Heimdal Survey: Executives Four Times More Confident About AI Risk Than The Teams Managing It

2026-06-17 · Source: HackerNoon · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy · Depth: Intermediate, short

Summary

Heimdal's "The State of AI Risk Management in 2026" report, based on a May 2026 survey of 1,000 IT professionals in the UK and US, reveals a significant confidence gap regarding AI risk. In the US, 29% of executives believe AI risk is under control, compared to only 7% of practitioners. A similar disparity exists in the UK, with 18% of executives confident versus 11% of practitioners. The research indicates AI adoption has outpaced security controls by roughly two to one, with ChatGPT present in 72% of UK and 69% of US IT environments, and Microsoft Copilot in 68% of UK and 59% of US. Only about 4 in 10 teams rate their security stack as AI-ready. Intriguingly, concern about data leakage rises with visibility into AI use, reaching 56% in UK and 59% in US teams with full visibility. The report also notes high operational load, with nearly three-quarters of teams losing at least a quarter of their week to low-value work, yet overloaded teams are more optimistic about AI's potential to ease their burden.

Key takeaway

For IT leaders overseeing AI adoption, recognize that your team's confidence in AI risk management likely exceeds reality. Prioritize closing the significant gap between executive perception and practitioner concerns by implementing robust technical controls and comprehensive procurement reviews for all AI services. You must establish clear guardrails and maintain a current inventory of both sanctioned and unsanctioned AI tools to prevent data leakage and ensure responsible AI use, rather than relying solely on policy.

Key insights

Executives significantly overestimate AI risk control compared to practitioners, as AI adoption outpaces security measures.

Principles

• Misplaced confidence amplifies security risks.
• Increased visibility often reveals greater concern.
• AI policies alone do not ensure oversight.

Method

Treat AI as core IT estate, applying scrutiny like critical suppliers. Implement procurement review, data-handling terms, tool inventory, and technical controls for access, execution, action chains, and privilege.

In practice

• Inventory all sanctioned and unsanctioned AI tools.
• Implement technical controls for AI access.
• Review data-handling terms for AI services.

Topics

• AI Risk Management
• Cybersecurity
• AI Adoption
• Data Leakage
• Security Controls
• Executive Confidence Gap

Best for: CTO, VP of Engineering/Data, Director of AI/ML, IT Professional, Executive, AI Security Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by HackerNoon.