Commvault Systems Inc., a reference in unified resilience at enterprise scale, released new research highlighting that many organizations across Australia and New Zealand (ANZ) are rapidly embedding AI into critical business operations, often without adequate safeguards in place to manage risks introduced by AI agents and AI-driven applications.This was one of the key findings from Commvault’s State of Data Resilience – Australia and New Zealand, 6th Edition (2026), accessible here.

Organizations across ANZ are placing significant bets on AI. Many are accelerating investments, with 36% increasing spend by more than 25% in 2026 compared to last year. More than 30% are already trialing or deploying agentic AI across hybrid and multi cloud environments, adding new layers of complexity to how data, systems, and AI agents are managed at scale.

The findings also show that data estates are growing at 30% compared to 2025, largely due to AI deployment and adoption. As data volumes grow and environments become more fragmented, maintaining consistent governance and oversight is becoming more difficult.

In response, organizations are moving to formalize governance, with 66% of respondents now have policies for AI-generated data and content, up from 29% last year, signaling a rapid shift toward stronger risk and compliance frameworks. However, AI adoption is outpacing process alignment, leaving many organizations without the safeguards and due diligence needed to enforce these policies in practice.

The data exposes critical gaps in these controls:

• 58% of respondents lack high confidence when AI systems are compromised or operating outside defined guardrails
• Only one third of organizations have rigorously assessed security and governance risks before AI deployment
• Just 36% have extended resilience planning to AI agents, leaving most agentic environments exposed

“AI is now central to how organizations operate but its value depends on the integrity of data behind it,” said Martin Creighan, VP, APAC, Commvault. “That data must be understood, validated, and free of sensitive information. Without strong governance and resilience across the AI lifecycle, organizations risk losing confidence in the business-critical outcomes AI delivers.”

Cyber Resilience Imbalance: Prioritizing AI Outcomes Over Readiness  
According to the findings, organizations are focusing on understanding AI-driven decisions, instead of investing in the systems that sustain cyber resilience. Explainability and transparency of AI models ranked highest at 22%. In contrast, foundational resilience enablers, like integration (14%), incident response automation (12%), and scalability (8%) lag.

Managing AI at scale requires a lifecycle approach to resilience, one that starts with safely activating data for AI purposes to support regulatory requirements and extends through discovery, governance, protection and recovery.

“Agentic environments are inherently dynamic, with AI continuously interacting across data, identities, and infrastructure,” said Gareth Russell, field CTO, security, APAC, Commvault. “Today, recovery isn’t just about restoring data, but bringing systems, configurations and dependencies back to a known good state. That level of control is critical to operating AI at scale.”

About Research Methodology
TRA, now part of Omdia, conducted an independent quantitative market survey of 411 organizations across ANZ with respondents including CIO/ CISO, IT leader, IT decision maker and direct reports.

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