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Reducing the Evidence Collection Tax Through Agentic Audit Automation

Reducing the Evidence Collection Tax Through Agentic Audit Automation

1 CPE

Access until 16 Jul 2027

Online•English

Description: Audit and compliance teams spend too much time manually collecting evidence. This session examines how agentic AI is shifting the balance of where we spend our time by transforming evidence collection, and what we must understand before trusting it. We explore three critical dimensions: hallucination risk that can make AI-collected evidence unreliable; cryptographic chain of custody as an architecture for defensible evidence integrity; and continuous controls monitoring as the shift from point-in-time snapshots to real-time assurance. Attendees leave with a practical framework for governing AI evidence collection and five diagnostic questions to apply immediately in their organizations. Speaker: Sandy Buchanan, P.Eng, CISSP, CISM, CISA, Lead Product Manager, Wolters Kluwer Access until: 12 pm CT on 16 July 2027

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Description:

Audit and compliance teams spend too much time manually collecting evidence. This session examines how agentic AI is shifting the balance of where we spend our time by transforming evidence collection, and what we must understand before trusting it. We explore three critical dimensions: hallucination risk that can make AI-collected evidence unreliable; cryptographic chain of custody as an architecture for defensible evidence integrity; and continuous controls monitoring as the shift from point-in-time snapshots to real-time assurance. Attendees leave with a practical framework for governing AI evidence collection and five diagnostic questions to apply immediately in their organizations.

Speaker: Sandy Buchanan, P.Eng, CISSP, CISM, CISA, Lead Product Manager, Wolters Kluwer

Access until: 12 pm CT on 16 July 2027

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Description: Audit and compliance teams spend too much time manually collecting evidence. This session examines how agentic AI is shifting the balance of where we spend our time by transforming evidence collection, and what we must understand before trusting it. We explore three critical dimensions: hallucination risk that can make AI-collected evidence unreliable; cryptographic chain of custody as an architecture for defensible evidence integrity; and continuous controls monitoring as the shift from point-in-time snapshots to real-time assurance. Attendees leave with a practical framework for governing AI evidence collection and five diagnostic questions to apply immediately in their organizations. Speaker: Sandy Buchanan, P.Eng, CISSP, CISM, CISA, Lead Product Manager, Wolters Kluwer Access until: 12 pm CT on 16 July 2027

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