As organisations accelerate AI adoption, ensuring these capabilities deliver strategic value without compromising security, privacy, quality, or safety has never been more critical. Our Architecting Secure and Responsible AI Services, aligned with ISO 42001 and the NIST AI Risk Management Framework and grounded in Enterprise Security Architecture principles, are designed to help you harness AI’s potential while confidently protecting data and managing risk.
Develop A Secure & Responsible AI Framework
Security embedded into every stage of AI use, product development, and operations
Self-assess for smooth and problem free AI implementation
AI Readiness Assessment
Review your organisation’s AI Readiness with our free online self-assessment tool.
Take a strategic look at your ability to adopt and benefit from AI deployment and provide key insights into the organisational capability and understanding of what is required to effectively manage AI.
Our AI Readiness Assessment will provide you with a report across 6 key areas:
- Commitment
- Architecture
- Capability
- Competence
- Scope & Value
- Obligations
AI Project Success factors
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Strategic Security Alignment
Ensure AI initiatives are tightly aligned with enterprise goals and ISO 42001 requirements, transforming AI from isolated experimentation into a secure, responsible, and strategic business asset.
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Consistency & Scalability for AI
Establish cohesive frameworks, reusable patterns, and operating models that ensure AI security and governance are applied consistently across the enterprise, delivering both scalability and efficiency.
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Proactive AI Risk Mitigation & ROI Assurance
Embed AI governance to manage risks from both threat and opportunity perspectives, while establishing clear accountability and measurable return on investment through value-chain alignment.
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Trusted Data & Information Architecture
Develop a logical information architecture and design patterns that guarantee the right data sources, integrity, and protection are in place — addressing a leading cause of AI project failure and enabling effective, fair, and explainable outcomes.
Comprehensive, Business-Aligned AI Frameworks
AI Security Architecture, Agentic and Product Architectures, through to AI Guardrails and Governance, all grounded in Enterprise Security Architecture Principles with SABSA.
Cohesive, Consistent & Trusted AI Architecture
By embedding security into every stage of AI use, product development, and operations, we enable your organisation to accelerate strategic objectives, strengthen trust, improve efficiency, and deliver secure and responsible AI products and services with confidence.
Secure & Responsible AI Services
Overview
The AI Architecture Accelerator is a fast-track engagement designed to rapidly establish the foundations of secure and responsible AI. DLC consultants work alongside enterprise representatives and key stakeholders to create a business-aligned AI security architecture, directly connecting AI initiatives to strategic objectives and risk context.
Through interviews, analysis, and collaborative workshops, we connect AI initiatives directly to your strategic objectives and risk context, providing clarity, traceability, and confidence in your AI journey.
The AI Accelerator delivers:
- A high-level AI security architecture aligned with business goals
- An AI threats and opportunities assessment
- A baseline AI Policy and Ethical Statement
- A baseline AI Management Plan in accordance with ISO/IEC 42001
Outcomes
- Business-Aligned AI Strategy: Establish a clear AI architecture aligned to business objectives, value chains and strategic priorities from the outset.
- Accelerated AI Readiness: Rapidly define the foundational architecture, governance and management artefacts needed to confidently commence AI initiatives.
- Early AI Risk Visibility: Identify key AI threats, opportunities, dependencies and governance considerations before significant investment is made.
- Executive Alignment & Decision Confidence: Create shared understanding across business, technology and risk stakeholders through a common architectural view of AI.
- Foundation for Secure & Responsible AI: Establish baseline AI policies, ethical principles and ISO 42001 management planning to enable trusted AI adoption.
- Reduced Project Failure Risk: Improve the likelihood of successful AI delivery by establishing architecture, governance and accountability before implementation begins.
Overview
The AI Architecture & ISO 42001 AI Management System (ISO AIMS) builds on the Accelerator or is delivered as a standalone service, providing the full architecture, governance, and operating model needed to embed secure, responsible, and business-aligned AI across the enterprise.
Key artefacts delivered as part of the AI Management System Service, aligned with ISO 42001, include AI Security Architectures, AI governance and accountability frameworks, AI control strategies, and AI Operating Models. Through conceptual and logical AI architectures aligned to business value chains, the service enables secure, responsible, and business-aligned AI adoption across the enterprise.
The service also establishes governance processes, Delegations of AI Authority (DOA), and RACI frameworks to support accountable decision-making, AI risk ownership, transparency, and control effectiveness, while ensuring the right information and data architectures are in place to support effective AI operations.
