From ERP nightmares to Agentic workflows: Tricentis’ roadmap for AI-first enterprises
Tricentis, a software testing platform, recently unveiled its vision for the future of AI-powered quality engineering at its Transform event in London. This announcement signifies a pivotal shift in how enterprises will approach software development, testing, and deployment in the age of AI. The company is aiming to transform quality engineering into a strategic discipline driven by intelligent, autonomous systems. The core of Tricentis's new strategy involves a unified AI workspace and an agentic ecosystem. This integrated system combines Tricentis's AI agents, Model Context Protocol (MCP) servers, and AI platform services. The goal is to establish a centralized hub for managing quality at the accelerated pace of modern innovation. This approach addresses the increasing complexity and volume of code generated through generative AI, which traditional testing methods struggle to manage. This shift will significantly affect large organizations that depend on complex technology stacks, some of which may be decades old. The company emphasizes the ability to test across both legacy and new technologies. The agentic AI technologies aim to generate and execute tests, and continuously learn from results to improve reliability and reduce risks. The 2025 Tricentis Quality Transformation Report indicates that 63% of organizations deploy code without fully testing it, and over 80% report financial impacts exceeding $500,000 annually due to software defects. Tricentis is addressing a crucial challenge, as "wrong" responses in AI are not necessarily bugs, but rather, data points that require different approaches than traditional software fixes. The company's focus on AI-driven testing solutions highlights the need for continuous learning and adaptation in the face of increasingly complex software development paradigms.
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