EP 227 - Why Quality Assurance Is Now a CEO-Level Concern in APAC
Tue Oct 28 2025
In this episode we spoke with Damien Wong, Senior Vice President for Asia Pacific at Tricentis, about how Agentic AI is redefining software quality assurance (QA) for enterprises navigating digital transformation. Damien shared his journey through 30 years in enterprise technology and explained how Tricentis is pioneering a future where autonomous testing drives both speed and reliability in software delivery.
We explored why QA is fast becoming a board-level priority, how AI is removing the human bottlenecks in testing, and why quality is now existential in sectors like finance, healthcare, and government.
Key Insights:
• From manual to agentic: QA has evolved from manual testing to script-based automation, to codeless model-based testing, and now to agentic test automation. The equivalent of moving from driving a car to a fully autonomous vehicle.
• AI-accelerated quality: Tricentis' agentic automation enables systems to autonomously create, execute, and adapt tests, dramatically accelerating release cycles and reducing risk from untested code.
• Quality as a board concern: In Tricentis' Quality Transformation Report, two-thirds of organizations admitted to shipping untested code, making QA failures a C-suite and reputational risk rather than an IT issue.
• Compliance through transparency: With acquisitions like SeaLights, Tricentis helps enterprises prove that every code change has been tested—critical for regulated sectors and global compliance.
• Bring-your-own-AI flexibility: Tricentis' support for the Model Context Protocol (MCP) allows companies to plug in their own private AI models, ensuring data security and regulatory control while leveraging AI capabilities.
• Empowering, not replacing, engineers: AI-driven testing shifts QA teams from repetitive test creation to strategic oversight, while tools like NeoLoad with natural language prompts make performance testing accessible to non-technical users.
• Industry impact: From Zespri's self-healing ERP testing to preventing outages like Haribo's global gummy bear disruption, intelligent QA ensures business continuity and customer trust.
• Future outlook: With 90% of code expected to be AI-generated within a year, the ability to test at AI speed will define competitive advantage in enterprise software delivery.
IoT ONE case study database: https://www.iotone.com/case-studies
The Industrial IoT Spotlight podcast is produced by Asia Growth Partners (AGP): https://asiagrowthpartners.com
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In this episode we spoke with Damien Wong, Senior Vice President for Asia Pacific at Tricentis, about how Agentic AI is redefining software quality assurance (QA) for enterprises navigating digital transformation. Damien shared his journey through 30 years in enterprise technology and explained how Tricentis is pioneering a future where autonomous testing drives both speed and reliability in software delivery. We explored why QA is fast becoming a board-level priority, how AI is removing the human bottlenecks in testing, and why quality is now existential in sectors like finance, healthcare, and government. Key Insights: • From manual to agentic: QA has evolved from manual testing to script-based automation, to codeless model-based testing, and now to agentic test automation. The equivalent of moving from driving a car to a fully autonomous vehicle. • AI-accelerated quality: Tricentis' agentic automation enables systems to autonomously create, execute, and adapt tests, dramatically accelerating release cycles and reducing risk from untested code. • Quality as a board concern: In Tricentis' Quality Transformation Report, two-thirds of organizations admitted to shipping untested code, making QA failures a C-suite and reputational risk rather than an IT issue. • Compliance through transparency: With acquisitions like SeaLights, Tricentis helps enterprises prove that every code change has been tested—critical for regulated sectors and global compliance. • Bring-your-own-AI flexibility: Tricentis' support for the Model Context Protocol (MCP) allows companies to plug in their own private AI models, ensuring data security and regulatory control while leveraging AI capabilities. • Empowering, not replacing, engineers: AI-driven testing shifts QA teams from repetitive test creation to strategic oversight, while tools like NeoLoad with natural language prompts make performance testing accessible to non-technical users. • Industry impact: From Zespri's self-healing ERP testing to preventing outages like Haribo's global gummy bear disruption, intelligent QA ensures business continuity and customer trust. • Future outlook: With 90% of code expected to be AI-generated within a year, the ability to test at AI speed will define competitive advantage in enterprise software delivery. IoT ONE case study database: https://www.iotone.com/case-studies The Industrial IoT Spotlight podcast is produced by Asia Growth Partners (AGP): https://asiagrowthpartners.com