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Backing up for the future: insights from the Keepit annual data report 2026

The Keepit Annual Data Report 2026 highlights shifts in data recovery practices as companies rely more on SaaS platforms.

  • Wednesday, 1st April 2026 Posted 2 months ago in by Sophie Milburn

In today’s digital landscape, organisations are increasingly using Software as a Service (SaaS) platforms to support their operations. Keepit has published its Annual Data Report 2026, examining trends in recovery readiness.

Based on observed backup and restore activity, the report highlights ongoing gaps in recovery practices, particularly among smaller organisations, while larger enterprises show higher levels of operational maturity.

Drawing on aggregated and anonymised behavioural data from its production backup environment, the report analyses how organisations use backup systems. Among the findings, 9 in 10 enterprises have validated bulk recovery, indicating a higher level of disaster recovery preparedness.

The report also finds that identity systems are tested less frequently than productivity systems, despite their role in controlling access to SaaS applications. In addition, 90% of restore activities involve single file downloads, reflecting the frequency of smaller-scale data loss incidents.

Despite high-profile global outages and security incidents, the data shows no corresponding increase in recovery testing activity.

The report identifies behavioural patterns in how organisations build recovery capability. Frequent, smaller restore actions contribute to familiarity with recovery processes but do not represent full validation for larger-scale incidents.

It also notes that recovery readiness is influenced by regular processes such as structured testing and guided recovery, rather than the adoption of additional tools alone.

The analysis is based on aggregated, anonymised data collected between January 1 and December 31, 2025, across multiple global regions. It does not rely on surveys or self-reported input, but instead reflects observed system usage patterns.

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