Topic starter
09/07/2026 3:20 pm
TL;DR: Business-focused AI solutions are already in use at 73% of organisations, while 68% believe AI increases breach likelihood and 70% have received a ransomware demand, according to Commvault’s commissioned ANZ survey of 408 organisations. The pattern shows that governance, audit, and recovery discipline are lagging the pace of adoption and risk, while recovery expectations remain far ahead of operational reality.
Editorial analysis by NHI Mgmt Group, based on content published by Commvault: “Navigating the Data Maze: Key Highlights from the 2025 State of Data Readiness in ANZ”.
By the numbers:
- The annual data growth rate in ANZ has marginally slowed from 28% last year to 27% this year.
- A majority, 62%, continue to operate in blended multi- or hybrid cloud data environments, and this is projected to increase to 71% by 2026.
Key questions
Q: How should security teams govern AI use in developer tooling?
A: Security teams should govern AI use as a data and access problem, not only a productivity feature.
Q: Why do recovery targets often fail in blended cloud environments?
A: Recovery targets fail when organisations assume backup presence equals business restoration.
Q: What are the warning signs that AI governance is lagging in an identity programme?
A: Common warning signs include no formal audit of AI tools before deployment, no policy for generated data, and no clear owner for access to AI outputs.
Practitioner guidance
- Audit AI tools before deployment Require security review of data handling, access scope, retention, and output reuse before business-focused AI is allowed into production workflows.
- Test recovery against real workloads Validate restoration of mission-critical workloads end to end, including identity dependencies, backup integrity, and sequencing across blended environments.
- Map data copies across cloud environments Inventory where regulated and recovery-critical data copies live, then align entitlement controls and retention rules across each environment.
Bottom line: ANZ organisations are facing a compound readiness problem where AI adoption, cloud sprawl, and regulatory pressure are moving faster than governance.
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09/07/2026 3:38 pm
AI readiness without data governance is a control illusion: The report shows that adoption is outpacing the discipline needed to govern data exposure, audit AI tools, and define content protections. When 73% of organisations are using business-focused AI but only 29% have comprehensive policies for AI-generated content, the gap is no longer theoretical. Practitioners should treat AI governance as an access and data-lifecycle problem, not a feature rollout problem.
A question worth separating out:
Q: What should organisations do when executive recovery expectations are too optimistic?
A: They should replace optimistic recovery targets with evidence from full restoration tests. The test should include identity recovery, mission-critical workload sequencing, and a realistic measure of when the business can actually operate, not just when systems come back online.
👉 Read our full editorial: ANZ data readiness is lagging behind AI and recovery risk