In this post: We unpack the three dominant categories of AI-related risk — cybersecurity and data integrity, integration with existing operations, and talent readiness — based on global survey data. We also include a set of leadership-driven questions to guide internal conversations.

Introduction

As artificial intelligence (AI) moves from isolated pilots to enterprise-wide deployment, boards and executives face growing pressure to manage not just the potential — but also the risk.

The 2026 Executive Perspectives on Top Risks and Opportunities report — developed by the ERM Initiative at NC State University’s Poole College of Management and global consulting firm Protiviti — identifies a critical shift: leaders are no longer viewing AI as a single risk or opportunity, but rather as a complex mix of risk categories requiring cross-functional attention.

This insight reframes how boards, CROs, CIOs, and other decision-makers should engage with AI in the year ahead.

AI Risk Categories

#1: Cybersecurity and Data Integrity

AI introduces new and rapidly evolving cybersecurity exposures. Survey respondents ranked “risks related to data required for AI use and cybersecurity exposure” as the top AI-related risk globally.

These concerns include:

• Model poisoning and data leakage during training or inference
• Insecure use of third-party AI tools
• Privacy vulnerabilities and compliance concerns
• Expanded attack surfaces not covered by existing frameworks

“No AI deployment can succeed without addressing the data lifecycle from acquisition to decommissioning.”
— 2026 Top Risks Report, p. 16

Tool: Are you asking the right questions about how AI is expanding our cybersecurity and data risk exposure?
Explore 3 key questions for executive teams ›

#2: Integration with Systems and Workflows

AI’s value can only be realized when integrated into core business operations — but that’s also where risks multiply. Poor integration leads to:

• Operational disruption
• Low adoption
• Poor ROI
• Uncoordinated governance

Across roles and industries, integration with existing technologies, processes, and the workforce was ranked among the most pressing AI risks.

Tool: Is your organization ready to scale AI in a way that aligns with enterprise systems, governance, and strategy?
Explore 3 key questions to assess AI integration risk ›

#3: Talent Readiness

Without talent readiness, even the best AI systems will underperform. The report highlights several interrelated concerns:

• Lack of upskilling and reskilling
• Difficulty attracting and retaining AI-capable talent
• Resistance to change among employees
• Erosion of leadership pipelines due to shifting skill needs

“The bottom line: Properly implemented, AI becomes an extension of the workforce.”
— 2026 Top Risks Report, p. 15

Tool: Do you have the right leadership, skills, and culture in place to support responsible AI adoption?
Explore 3 key questions on talent readiness for AI ›

Tool: Questions to Guide a Leadership Conversation on AI Risk

Use these questions to prompt discussion with your executive team, CIO, CRO, CHRO, or board.

Cybersecurity and Data Integrity

1. How confident are we in the security and privacy of the data being used to train and operate AI tools?
   Are we evaluating exposure risks at each stage of the AI lifecycle?
2. Do we understand the cybersecurity implications of third-party AI platforms we’ve adopted — or plan to adopt?
   Are vendors required to meet our enterprise risk and compliance standards?
3. Is our AI usage aligned with our data governance, regulatory, and risk appetite frameworks?
   Who owns accountability for monitoring that alignment?

Integration with Systems and Workflows

4. How are we ensuring that AI tools integrate with — rather than disrupt — existing processes and technologies?
   Are we proactively addressing operational friction?
5. Are we tracking which business units are experimenting with AI independently?
   Do we have governance in place to manage decentralized AI deployment?
6. What metrics are we using to evaluate the ROI and risk exposure of AI integration?
   Do we have clear criteria for scaling or retiring AI tools?

Talent Readiness

7. Do we have the talent and skills needed to support safe, strategic use of AI across the enterprise?
   Where are the biggest gaps — and how are we closing them?
8. How is AI adoption impacting morale, retention, or employee trust?
   Are we monitoring cultural risks alongside technical ones?
9. Is talent readiness part of our ongoing enterprise risk monitoring and reporting process?
   What is ERM’s role in supporting leadership development and upskilling efforts?

Read the Full Report

Access the full 14th Annual Top Risks and Opportunities Report for additional data, industry comparisons, and full risk rankings.

About the Experts Behind the Report

The 2026 Executive Perspectives on Top Risks and Opportunities report was developed by the ERM Initiative at NC State University’s Poole College of Management, in collaboration with global consulting firm Protiviti. The report is authored by:

• Mark S. Beasley, PhD – Director, ERM Initiative; Alan T. Dickson Distinguished Professor of Accounting
• Bruce C. Branson, PhD – Associate Director, ERM Initiative; Professor of Accounting
• Donald P. Pagach, PhD – Director of Research, ERM Initiative; Professor of Accounting