Cut through the AI washing in testing tools and learn to distinguish genuine AI-native platforms from retrofitted solutions that promise more than they deliver.
The testing industry is flooded with "AI-powered" claims, but most vendors simply bolted AI features onto legacy frameworks. This creates fundamental limitations that no amount of marketing can overcome. Understanding the architectural differences between built-on AI and bolt-on solutions is critical for making investment decisions that protect your team's future.
What You'll Learn:
- Identify architectural red flags and green flags that distinguish purpose-built AI testing platforms from legacy systems with retrofitted AI features, including technical indicators like DOM dependencies, scripting requirements, and maintenance overhead
- Evaluate vendor claims using a proven due diligence framework with specific questions to ask, proof-of-concept criteria, and reference validation strategies that reveal the truth behind AI marketing promises
- Assess long-term investment protection by understanding how core architectural decisions impact setup complexity, team adoption requirements, cross-platform consistency, and ongoing maintenance costs
Don't let AI washing derail your testing strategy. Join industry experts who've been building agentic AI for testing since before ChatGPT existed, and gain the knowledge to make informed platform decisions that will serve your team for years to come.
Speakers
Dennis Ashby
Jon Matthews
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