How does AI support risk and compliance management?
AI takes over the most time-consuming steps in GRC: finding data, assessing risk, running business impact analysis and preparing documentation. GRC AI Expert runs these analyses as a conversation and leaves decisions and approval to people.
Conversational risk assessment
The Expert runs a 7-step risk assessment covering identification, scoring, mitigation and KRIs, with no forms to fill in. It proposes inherent, residual and target risk ratings for an analyst to approve.
BIA and business continuity
Business impact analysis as a conversation: RTO, RPO, MTPD, impacts, dependencies and minimum viable resources, with reference to DORA Article 11 and ISO 22301.
Compliance and document analysis
The Expert answers questions about regulatory requirements such as DORA and NIS2, and reviews contracts, policies and vendor questionnaires to flag gaps. It draws on regulations and on your own documents, such as your risk methodology.
AI proposes, you decide: keeping AI under control in a regulated organisation
EU-hosted models or your own LLM
Use models hosted in the EU, or connect a model already approved by your organisation.
No training on your data
Your organisation’s data is never used to train models. This is guaranteed contractually and enforced technically.
A person approves every change
Every change the AI proposes waits for a user to accept it.
Full audit trail
Queries, tool calls and reasoning are recorded and ready to show an auditor.
AI in GRC: frequently asked questions
What is AI in GRC?
AI in GRC means applying artificial intelligence to governance, risk and compliance processes: risk assessment, compliance management, business continuity and audit. In practice, it is an assistant that answers questions using data from your GRC system, builds reports and drafts changes for a person to approve.
How does AI support risk management?
It speeds up finding risks in the register, assessing them and reporting on them. In BCMLogic Next, GRC AI Expert runs risk assessments as a conversation, proposes inherent, residual and target ratings, and builds reports with charts, KPIs and a rating matrix.
Does the AI change data in the GRC system on its own?
No. GRC AI Expert drafts a proposed change, such as a new risk or a coordinator assignment. You can refine it in the conversation, and it is only written to the system after a user approves it.
What data does GRC AI Expert use?
Data from the BCMLogic Next platform, such as risks, processes, assets and vendors; your organisation’s own documents, such as your methodology or internal reports; and general knowledge covering regulations and guidelines.
Can AI help with NIS2 and DORA readiness?
Yes, for analysis and documentation. The Expert answers questions about regulatory requirements, runs business impact analysis with RTO, RPO and MTPD, and flags gaps in contracts and policies. It does not replace legal advice.
Is our data used to train AI models?
No. Your organisation’s data is never used to train models, which is guaranteed contractually and enforced technically. You can use EU-hosted models or connect your own language model (Bring Your Own LLM).
How can I check where an AI answer came from, and is that enough for the AI Act?
The AI Audit module shows every query with its user and timestamp, each tool call with its arguments and results, and the full reasoning trail. AI Act compliance is the responsibility of the organisation deploying the AI; human oversight and full interaction logging make those obligations easier to meet.
Can GRC AI Expert make mistakes?
Yes, like any language model. That is why the interface reminds users to verify answers before acting on them, changes require approval, and every reasoning step can be checked in the audit log.
See GRC AI Expert on your own processes
Watch the video, then book a 30-minute demo. We’ll show the Expert live and answer your questions about models, data hosting and the AI Act.