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PRODID://NDCP//496147
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DTSTAMP:20260429T212322
VTIMEZONE:America/Chicago
DTSTART:20270308T150000Z
DTEND:20270308T161400Z
UID:496147
SUMMARY:The Controllership Series: The Controller's Role in Artificial Intelligence
LOCATION:Webinar
DESCRIPTION:The Controllership Series: The Controller's Role in Artificial Intelligence\n\n03/08/27 09:00 AM CST\n - 03/08/27 10:14 AM CST\Description:\nHere's a more detailed look at the controller's role in AI:
1. Data Integrity and Quality:
• Controllers are responsible for ensuring the quality and integrity of data used to train and inform AI models.
• They work to establish data governance frameworks, implement data quality initiatives, and ensure data lineage (tracking data from source to downstream systems).
2. Risk Management:
• Controllers assess potential risks associated with AI implementation, including inaccuracies, vulnerabilities, and ethical considerations.
• They help define and implement risk management frameworks for AI, ensuring that AI systems are used responsibly and ethically.
3. Compliance:
• Controllers stay informed about relevant regulations and ensure AI systems are compliant with those regulations.
• They monitor AI systems to ensure they are not violating any laws or policies.
4. Transparency and Auditability:
• Controllers work to ensure that AI decisions are transparent and auditable.
• They establish processes to review AI decisions and identify potential biases or errors.
5. Collaboration and Training:
• Controllers work with IT and business teams to understand AI's capabilities and limitations.
• They provide training to teams on how to use and manage AI tools effectively.
6. Value Creation:
• Controllers can leverage AI to identify areas for automation, improve efficiency, and gain real-time insights into financial operations.
• They can use AI to make more informed decisions and create more strategic recommendations for action.
7. Emerging Role:
• The role of the controller is evolving with the rise of AI, with controllers becoming more hands-on throughout the implementation process.
• They are increasingly seen as catalysts for AI-enabled transformation, helping to identify potential use cases and build confidence in the technology
This course will explore many of these topics.
Speakers:Lynn Fountain\Location:\nWebinar\n\n,
X-ALT-DESC;FMTTYPE=text/html:The Controllership Series: The Controller's Role in Artificial Intelligence
03/08/27 09:00 AM CST - 03/08/27 10:14 AM CST
Description:
Here's a more detailed look at the controller's role in AI:
1. Data Integrity and Quality:
• Controllers are responsible for ensuring the quality and integrity of data used to train and inform AI models.
• They work to establish data governance frameworks, implement data quality initiatives, and ensure data lineage (tracking data from source to downstream systems).
2. Risk Management:
• Controllers assess potential risks associated with AI implementation, including inaccuracies, vulnerabilities, and ethical considerations.
• They help define and implement risk management frameworks for AI, ensuring that AI systems are used responsibly and ethically.
3. Compliance:
• Controllers stay informed about relevant regulations and ensure AI systems are compliant with those regulations.
• They monitor AI systems to ensure they are not violating any laws or policies.
4. Transparency and Auditability:
• Controllers work to ensure that AI decisions are transparent and auditable.
• They establish processes to review AI decisions and identify potential biases or errors.
5. Collaboration and Training:
• Controllers work with IT and business teams to understand AI's capabilities and limitations.
• They provide training to teams on how to use and manage AI tools effectively.
6. Value Creation:
• Controllers can leverage AI to identify areas for automation, improve efficiency, and gain real-time insights into financial operations.
• They can use AI to make more informed decisions and create more strategic recommendations for action.
7. Emerging Role:
• The role of the controller is evolving with the rise of AI, with controllers becoming more hands-on throughout the implementation process.
• They are increasingly seen as catalysts for AI-enabled transformation, helping to identify potential use cases and build confidence in the technology
This course will explore many of these topics.
Speakers:
Lynn Fountain
Location:
Webinar
,
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