HomeTech PlusArtificial IntelligenceGenerative AI Tools Can Enhance the Efficiency and Insight of ERM Teams

Generative AI Tools Can Enhance the Efficiency and Insight of ERM Teams

Gartner Identifies Five Ways Enterprise Risk Management Teams Can Leverage GenAI

Enterprise risk management (ERM) teams can increase their efficiency and drive better risk insight and mitigation by using generative AI (GenAI) tools in five ways, according to Gartner, Inc.

“GenAI offers ERM teams a unique opportunity to expand their capabilities without significant investments,” said Joel Backaler, Director Analyst in the Gartner Assurance Practice. “By focusing on five quick-win use cases, ERM leaders can increase efficiency by using GenAI as a communicator, a notetaker, a researcher, a librarian, and a trainer.”

These five ERM use cases are areas in which GenAI excels and can add depth to typically resource-constrained ERM teams (see Figure 1).

Figure 1: Five Ways ERM Can Experiment with GenAI
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Source: Gartner (March 2025)

Key Use Cases for Generative AI in ERM:

  1. Communicator:
    GenAI can enhance internal communications by drafting a variety of content, such as emails, risk reports, and policies. This ensures consistent messaging and saves time. For instance, when announcing an enterprise risk assessment, GenAI can craft a professional email tailored to the organization’s tone. ERM leaders can customize drafts for specific audiences, ensuring clarity and engagement.

    “Using GenAI as a communicator allows ERM teams to maintain a consistent voice while freeing up time for more strategic initiatives,” said Backaler.

  2. Notetaker:
    During risk workshops, GenAI-powered transcription bots can capture real-time notes, allowing ERM teams to focus on nonverbal cues and deeper insights. This reduces the need for follow-up questions and enhances participant engagement.

    “GenAI as a notetaker transforms how ERM teams capture and analyze discussions,” stated Backaler. “By automating note-taking, teams can concentrate on the nuances of conversations, leading to more informed risk assessments.”

  3. Researcher:
    GenAI can act as a document-grounded research assistant, sifting through large volumes of text to extract key insights and identify risk patterns. By analyzing recording transcripts from workshops and interview sessions, GenAI can identify areas to enhance risk reporting and inform audit planning.

    “Leveraging GenAI as a researcher enables ERM teams to uncover critical insights more efficiently,” noted Backaler.

  4. Librarian:
    GenAI can streamline information access through a central ERM resource center. Such a hub enables stakeholders to navigate policy documents and historical data via natural language queries, providing on-demand support and reducing direct inquiries to ERM teams.

    “GenAI as a librarian empowers stakeholders with immediate access to essential information,” explained Backaler. “This reduces the burden on ERM teams and ensures that everyone has the resources they need at their fingertips.”

  5. Trainer:
    GenAI-powered training assistants can deliver interactive learning experiences for new risk owners, teaching foundational risk management practices and terminology. This scalable solution addresses high-volume, low-complexity requests, supporting ERM teams in educating new stakeholders efficiently.

    “As a trainer, GenAI can facilitate the onboarding process, ensuring new risk owners are well-equipped to contribute effectively,” said Backaler. “This approach allows ERM teams to scale their training efforts without compromising quality.”

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