory team to assess how AI systems may create legal, ethical, operational, or reputational exposure. Focused on identifying material risk early and documenting decisions in a defensible way.

    • AI impact assessment (AIIA) reports aligned to regulatory expectations

    • Algorithm Bias and fairness evaluations using recognized standards (NIST AI RMF and ISO/IEC42001)

    • Third-party AI vendor risk assessments

    • AI system tiered risk classification (high/medium/low risk) across the AI portfolio

    • Data quality and training data origin reviews

    • Explainability and transparency assessments

    • Human rights impact assessment for high-risk AI systemsxt goes here

  • Early identification of high-risk AI use cases for proactive risk mitigation

    • Defensible documentation supporting approval decisions

    • Faster deployment with fewer regulatory surprises

    • Increased confidence from regulators and stakeholders

    • Reduced liability through structured risk records

 

RESPONSIBLE AI IMPLEMENTATIONS

The translation of responsible AI governance from policy into daily operations, enabling product teams, procurement, and leadership to implement AI systems responsibly through clear processes, accountability, and practical decision-making.

    • Responsible AI controls integrated into existing workflows and product cycles

    • Practical tools including templates, checklists, and decision guides

    • AI model documentation and transparency protocols

    • Human oversight and review process design

    • Monitoring and performance evaluation tools and frameworks

    • AI incident response plans

    • Responsible AI controls integrated into existing workflows and product cycles

    • Practical tools including templates, checklists, and decision guides

    • AI model documentation and transparency protocols

    • Human oversight and review process design

    • Monitoring and performance evaluation tools and frameworks

    • AI incident response plans

    • Governance that fits your workflows, not disrupts them

    • Faster development without compliance shortcuts

    • Reduced friction between teams and leadership

    • Monitoring strategies that evolve with your AI

    • Preparedness when AI systems fail or underperform

    • Governance that fits your workflows, not disrupts them

    • Faster development without compliance shortcuts

    • Reduced friction between teams and leadership

    • Monitoring strategies that evolve with your AI

    • Preparedness when AI systems fail or underperform

AI COMPLIANCE & REGULATORY ADVISORY

Clear guidance on how current and emerging AI regulations apply to your organization, and how to respond in a structured, defensible way. Our AI governance consulting services provide curated, case-specific expert guidance on compliance obligations.

    • Regulatory mapping across Canada, the EU, the US, and regulated sectors

    • Canadian AI regulatory readiness assessment and compliance gap analysis

    • EU AI Act classification and conformity assessment preparation

    • Sector-specific regulatory compliance (OSFI E-23, Privacy compliance including PIPEDA, PHIPA

    • Regulatory submission preparation and stakeholder engagement support

    • Ongoing compliance monitoring and regulatory change management

    • Clear understanding of sector and case specific obligations across jurisdictions

    • Readiness before requirements become mandatory

    • Documentation that satisfies regulatory scrutiny

    • Market differentiation through verified compliance

    • Systematic adherence to regulatory standards

 

AI TRANSPARENCY & ETHICS ADVISORY SERVICES

A structured approach to embedding fairness, accountability, and transparency into AI systems, helping organizations ensure decisions are explainable, auditable, and ethically grounded for regulators, customers, employees, and internal stakeholders

    • Fairness, accountability, transparency (FAT) framework implementation

    • Training Data Validation Checkpoints

    • Independent ethics advisory access

    • Stakeholder impact assessments and engagement strategies

    • AI ethics and transparency training for executives, developers, and business units

    • Values-to-Requirements Traceability Matrix

    • Public AI transparency reporting and disclosure strategy

    • Clear and defensible AI explanations

    • Consistent handling of ethical uncertainty

    • Increased trust from regulators and the public

    • Reputational Protection through proactive management of bias/discrimination and ethical risks

    • More inclusive and responsible AI outcomes

AI CONTRACT & VENDOR MANAGEMENT

Protect your organization through structured oversight of third-party AI vendors to reduce legal, operational, and reputational exposure. Our AI Governance Consultants  ensure contracts allocate risk appropriately and vendors meet responsible AI standards.

    • Vendor Risk Assessment 

    • AI Vendor contract review and negotiation support (liability, privacy, model training, IP, data processing rights)

    • Vendor AI governance assessment and certification validation

    • AI service level agreement (SLA) design with performance and fairness metrics

    • AI Procurement Framework development with responsible AI criteria

    • Vendor AI audit rights and assurance report review

    • Exit and data deletion provisions for AI vendor relationships

    • Appropriate allocation of AI-related liabilities

    • Stronger vendor accountability through clear performance and ethical standards

    • Protection of proprietary data and IP

    • Consistent compliance across vendors

    • Maintained control when AI is outsourced

 

AI TRAINING & CAPABILITY BUILDING

Role-specific education that builds internal AI governance capability across leadership, legal, risk, and technical teams.

    • Executive AI governance workshops (board and C-suite)

    • Training for legal, compliance, and risk teams

    • Developer training on AI-by-Design and responsible AI tools

    • Industry-specific AI scenario simulations and case studies

    • AI governance maturity assessment and upskilling roadmaps

    • Internal expertise reduces reliance on external support

    • Shared understanding of responsible AI across functions

    • Better-informed AI investment and risk decisions

    • Teams equipped to implement governance in practice

    • Training programs that grow with your AI adoption

 
 
We're here to help. Give us a call.

Industry SnapShot

AI governance can feel overwhelming, especially when the risks vary so much from one industry to the next.
These snapshots offer a simple, human-centered overview to help you make smarter, more confident decisions about managing AI responsibly.

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Frequently Asked Questions

  • AI governance is how an organization oversees the use of AI. It defines who makes decisions, how risk is managed, and how AI systems are monitored so they are used responsibly and lawfully.

  • AI governance matters because executives and boards remain accountable for AI outcomes. Clear governance reduces legal, regulatory, financial, and reputational risk while supporting safe innovation.

  • AI governance addresses risks such as bias, lack of transparency, privacy violations, security failures, and poor decision accountability. These risks can affect people, business outcomes, and regulatory compliance.

  • Responsibility typically sits with executive leadership and the board, supported by legal, risk, privacy, and technical teams. AI governance works best when roles and decision authority are clearly defined.

  • AI governance should be implemented before AI systems are widely deployed. Waiting until problems occur often leads to rushed decisions, higher costs, and increased risk.

  • No. Effective AI governance creates clear rules and approval paths. This reduces uncertainty and helps teams move faster without introducing unmanaged risk.

  • Any AI system that affects decisions, people, data, or business operations should be governed. This includes internal tools, customer-facing systems, analytics models, and third-party AI services.

  • An AI governance risk assessment is a structured review of how an AI system could create legal, ethical, operational, or reputational risk. The goal is to identify issues early and document decisions clearly.

  • AI governance and privacy overlap when AI systems use personal or sensitive data. Governance ensures privacy requirements are built into AI design, use, and oversight.

  • Yes. Smaller organizations often face higher risk due to limited controls. AI governance can be scaled to match the size and complexity of the organization.

  • AI Governance Consultants help organizations design oversight models, assess risk, define decision roles, and align AI use with business goals and regulatory expectations.

  • The first step is identifying where AI is already being used and who is responsible for it. From there, governance structures and risk controls can be put in place.