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PodChats for FutureCISO: Why 2026 demands a self-defending network
Manage episode 519380346 series 2912947
By 2026, the paradigm of network defence is set to undergo its most profound shift. For CISOs and Heads of Networking, the escalating velocity of AI-powered threats is rendering human-scale response obsolete.
According to Cybersecurity Ventures, these attacks are projected to cost the world $60 billion annually by 2025, creating pervasive and costly risk.
In this landscape, a self-defending network is no longer a futuristic concept but a strategic imperative. It represents the evolution from human-led, reactive security to an AI-native architecture capable of autonomous threat detection, isolation, and remediation, ensuring business resilience.
In this PodChats for FutureCISO, we are joined by Nick Harders, APJ Systems Engineering Director, HPE Networking, to talk to us about why enterprises must reframe their security strategy around a self-defending network in 2026.
1. What is your definition of self-healing, AI-driven networks?
2. How can we effectively measure the ROI of self-healing, AI-driven networks beyond traditional uptime metrics, perhaps in terms of risk reduction or operational expenditure savings?
3. As we deploy agentic AI for autonomous network operations, what new governance and audit frameworks are required to ensure its decisions remain aligned with business objectives and compliance mandates?
4. In a region with diverse data sovereignty laws, how can we design our autonomous network architecture to ensure data for AIOps and security analytics is processed and stored compliantly across different Asian jurisdictions?
5. With AI-powered threats capable of social engineering and polymorphic code, how do we ensure our AI-native defences can adapt quickly enough without generating excessive false positives that disrupt business?
6. To what extent can we trust predictive insights from our network AI, and what processes are needed for human teams to validate and act upon these proactive recommendations?
7. Given the increased reliance on AI, how do we protect AI's own infrastructure—the data pipelines, models, and control loops—from becoming a primary target for sophisticated threat actors?
8. With the attack surface expanding to include every connected user and device, how does a converged NetSec strategy fundamentally change our approach to implementing and enforcing a zero-trust architecture?
9. As networking and security teams converge, how do we bridge the cultural and skills gap to create unified "NetSec" engineers, and what does their new career path look like?
10. What is the realistic division of responsibility between human teams and AI agents in a security incident response loop, and where should the final 'kill chain' authority lie?
11. What strategic, human-centric skills should we be prioritising in the recruitment and training of our next-generation NetSec professionals?
12. What are your expectations in 2026 and advise for CISOs and CIOs?
468 episodes
Manage episode 519380346 series 2912947
By 2026, the paradigm of network defence is set to undergo its most profound shift. For CISOs and Heads of Networking, the escalating velocity of AI-powered threats is rendering human-scale response obsolete.
According to Cybersecurity Ventures, these attacks are projected to cost the world $60 billion annually by 2025, creating pervasive and costly risk.
In this landscape, a self-defending network is no longer a futuristic concept but a strategic imperative. It represents the evolution from human-led, reactive security to an AI-native architecture capable of autonomous threat detection, isolation, and remediation, ensuring business resilience.
In this PodChats for FutureCISO, we are joined by Nick Harders, APJ Systems Engineering Director, HPE Networking, to talk to us about why enterprises must reframe their security strategy around a self-defending network in 2026.
1. What is your definition of self-healing, AI-driven networks?
2. How can we effectively measure the ROI of self-healing, AI-driven networks beyond traditional uptime metrics, perhaps in terms of risk reduction or operational expenditure savings?
3. As we deploy agentic AI for autonomous network operations, what new governance and audit frameworks are required to ensure its decisions remain aligned with business objectives and compliance mandates?
4. In a region with diverse data sovereignty laws, how can we design our autonomous network architecture to ensure data for AIOps and security analytics is processed and stored compliantly across different Asian jurisdictions?
5. With AI-powered threats capable of social engineering and polymorphic code, how do we ensure our AI-native defences can adapt quickly enough without generating excessive false positives that disrupt business?
6. To what extent can we trust predictive insights from our network AI, and what processes are needed for human teams to validate and act upon these proactive recommendations?
7. Given the increased reliance on AI, how do we protect AI's own infrastructure—the data pipelines, models, and control loops—from becoming a primary target for sophisticated threat actors?
8. With the attack surface expanding to include every connected user and device, how does a converged NetSec strategy fundamentally change our approach to implementing and enforcing a zero-trust architecture?
9. As networking and security teams converge, how do we bridge the cultural and skills gap to create unified "NetSec" engineers, and what does their new career path look like?
10. What is the realistic division of responsibility between human teams and AI agents in a security incident response loop, and where should the final 'kill chain' authority lie?
11. What strategic, human-centric skills should we be prioritising in the recruitment and training of our next-generation NetSec professionals?
12. What are your expectations in 2026 and advise for CISOs and CIOs?
468 episodes
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