Research, red-teaming and emerging risk
Adversarial testing, emerging framework evaluation and applied research — published where the work is ready to share.
Enterprise AI Lab
The Enterprise AI Lab is EAIC's internal research function. We use it to stay ahead of the threat and compliance landscape — running adversarial testing on AI systems, evaluating emerging governance frameworks before they become mandatory, and publishing our findings where the work is ready to share.
Current work includes red-teaming methodology for high-risk AI systems under Article 9 of the EU AI Act, evaluation of ISO 42001 certification pathways for mid-market regulated firms, and developing a risk-adjusted ROI framework for agentic AI systems that sits outside existing governance models.
Research outputs are published here and via our Thought Leadership channel. Organisations interested in commissioning applied research or red-teaming engagements should contact us through Advice & Guidance.
Current research areas
Adversarial testing frameworks for high-risk AI systems under EU AI Act Article 9 obligations. Establishing what "adequate testing" means in practice for regulated FS deployments.
Active
Developing governance and oversight models for autonomous AI agents that operate outside the human-in-the-loop frameworks current regulations assume. Risk-adjusted ROI modelling for agentic deployments.
Active
Mapping ISO 42001 requirements against the Sentinel governance programme. Building an evidence bundle framework that supports certification without duplicating work already done in a Sentinel engagement.
Ongoing
Evaluation and improvement of AutoDiscover methodology. Testing detection rates across cloud platforms, API gateways and OAuth permission graphs. Publishing findings on shadow AI prevalence in regulated FS.
Ongoing
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