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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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✓ Tecban✓ CyberArk✓ Atlassian
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What the wiki can establish

Evidence gaps remain visible as “Not established” instead of being filled by inference.

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 questionTecbanCyberArkAtlassian
What was rolled out
  • Microsoft's customer story says Tecban adopted Microsoft 365 Copilot and GitHub Copilot, recorded 98 use cases, completed 35, and onboarded more than 3,000 users.Vendor-reported · Read entry 1
No source-linked detail in this snapshotNo source-linked detail in this snapshot
Business workflow
  • The case illustrates scaled adoption in a regulated banking environment, not a controlled causal estimate of Copilot's impact.Vendor-reported · Read entry 1
No source-linked detail in this snapshot
  • 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
Reported resultNo source-linked detail in this snapshot
  • 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
  • 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
Measurement basis
  • The story also reports an estimated 30% development productivity gain and 14% testing gain.Vendor-reported · Read entry 1
No source-linked detail in this snapshotMeasurement basis included in reported result above
Limits and unknownsNo source-linked detail in this snapshot
  • 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
  • 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

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.

ClassificationTecbanCyberArkAtlassian
Adoption stageProductionProductionProduction
Business functionsNot establishedCustomer ServiceNot established
Outcome categoriesProductivityCycle TimeCycle Time
Source date2026-06-022026-02-182026-08-28

Tecban

CyberArk

Atlassian

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