The boundary between IT risk and business risk has collapsed, accelerated by AI’s deep integration into operations, decision-making, and customer engagement. AI systems now influence supply chains, financial controls, hiring decisions, and customer interactions, often with minimal human intervention.
As a result, CISOs are no longer responsible only for securing systems. They are responsible for ensuring that AI-augmented business processes remain trustworthy, available, and controllable under stress. In practice, CISOs have already begun operating as chief resilience officers.
Vice President of Sales, India, SAARC, SEA & ANZ
Fortinet
This evolution reflects reality. AI increases speed, scale, and dependency. In that environment, when failures occur, they propagate faster and farther. So in 2026, CISOs will need to assume that disruption will involve AI-enabled components, whether through compromised models, poisoned data, manipulated agents, or automated misuse. Success will be measured by how well organizations absorb and contain those failures.
Strategy One: Build for Business Continuity in an AI-Augmented Enterprise
Large-scale disruption is not hypothetical. AI increases both the likelihood and the blast radius of failure. Because of this, business continuity planning will need to evolve accordingly.To start, CISOs must redefine the organization’s Minimum Viable Business (MVB) with AI dependencies in mind. Which AI-driven systems are essential to keep operating? Which automated decisions need to be paused or overridden during an incident? What happens if a model, dataset, or agent becomes unavailable or untrustworthy?
Resilience in 2026 means understanding not just how systems fail, but how AI amplifies those failures. Traditional continuity plans rarely account for AI behaviour under stress, and that must change. Similarly, tabletop exercises must now include AI failure scenarios, corrupted data pipelines, and autonomous actions that require rapid human intervention.
Strategy Two: Treat AI as a Governed, High-Risk Capability
AI is increasingly being embedded across the enterprise, often outside traditional security visibility. Marketing teams use generative tools. Developers integrate external models. Business units deploy automation to accelerate decisions. Each of these introduces risk.
AI systems can leak sensitive data, be manipulated through adversarial inputs, or be coerced into unsafe behaviour through prompt injection. And agentic AI introduces additional complexity, as autonomous agents interact with other systems and identities without direct human oversight.
In 2026, CISOs will need to treat AI as a high-risk capability that demands explicit governance. That includes defining ownership, enforcing access controls, securing training and inference data, and monitoring AI behaviour in production. AI should be subject to the same scrutiny as any system capable of materially impacting the business.
Used responsibly, AI strengthens resilience by accelerating detection and response. Used without governance, it becomes a force multiplier for attackers.
Strategy Three: Harden Identity for Humans, Machines, and AI Agents
Identity has become the control plane for modern environments, and AI is accelerating the complexity of those environments. The “2026 CISO Predictions” highlighted non-human identity as a growing source of systemic risk. A single compromised machine or agent identity can cascade across environments in seconds. Today, non-human identities already outnumber human users in many organizations. AI agents add a new layer by authenticating, querying systems, and taking action at scale.
In an AI-driven enterprise, identity compromise is not just a security incident. It is a resilience failure. CISOs need to ensure that identity controls are consistent across users, machines, APIs, and AI agents, with continuous verification and least-privilege enforcement. At the same time, identity governance must also assume automation, scale, and speed.
Strategy Four: Strengthen Collaboration as AI Blurs Traditional Boundaries
AI dissolves traditional organizational boundaries. Decisions once made by individuals are now distributed across systems, teams, and automated workflows. During incidents, this complexity can slow response if roles and responsibilities are unclear.
No organization can build AI resilience in isolation. Instead, resilience depends on collaboration. To achieve this, CISOs need to align security, IT, data science, legal, risk, and executive leadership on shared assumptions about AI risk and response. And externally, collaboration with peers, partners, and public-sector organizations becomes even more critical as AI-enabled threats scale globally.
Strategy Five: Assume AI-Accelerated Disruption and Stay Adaptive
AI compresses timelines. Attackers adapt faster. Mistakes propagate faster. Regulatory expectations evolve faster. In this environment, the appropriate mindset is to assume AI-accelerated disruption.
That mindset prioritizes continuous testing, regular reassessment of AI use cases, and rapid feedback loops between security and business teams. Resilient organizations treat adaptation as an ongoing discipline, not an annual review.
For CISOs, the implication is clear. In 2026, resilience planning must explicitly account for AI-driven scale, speed, and opacity. The question is no longer whether AI will be used, but whether it is being deployed in a way that is secure, transparent, and aligned with business risk tolerance.
–Authored by Vishak Raman, Vice President of Sales, India, SAARC, SEA & ANZ, Fortinet
