From Manual to Automated Testing: The Role of AI in the Transition

This presentation explores how AI is revolutionizing the transition from manual to automated testing, addressing common challenges organizations face during this evolution.

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Through case studies and live demonstrations, we'll show how organizations have reduced testing cycles by up to 60% while increasing coverage by 35%, enabling true continuous testing aligned with modern CI/CD pipelines.

Value for the audience:
Attendees will gain practical insights into implementing AI-assisted testing without disrupting existing workflows, including concrete strategies for measuring ROI, upskilling testing teams, and achieving incremental automation success. We'll provide a clear roadmap with actionable steps that can be implemented immediately, regardless of current testing maturity. Participants will learn how to leverage AI to reduce test creation and maintenance effort while simultaneously increasing test coverage and reliability.

Problems addressed:
Organizations struggle to maintain testing quality and coverage as software complexity increases and development cycles shorten, creating a growing gap between what needs to be tested and what can feasibly be verified through manual approaches.


Traditional test automation requires significant upfront investment in scripts, frameworks, and specialized skills that many organizations lack, leading to failed automation initiatives or limited ROI on automation investments.


The transition from manual to automated testing often results in loss of institutional knowledge, test brittleness, and resistance from testing teams concerned about their changing roles.

Talk language: English
Level: Newcomer
Target group: Quality Assurance professionals, Test Managers, Development Team Leads, DevOps Engineers, CIOs/CTOs interested in modernizing their testing approaches

Company:
Thunder Code SAS

Karim Jouini