Outcomes
- Enterprise-Wide AI Governance: Establish a comprehensive AI Management System that embeds governance, accountability and decision-making across the AI lifecycle.
- Business-Aligned AI Architecture: Connect AI capabilities, data, controls and operating models directly to business objectives, value chains and measurable outcomes.
- ISO 42001 & Regulatory Readiness: Implement governance and management processes aligned with ISO 42001 and evolving AI regulatory expectations.
- Operational AI Management: Define the operating model, Delegation of AI Authority (DOA), RACI structures and management processes required to operate AI at enterprise scale.
- Consistent & Scalable AI Adoption: Develop reusable architecture patterns, governance frameworks and security controls that enable AI to scale consistently across the organisation.
- Trusted & Responsible AI Capability: Build organisational capability to securely govern, manage and continually improve AI systems while strengthening trust with customers, regulators and stakeholders.
Overview
Our AI Audit Assessment Service provides a structured and evidence-driven assessment of AI governance, processes, controls, and operational practices across the enterprise AI lifecycle. Underpinned by SABSA Enterprise Security Architecture principles and aligned with ISO/IEC 42001, ISO 19011, the NIST AI Risk Management Framework, and ISACA AI Audit methodologies, the service enables organisations to evaluate whether AIsystems and supporting management processes are secure, explainable, resilient, compliant, and operating in alignment with business objectives and risk tolerance.
The service assesses AI governance maturity, AI-enabled business processes, AI inventories, control frameworks, model and data supply chains, operational controls, workforce impacts, and AI-specific security and risk management practices. Through structured controls assessment, evidence validation, process maturity review, explainability assessment, and gap analysis, we help organisations identify weaknesses, validate control effectiveness, and strengthen governance, transparency, operational resilience, and ongoing assurance capabilities. The assessment approach supports both executive oversight and practical operational improvement, enabling organisations to establish repeatable and scalable AI assurance practices.
The AI Auditing Assessment Service can be delivered as an assessment or as a formalised and comprehensive ISO42001-aligned audit.
Outcomes
- Independent AI Assurance: Establish confidence that AI systems, governance processes, and operational controls are secure, effective, and operating responsibly.
- Governance & Regulatory Alignment: Align AI operations and management practices with ISO/IEC 42001, ISO 19011, NIST AI RMF, ISACA AI Audit methodologies, and emerging regulatory obligations.
- Enhanced AI Visibility & Traceability: Gain structured insight into AI applications, models, datasets, supply chains, AI inventories, business dependencies, and operational ownership.
- Improved AI Control Effectiveness: Assess the design and operational effectiveness of AI guardrails, monitoring, observability, lifecycle management, and AI-specific security controls.
- Responsible AI & Explainability Assessment: Evaluate AI systems for explainability, transparency, fairness, accountability, safety, hallucination management, and harmful output risks.
- Actionable Improvement Roadmap: Deliver prioritised recommendations to strengthen AI governance maturity, operational resilience, risk management, and continuous assurance capabilities over time.
Overview
Our AI Red Team Technical Assessment Service provides a baseline model performance and structured adversarial assessment of AI systems to evaluate their security, robustness, resilience, and technical control effectiveness. Underpinned by SABSA Enterprise Security Architecture principles and aligned with emerging AI security practices, OWASP guidance for LLMs, and MITRE ATLAS threat techniques, the service helps organisations identify vulnerabilities, attack paths, and operational weaknesses across AI models, agents, datasets, prompts, APIs, integrations, and supporting infrastructure.
The baseline performance activity compares the performance of the AImodel against a range of recognised benchmarks and shows how it stacks up against a number of leading SLM and LLM models. All testing can be performed through multiple languages.
The adversarial assessment activity uses controlled adversarial testing, attack simulation, and technical validation techniques to assess susceptibility to prompt injection, jailbreaks, harmful outputs, hallucinations, insecure integrations, model manipulation, data leakage, and supply chain compromise. Through structured test plans, attack execution, guardrail validation, and technical risk analysis, we provide actionable recommendations to strengthen AI defensive posture, improve operational resilience, and support the secure deployment of AI capabilities at enterprise scale.
Outcomes
- AI Threat & Vulnerability Visibility: Identify weaknesses, attack paths, and security exposures across AI models, agents, datasets, APIs, and supporting infrastructure.
