As software development accelerates through AI and generative technologies, testing is under pressure to keep pace. The rise of TuringBots and AI-generated code has collapsed traditional development cycles, introducing new complexities and risks. Yet many testing practices remain manual, fragmented, and slow. Without a strategic shift, testing threatens to become the bottleneck of the software delivery lifecycle, undermining speed, quality, and business agility. Organizations need to rethink how they approach testing — not just as a technical checkpoint but as a continuous, intelligent process that aligns with modern development increasingly based on generative, agentic AI. This is why we shifted our research from continuous automation platforms to autonomous testing platforms, as announced in this blog post a few months ago.

Who Offers What To Support Your Autonomous Testing Strategy

To help technology leaders and QA professionals make sense of this dynamic space, Forrester just published The Autonomous Testing Platforms Landscape, Q3 2025. This report profiles 31 vendors and defines the emerging category of autonomous testing platforms (ATPs) — solutions that combine traditional automation with AI and genAI agents to perform increasingly autonomous testing tasks. The report offers a comprehensive view of how ATPs are evolving, what business value they deliver, and how buyers can evaluate platforms based on core and extended use cases. It’s a valuable resource for anyone looking to modernize their testing strategy and align it with the pace of innovation in software development.

What Autonomous Testing Platforms Bring To The Table

  • Accelerate time to value through AI-driven test automation. ATPs reduce the time required to design, generate, and maintain test cases by automating traditionally manual tasks. They enable self-healing for brittle tests, optimize execution, and generate tests directly from requirements.
  • Reduce strategic risk and improve governance. AI-powered platforms support risk-based orchestration, intelligent test scoping, and real-time analytics. They prioritize testing based on business impact and historical defect patterns, ensuring that critical paths are validated.
  • Democratize testing and foster cross-team collaboration. With no-code/low-code interfaces and natural language test authoring, ATPs empower nontechnical users to “vibe-test.” Business stakeholders, product managers, and developers can all participate in defining and validating tests, leading to broader coverage and better alignment with business goals.
  • Start addressing the testing of AI applications. As AI inserts itself into production enterprise applications (AI-infused apps, or AIIAs), these also need to be tested, which means we now need to test whether the AIIA is hallucinating, not being accurate, or not meeting original intent — these are all additional capabilities that testing tool platforms need to address.

A Market In Transition — And Why It Matters

The ATP market is rapidly evolving but still maturing. While many vendors claim AI-native capabilities, buyers must distinguish between genuine innovation and marketing hype. Core features such as DevOps integration and UI testing are now table stakes; differentiation lies in agentic testing, business outcome validation, and intent-based test creation.

Organizations face challenges typical of a market in flux: fragmented toolchains, skill gaps, unclear ROI, and resistance to change. The emergence of agentic AI — systems that autonomously discover, generate, and execute tests — is redefining the role of testers and the architecture of testing platforms. This shift demands new frameworks, governance models, and cross-functional collaboration.

Take The Next Step Toward Autonomous Testing

If your organization is grappling with the speed and complexity of modern software delivery, now is the time to explore autonomous testing. The Autonomous Testing Platforms Landscape, Q3 2025, provides the clarity and structure needed to evaluate vendors, align testing with business outcomes, and prepare for the future of AI-driven quality assurance. We are just about to kick off the next step in this research, which is the Forrester Wave™ evaluation covering autonomous testing platforms (set to publish in Q4 2025) that will pick and compare the leading 15 players featured in the landscape. Reach out to schedule an inquiry or guidance session if you are updating your testing strategy and just want to keep up with the new requirements and opportunities that genAI and agents are creating.