QMet / Consulting Deploy AI with confidence. Govern it with discipline.

AI Risk & Governance Advisory

AI adoption is advancing faster than many governance models can mature. We help organizations establish responsible AI practices that address regulatory expectations, reduce model risk, and support sustainable innovation.

End-to-end AI security assessments across model integrity, data pipelines, and inference environments
AI governance frameworks aligned with the EU AI Act, NIST AI RMF, and ISO/IEC 42001
Practical oversight models that balance innovation speed with accountability

The Challenge

AI creates significant opportunity—and material risk.

Organizations moving quickly to deploy AI often accumulate model risk, regulatory exposure, and reputational vulnerability before the right governance structures are in place.

AI Models Operating Without Governance

High-impact decisions may be made by opaque models without an audit trail, bias controls, or documented risk classification, creating legal, regulatory, and operational exposure.

Adversarial Attacks on AI Systems

Prompt injection, model inversion, and data poisoning can compromise outputs, expose sensitive training data, and influence business-critical decisions.

Regulatory Uncertainty and Compliance Risk

The EU AI Act, emerging sector-specific requirements, and evolving data regulations create a compliance landscape that many organizations are not yet prepared to navigate.

Shadow AI and Unmanaged LLM Use

Unmanaged employee use of AI tools can lead to data leakage, intellectual property exposure, and uncontrolled third-party dependencies across the enterprise.

The Solution

Responsible AI—from strategy through operational governance.

We help bridge the gap between AI ambition and operational accountability. Our advisors combine AI security expertise, governance design experience, and regulatory insight to build AI programs that are both effective and trustworthy.

Risk-based AI classification and tiered governance frameworks aligned with regulatory requirements
Technical security testing across AI and machine learning pipelines, model serving, and API layers
Responsible AI policies designed to support board oversight and stakeholder confidence
Vendor risk assessment methods for third-party AI tools and model dependencies
Ongoing oversight structures, including model monitoring and incident escalation processes

Our Services

AI Security, Strategy, and Governance Services

01 AI Risk Assessment

Enterprise AI Risk Assessment

Systematic evaluation of your AI portfolio against security, privacy, bias, and regulatory risk dimensions. Includes inventory of AI systems, risk classification, and stakeholder accountability mapping.

Deliverables Risk-classified AI inventory, prioritized remediation actions, and a board-ready risk summary.

02 AI Governance Framework

AI Governance & Oversight Program Design

Design and implementation of an AI governance program including policies, review boards, approval workflows, model documentation standards, and ongoing oversight mechanisms.

Deliverables An operating governance structure that improves accountability, auditability, and stakeholder confidence in AI deployment.

03 AI Security Testing

AI/ML Security & Adversarial Testing

Technical assessment of AI system security covering adversarial input testing, prompt injection simulation, model extraction attempts, training data leakage analysis, and API security review.

Deliverables A security assurance report with findings, risk ratings, and recommended hardening controls.

04 Regulatory Compliance

EU AI Act & Regulatory Compliance Advisory

Gap analysis against EU AI Act requirements, NIST AI RMF, ISO/IEC 42001, and sector-specific AI obligations. Preparation support for conformity assessments and regulatory documentation.

Deliverables A compliance readiness roadmap with prioritized obligations, timelines, and supporting documentation templates.

05 AI Strategy

Responsible AI Strategy & Roadmap

Strategic advisory on AI adoption priorities, build vs. buy decisions, vendor evaluation frameworks, and risk-aware implementation roadmaps that align AI investments with business objectives.

Deliverables An executive-approved AI strategy that accelerates adoption while embedding accountability from the outset.

06 AI Vendor Risk

Third-Party & Vendor AI Risk Management

Due diligence and ongoing oversight frameworks for AI vendor relationships, including SaaS AI tools, embedded ML APIs, and foundational model providers. Covers contractual, technical, and operational risk dimensions.

Deliverables A vendor AI risk register with tiered due diligence requirements and recommended contractual controls.

Track Record

Why Organizations Trust Us

QMet in Numbers Est. 2005 Saudi Arabia Bahrain India

01 0+ Years of experience Advising since 2005

02 0+ Industries served Government, telecom, banking & energy

03 0 ISO standards delivered From ISO 9001 to ISO 42001

04 0 Countries Saudi Arabia, Bahrain, Oman, UAE, India & Singapore

How We Work

Our approach to AI governance engagements

Our approach is designed to move efficiently without compromising rigor, delivering governance structures that are practical, scalable, and adoptable.

01 AI Inventory & Classification Catalogue all AI systems, use cases, and risk levels across the organization
02 Risk & Compliance Gap Analysis Assess against regulatory requirements and internal risk appetite
03 Governance Design Build policies, oversight structures, and review workflows tailored to your organization
04 Security Hardening Technical controls, adversarial testing, and monitoring implementation
05 Embed & Enable Train teams, establish ongoing review cadences, and document for regulators

Start Today

AI risk will not wait for your governance model to catch up.

If your organization is scaling AI, now is the time to put the right controls, oversight, and accountability in place.

Schedule a Focused Discussion Speak to an Expert