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Enterprise AI Adoption

Explore documented AI business activity, including adoption, partnerships and deployments—and see what each source actually establishes.

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✓ Atlassian✓ CyberArk✓ Qonto
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What the wiki can establish

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Use this matrix to compare published evidence—not to rank organisations or products. Each detailed claim links to its supporting wiki entry. Documented means that a source reported it, not that the wiki independently verified a causal outcome.

Business questionAtlassianCyberArkQonto
What was rolled outNo source-linked detail in this snapshotNo source-linked detail in this snapshotNo source-linked detail in this snapshot
Business workflow
  • Atlassian uses Claude for complex and long-running workflows in Rovo Chat, Rovo CLI, and early-access Rovo Max, while Claude Code is used within engineering and was piloted in non-technical teams.Vendor-reported · Read entry 1
  • Its April 2026 engineering account says the system used Anthropic Claude 3.5 Sonnet to generate review suggestions, alongside separate quality checks.Source-reported · Read entry 1
No source-linked detail in this snapshot
  • Qonto deployed Claude in agents inside its banking and bookkeeping product, using Amazon Bedrock for the more complex steps.Vendor-reported · Read entry 1
  • Qonto's AI Lab also uses Claude Code internally for engineering.Vendor-reported · Read entry 1
Reported result
  • Atlassian reported a 30.8% reduction in median pull-request cycle time with its Claude-backed Rovo Dev Code Reviewer and 35.6% fewer human-written review comments.Source-reported · Read entry 1
  • The authors report up to a 95% reduction in the time from support-case assignment to resolution: simple cases reportedly moved from 4–6 hours to 15–30 minutes, and complex cases from as long as 15 days to 2–4 hours.Source-reported · Read entry 1
  • Anthropic reports bank transfers completed twice as fast, client invoices created in one-third the time, and payroll flows handled five times faster in the described workflows.Vendor-reported · Read entry 1
Measurement basisMeasurement basis included in reported result aboveNo source-linked detail in this snapshotNo source-linked detail in this snapshot
Limits and unknowns
  • The same story reports millions of Rovo Chat users but does not provide a controlled measure of Claude-specific productivity or customer outcomes.Vendor-reported · Read entry 1
  • Anthropic's customer story says more than five million AI agents ran in customer business workflows in one month, but does not attribute all those executions to Claude; Rovo uses multiple models.Vendor-reported · Read entry 1
  • It does not independently validate the adoption scale in Anthropic's customer story, nor establish a Claude-specific productivity outcome.Adopter-published · Read entry 1
  • These results are customer/vendor-reported, not independently verified; the reported "up to" figure must not be read as an average.Source-reported · Read entry 1
  • These are vendor-published customer claims, not independently audited causal estimates across Qonto's entire customer base.Vendor-reported · Read entry 1

Not directly comparable: reported results may use different measures, populations, baselines, methods or dates. Read each measurement basis and source before drawing a conclusion.

Snapshot classificationsContext, not cited per-cell claims

These classifications summarise each entity dossier; they are not individually cited claims. Open a linked claim above for source-specific detail.

ClassificationAtlassianCyberArkQonto
Adoption stageProductionProductionProduction
Business functionsNot establishedCustomer ServiceFinance
Outcome categoriesCycle TimeCycle TimeCycle Time
Source date2026-08-282026-02-182026-09-03

Atlassian

CyberArk

Qonto

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