- Improved AI Defensive Resilience: Validate the effectiveness of AI guardrails, monitoring, filtering, observability, and security controls against adversarial attack scenarios.
- Reduced AI Exploitation Risk: Assess susceptibility to prompt injection, jail breaks, harmful outputs, hallucinations, data leakage, model manipulation, and supply chain compromise.
- Secure AI Lifecycle Validation: Evaluate the security posture of AI pipelines, integrations, model deployment processes, and operational environments. Available in multiple languages.
- Enhanced Trust & Assurance: Increase confidence that AI systems operate safely, securely, and responsibly under real-world attack conditions.
- Actionable Technical Remediation: Deliver prioritised technical findings and remediation recommendations to strengthen AI security maturity and operational resilience over time.
Our AI Guardrails Assessment Service provides a structured architectural definition of guardrail requirements as a controls component of the business enterprise security architecture, an assurance assessment of existing guardrail capability, and/or a deployment service for the introduction of guardrails. The service involves establishing the guardrail architecture, control functionality, and operational and cost performance requirements based on delivering mitigation for relevant AI vulnerabilities, informed as appropriate by our AI Red Team Assessment reports. Guardrails can be architected as part of business applications or as stand-alone proxy services.
Baseline guardrail functionality includes detection of prompt injections, PII and toxicity on input prompts and monitoring for toxicity, harm, PII and hallucinations on output responses. Additional standard guardrails can be applied for a wide range of issues, including topic limitations, company and subject constraints. We can also assist with the development of customised guardrails. The service involves architecting, designing, and performing both comparative and performance assessments of the candidate guardrail solutions. We have experience in supporting the provision of a number of commercial AI secure proxy and guardrail solutions, as well as developing custom guardrail deployments.
Outcomes
- Guardrail Architecture. Enterprise security architecture viewpoint on guardrails as an enterprise capability, including design patterns for use and monitoring.
- Guardrail Design. Solution guardrail design for the consumption of enterprise guardrail capability and integration into enterprise guardrail continuous assurance.
- Attack Prevention. Guarding the AI model from malicious prompts will limit the opportunities for adversaries to manipulate the AI model’s instructions to gain control or steal information.
- Data Breach Prevention. Detection and prevention of PII leakage will help avoid data breaches from AI models.
- Reputational Integrity. Ensuring the AI model does not respond in harmful, toxic, or hallucinatory ways will go a long way to maintaining the reputation of the business and demonstrating due diligence in its use of AI.
- Continuous Assurance. Enterprise-level assurance monitoring of guardrail operation to provide observability and ensure effective guardrail operation against validation datasets.
- Drift Detection. Early detection of operational drift, which reduces the effectiveness of guardrails, enables timely review and realignment.
Simplify AI
Decision Making
QNOUS
Our AI advisory services are powered by Qnous: A SaaS solution that shifts the cybersecurity paradigm by challenging core beliefs and driving better decision making.
- Model the security posture of your organisation and create a single source of truth
- Leverage a dynamic visualisation engine to render information more accessible to stakeholders across the enterprise
- Take advantage of automated insights to query the data and create valuable viewpoints to simplify security decisions
- Create what-if scenarios to identify the optimum way to act on risk and opportunities in the face of uncertainty
- Use dashboards and bespoke reporting mechanisms to communicate the readiness of operational resilience to all possible audiences
- Out-of-the-box compatibility with ISO 42001
Ask Us How
Get in touch and find out how David Lynas Consulting can accelerate your AI capability.
LEARN SABSA
from the
source.
Our SABSA Training programme is led by David Lynas: co-author of SABSA, CEO of the SABSA Institute, and principal author of the SABSA Institute intellectual property. Quite simply there is no better source of SABSA Education!
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Flexible Learning
In-person classroom, virtual classroom or private in-house training to suit your needs.
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Training Schedule
View upcoming training dates in a region or timezone that's right for you.
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SABSA Certification
Advance your cybersecurity career with certification in a framework that equips cybersecurity professionals with skills that enable an ever-changing business environment.
Insights &
Resources
Architecting Secure & Responsible AI Webinar: Achieving Valuable and Responsible AI – 25 June 2026
In this webinar, we explore the reasons why architecting our AI solutions using SABSA is the key to business success in adopting AI as a fit-for-purpose capability for the enterprise.
R101 – The SABSA Matrices 2018 Release Notes
An update to the SABSA Matrix™ and the SABSA Management Matrix™ in 2018 and an analysis of the changes made in that update.