Agentic AI in GRC: From Novelty to Strategic Business Advantage Slide Deck
Join us as we discuss how GRC practitioners can put agentic AI to work to enhance productivity and decision-making without adding complexity.
GRC has already moved from back-office function to business enabler. Now, agentic AI has arrived, and it's changing what GRC can be, not just how fast it runs.
Join GRC 20/20 industry analyst and pundit Michael Rasmussen for a discussion on how GRC practitioners can put agentic AI to work to enhance productivity and decision-making, without adding complexity.
In this session, we'll discuss how AI shifts GRC:
- From fragmented tools to orchestrated intelligence — Manual GRC leaves risk, compliance, audit, and cyber data siloed across disconnected systems. Agentic AI orchestrates that data, workflows, and people so nothing falls through the cracks between cycles.
- From periodic assessments to continuous sensing — Point-in-time reviews leave organizations exposed the moment conditions change. AI-enabled systems of intelligence sense, interpret, and reason across internal and external signals in real time.
- From reactive reporting to predictive response — Manual processes tell you what already happened. Agentic AI moves GRC from generating information to initiating action, recommending or executing responses as risk emerges.
- From bolted-on to built-in AI for true transformation — Applying AI to summarize or accelerate an existing broken process just makes a weak process faster. The real opportunity is redesigning risk and compliance around what continuous data and autonomous agents now make possible
- From assurance-speak to business decision language — Traditional GRC struggles to get in front of leadership until something goes wrong. AI translates risk insight into the language of business decisions, embedding it at the point of investment or strategic commitment.
- From ungoverned automation to built-in governance — As AI moves from advising to acting, practitioners need clear answers on authority, data access, escalation paths, and kill switches. Governance has to be built into the architecture, not bolted on after.
The organizations pulling ahead aren't automating an outdated process. They're asking what risk identification, assessment, and response would look like if designed from scratch around what AI now makes possible.
Speakers:
- Michael Rasmussen, GRC Analyst & Pundit, GRC 20/20 Research, LLC, OCEG™ Fellow
- Patricia McParland, Vice President, Product Marketing, MetricStream
Featured in: AI / Artificial Intelligence , Governance / Strategy , Risk Management , Compliance
