KBTG Unveils 8 AI Risks and Governance Framework for 2026
KBTG's Chatchawat Asavarakwong cites Gartner data showing only 7% of global firms are AI ethics leaders, outlining 8 key risks and mitigation strategies.
Stock photo for illustration only, not from the actual event
- Only 7% of global organizations are AI ethics leaders, with 31% having robust governance systems.
- Chatchawat Asavarakwong notes AI has shifted from a tech project to a core business competitive advantage.
- Highlights 8 AI risks for organizations to review using international standards like ISO/IEC 42001.
- Outlines a 6-step AI development lifecycle alongside AI Red Teaming for enhanced security.
Only 7% of organizations worldwide are recognized as leaders in AI ethics readiness, while just 31% have established robust governance systems. According to Gartner research, this data reflects a global reality where technology has outpaced regulatory governance by several steps.
Chatchawat Asavarakwong, Vice Chairman and Group Chief Information Security Officer at KBTG, highlighted these figures during the session 'AI with Accountability: Building Trust in the Intelligent Enterprise' at Techsauce Global Summit 2026. He emphasized that organizations must shift their fundamental question from how to adopt AI faster to how to use AI responsibly and reliably.
Stock photo for illustration only, not from the actual event
The rapid proliferation of AI is driven by executives and employees utilizing the technology for document drafting, report summaries, marketing campaigns, and customer service operations. Generative AI has become the fastest-growing technology in history within a span of just three years, yet the pressing question remains: how much can we trust it?
When organizations allow employees to use public AI tools, risks multiply significantly, especially in customer-facing roles. If an AI system fails to understand context and delivers erroneous responses to clients, the resulting business liability can quickly escalate from a technical glitch into a major enterprise risk.
"Organizations must shift their fundamental question from how to adopt AI faster to how to use AI responsibly and reliably."
To help organizations self-assess, Chatchawat outlined 8 critical AI risks and recommended adopting established international standards as a baseline, such as the EU AI Act, ISO/IEC 42001, and the NIST AI Risk Management Framework, alongside regional guidelines from Singapore's CSA and Thai agencies including ETDA, NCSA, and the Bank of Thailand.
Adopting established international standards helps organizations bridge regulatory and operational gaps. Standards such as ISO/IEC 42001 provide a vital milestone for establishing verifiable AI management systems amidst rapid technological evolution.
Stock photo for illustration only, not from the actual event
For practical implementation, organizations must establish an AI governance framework covering principles, risk management, and the complete AI lifecycle. This includes a 6-step operational process ranging from requirement planning and Proof of Concept (POC) to deployment, performance monitoring, and systematic retirement.
Source: Techsauce
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