ACPEN: The Risks of Artificial Intelligence - Part 2

Overview

As artificial intelligence (AI) becomes deeply integrated into business operations and decision-making, organizations must recognize that effective oversight extends beyond technical safeguards.The governance, risk and control (GRC) responsibilities of AI also carry a cultural dimension requiring alignment with corporate ethical values ethical principles and accountability structures.Cultural governance emphasizes leadership commitment, employee engagement and cross-function ownership of AI practices to ensure trust and transparency.  AI-related risks – ranging from bias and ethical concerns to regulatory compliance, reputational exposure and operational vulnerabilities necessitate robust control frameworks and proactive mitigation strategies.   These include governance structures, policies, risk assessments, transparency measures, and continuous monitoring.  By embedding cultural governance and mitigation responsibilities into enterprise AI initiatives, organizations can responsibly harness innovation while safeguarding stakeholders, protecting reputation and ensuring sustainable long-term value.

Note:  This is Part 2 in a two-part series on the risks of AI

Highlights

• Society and cultural risks of AI
• Governance and control risks of AI
• Mitigation and Responsible AI

Prerequisites

Risks of AI - Part 1

Designed For

Accountants, Auditors, Internal Auditors & Finance Professionals  

Objectives

Societal and Cultural Risks

• Explain how AI may exacerbate economic and social divides
• Identify the role of AI in spreading disinformation
• Evaluate the impact of AI on trust and credibility
• Discuss cultural and geopolitical risks of AI dominance

Governance and Control Risk

• Understand how regulation lags behind AI development
• Identify corporate and geopolitical risks of AI dominance
• Evaluate AI’s role in cybersecurity threats
• Discuss long-term debates around AI alignment and safety

Mitigation and Responsible AI

• Apply ethical frameworks to assess AI adoption
• Recommend governance structures for AI oversight
• Design approaches to keep human judgment central
• Propose workforce strategies for adapting to AI-driven change

Preparation

Basic Understanding of Artificial Intelligence