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AI Red Teaming & ML/LLM Testing

Assurance that AI systems behave as intended in practice
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Independent testing to expose AI risk, misuse and failure before it matters

AI systems behave differently under pressure. What looks safe in development can fail, mislead or be misused in the real world, often in ways teams did not anticipate.

GRC Solutions provides AI red teaming, machine learning (ML) testing and large language model (LLM) testing to help organisations understand how their AI systems can fail, be exploited or behave unexpectedly, and to evidence that governance and controls work in practice. Our testing is aligned with recognised industry methodologies, including the OWASP Top 10 for LLMs, to ensure coverage of realistic and emerging AI risk scenarios.

This is not theoretical AI ethics. It is hands-on, adversarial testing designed to improve trust, resilience and accountability.

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Who is AI red teaming for?

We typically support mid-sized and enterprise organisations where AI failure would have material regulatory, reputational or commercial impact.

Our AI red teaming and ML/LLM testing services are designed for organisations that:

Deploy AI or GenAI in production or customer-facing environments
Use or have recently implemented AI in high-risk, regulated or safety-critical use cases
Require assurance that implemented or modified AI guardrails operate effectively in practice
Are preparing for AI governance standards such as ISO 42001
Want independent evidence of AI risk management and control

Why use AI red teaming?

Traditional testing checks whether AI works as designed.
AI red teaming asks a more important question: how could this system fail, be misused or cause harm?

AI red teaming and ML/LLM testing helps organisations to:

Identify unintended behaviour, bias and misuse scenarios
Test AI controls under adversarial and edge-case conditions
Understand real-world AI risk, not just theoretical risk
Validate governance, oversight and accountability mechanisms
Build confidence with regulators, clients and stakeholders

What does AI red teaming cover?

GRC Solutions delivers structured, adversarial AI testing across the AI lifecycle, including:

Identifying realistic threat, misuse and failure scenarios based on how AI systems are actually used.

Testing ML models for bias, robustness, drift, data sensitivity and unintended outcomes.

Assessing LLMs for prompt injection, hallucination, data leakage, misuse and unsafe outputs.

Simulating malicious, negligent or unexpected user behaviour to challenge AI safeguards.

Testing whether policies, guardrails, monitoring and human oversight operate effectively in practice.

Clear, structured reporting that supports governance, ISO 42001 alignment and regulatory scrutiny.

Who can deliver AI red teaming?

Effective AI red teaming requires more than technical testing skills.
GRC Solutions brings together AI risk expertise, assurance discipline and governance insight to deliver testing that is credible, defensible and decision-ready.
Our teams understand:

  • How AI systems behave in real environments
  • How regulators and auditors assess AI risk
  • How governance frameworks such as ISO 42001 are evidenced in practice

That means findings are not just technically interesting, they are actionable and accountable.

GRC Solutions AI red teaming services

Our AI red teaming services are flexible and tailored to AI maturity, risk profile and regulatory context.

AI red teaming engagements

Targeted adversarial testing designed to surface real-world AI risk.

ML and LLM testing

Hands-on testing of machine learning models and large language models in production or pre-production.

AI governance validation

Testing AI controls, oversight and accountability mechanisms aligned to ISO 42001.

Pre-deployment AI assurance

Independent testing before AI systems go live or scale.

Post-incident AI analysis

Root cause analysis following AI failures, misuse or unexpected behaviour.

Ongoing AI risk testing programmes

Repeatable testing to support continuous AI governance and improvement.

Why GRC Solutions?

Most AI testing focuses on tools. GRC Solutions focuses on trust, governance and accountability.

Adversarial by design

We deliberately challenge assumptions, safeguards and controls, not just functionality.

Governance-led testing

Our testing aligns to governance frameworks, not just technical checklists.

Regulator and client ready

Outputs are designed to stand up to regulatory, audit and client scrutiny.

Practical, not performative

No hype, no theatre. Just evidence-based insight that improves decision-making.

AI red teaming FAQs

AI red teaming is an adversarial testing approach that explores how AI systems can fail, be misused or behave unexpectedly under real-world conditions.

No. AI red teaming supports security, risk, compliance, legal and AI teams by providing evidence of AI risk and control effectiveness.

No. It complements traditional testing by focusing on misuse, edge cases and governance failure rather than expected behaviour.

ISO 42001 does not mandate specific testing methods, but AI red teaming is an effective way to evidence that AI risks are identified, managed and monitored in practice.

AI red teaming can be used pre-deployment, during scaling, after incidents, or as part of ongoing AI governance.

Assess your AI risk exposure

If you are unsure how your AI systems would behave under misuse, pressure or unexpected conditions, a short AI red teaming scoping discussion is often the fastest way to gain clarity.
This initial assessment helps organisations to:

  • Identify which AI systems carry the highest risk
  • Understand where ML or LLM testing adds the most value
  • Decide whether full AI red teaming is proportionate and necessary
  • Prioritise next steps aligned to governance and regulatory expectations

Request an AI red teaming scoping discussion