Basware Certified: AI Skilled Quality Professional

Basware is how the world's best finance teams gain complete control of every invoice, every time. Powered by the world's most sophisticated invoice-centric AI — trained on over 2.5 billion invoices — and trusted by 6,500+ customers globally including DHL, Heineken, and Sony. Recognized as a Leader in the Gartner® Magic Quadrant™ for AP Applications, Basware is pioneering the next era of finance.

To earn this credential the holder has

• Completed the Silver phase: common foundational tasks plus the opening exercises of their chosen learning path (Test Automation or Test Planning)
• Completed the Gold phase: the main body of the same path, applying AI to real product work under mentor supervision
• Guided AI using structured context files (AGENTS.md, SKILL.md) rather than relying solely on prompting
• Had their work reviewed and approved by a learning mentor and the programme core team
• Completed a graduation reflection on the AI/human split and where domain expertise was essential

On completion the earner demonstrates the ability to

Core (both learning paths)

• Generate test cases with AI from real product requirements and critically evaluate the output: gaps, incorrect assumptions, missing domain context
• Execute AI-driven browser tests using Playwright CLI and agent skills
• Write and maintain SKILL.md files that encode QA knowledge and guide AI output in repeatable, project-specific ways
• Articulate where AI adds value and where domain expertise cannot be substituted
• Apply AGENTS.md, SKILL.md, and iterative prompting as a transferable framework for integrating AI into new work beyond the training

Test Automation learning path

• Design and implement a greenfield UI test automation suite from scratch with AI, using pytest or Robot Framework and Selenium page objects
• Author AGENTS.md convention files that measurably improve AI code generation quality
• Contribute AI-assisted improvements to a production test codebase: new coverage, flakiness fixes, modernization, or framework migration
• Apply best practices (class-based tests, fixtures, parametrize, page objects, error handling) with AI guided by authored skills

Test Planning learning path

• Analyse system logs with AI to identify anomalies, correlate events, and form failure hypotheses
• Triage defects with AI: assess severity, hypothesize root causes, and spot where AI analysis diverges from domain knowledge
• Run a structured exploratory testing session and compare AI-suggested scenarios against manual findings
• Generate an AI-assisted test plan for a real feature and improve it with domain knowledge, annotating what AI missed and why
• Design cross-team E2E test scenarios covering happy paths, failure modes, and integration risks across multiple systems
• Perform an AI-supported regression analysis: extract defect patterns from historical data, cross-reference release changes, and build a prioritized test list with explicit defect history traceability