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AI is reshaping cyber risk: Time to rethink cybersecurity regionally

By Simon Green, President (Asia-Pacific and Japan), Palo Alto Networks | Thursday, January 8, 2026, 10:44 AM Asia/Singapore

AI is reshaping cyber risk: Time to rethink cybersecurity regionally

Zero Trust, enhanced public-private partnerships, and employee training can counter the rapidly evolving AI-driven threats.

The rapid adoption of AI is creating hidden security risks, as seen in incidents of a surge in data leaks, intellectual property disputes, and regulatory exposure.

​As cybercriminals leverage AI to enhance the speed and sophistication of attacks, traditional security tools are no longer sufficient. Attackers can now exfiltrate data three times faster, with a quarter of breaches seeing theft within five hours.

The message is clear: organizations need to build resilient security strategies that keep pace with AI-driven threats. Resilience must be prevention-first, ensuring attackers are stopped before breaches occur. By embedding Zero Trust at the heart of their defenses and establishing strong public-private partnerships, organizations can gain greater visibility into evolving cyber threats.

The growing threat of AI-enhanced attacks

Cybersecurity budgets are growing across organizations, with the largest planned increases in data protection, security software, and application security or identity access. Despite these investments, ransomware threats continue to rise, driven by the emergence of AI-enhanced attacks. One of the newest threats to corporate security is AI-generated insider extortion.

The rise of adversarial AI, where attackers deliberately manipulate AI systems, is exemplified by North Korean actors using AI-generated identities to steal proprietary code from companies. This erodes trust in digital systems and drives operational disruptions across finance and supply chains.

As more employees experiment with GenAI tools without IT oversight, Chief Information Security Officers (CISOs) will be unable to detect proprietary or regulated data that is fed into external AI systems. This expands the “AI attack surface” and leaves most AI models vulnerable to jailbreak attacks that generate harmful content.

Large language models (LLMs) embedded in advanced AI models can be exploited to generate harmful outputs such as malicious code or dangerous instructions. Such unauthorized third-party LLMs may inadvertently expose confidential data in organizations.

Strengthening organizational resilience

Organizations need to re-evaluate their cybersecurity strategies and strengthen defenses for proprietary data and critical systems. For many executives, the biggest challenge is complexity. That is the increasing difficulty of managing security across numerous tools, systems, processes, and cyber threats. We need to move beyond a piecemeal approach to security:

  • Governments in the region can try to get ahead of evolving threats by partnering with more local organizations to ensure products are secure-by-design. These public-private partnerships are vital for building a stronger cybersecurity ecosystem.
  • Zero Trust initiatives cannot stop at the organizational perimeter: they must extend inside, to address advanced malware and AI-driven threats. By continuously verifying every user, device, and application, even within the network, organizations can limit lateral movement and protect critical assets.
  • Equally important is ensuring accountability in the age of AI. Defenders will need to combine AI-driven detection with human oversight to strengthen decision-making. Employees must be empowered through education and strong internal safeguards to uphold a culture of security.

AI security is a shared responsibility, requiring a strong mix of technology, people, and partnerships. By uniting Zero Trust principles with responsible AI governance, organizations can build a resilient security posture.

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