Autonomous Testing Platforms: Forrester Explores a New Paradigm for Software Dev Assurance

The modern software development lifecycle is undergoing a profound transformation. Driven by escalating expectations around speed, agility, and innovation, every phase—from requirements gathering to deployment—is evolving toward greater levels of autonomy. Testing, traditionally seen as a manual or semi-automated checkpoint, must adapt.

In this context, autonomous testing platforms, or ATPs, are emerging as critical enablers of modern enterprise software delivery. Recently, Forrester listed Opkey among “notable vendors” in The Autonomous Testing Platforms Landscape, Q3 2025. We’re grateful for this mention, and are taking the opportunity to reflect on where the industry is heading.

What is Autonomous Testing?

Forrester defines autonomous testing platforms as platforms that, “combine traditional automation with AI and genAI agents to continuously perform increasingly autonomous testing tasks.” This is a far broader set of capabilities than early test automation, which involved automating test scripts. ATPs dynamically interpret system behavior, generate new test scenarios using natural language processing and AI, and evolve with the application as requirements change or expand.

In our experience, as software systems grow in complexity, maintaining quality assurance across environments has surpassed the potential capabilities of legacy automation tools. ATPs, on the other hand, are built to handle that complexity at speed and scale.

A Maturing Technology Offers Strategic Value

A key takeaway from the report is the evolution of the ATP market beyond what were once novel features and functions. As Forrester observed, “Differentiation is moving toward higher-order features such as test cases expressed through natural language intent specification, AI-agentic testing, risk-based orchestration, and business outcome validation. This signals a maturing baseline where vendors must now compete on strategic value, not just technical features.” We believe that this maturation has significant implications.

As a vendor in the space, we have observed this shift first-hand. While at one point, success in software testing tools was measured by scripting speed or breadth of integration coverage, ATP vendors are now judged by how well they align software testing efforts with overarching business outcomes. Advanced capabilities like risk-based orchestration, intent-driven test generation, and autonomous regression monitoring are enabling teams to prioritize user experience and business outcomes over simply achieving high coverage rates or faster deployment.

The Strategic Risk of Lagging Testing

The pursuit of greater autonomy in testing, and an evolved role for the humans who manage it, is no longer an aspirational hope. It’s a necessary, and difficult, shift for teams. Forrester writes: “Testers must evolve into strategic orchestrators and AI supervisors who interpret what good quality looks like. However, most teams lack the skills and frameworks to support this shift. ROI proof and alignment of testing with business outcomes remain persistent hurdles.” This insight may resonate with leaders who’ve begun to modernize, but still find QA cycles lagging behind release cadence.

We believe that testing that fails to keep pace introduces real strategic risk. Even fast-moving organizations risk regressions, broken UI paths, and errant data behaviors if validation workflows remain manual or brittle. Additionally, in our experience, the degree of regulation in a given industry has significant implications. In highly regulated sectors like

healthcare and finance, such gaps can translate into compliance exposure and erosion of public trust.

The way we see it, as ATPs gain adoption, they offer a way not only to close this velocity gap, but to elevate the role of testing into a cross-functional enabler of agility and governance alike. Automation is becoming a foundational pillar of resilient digital delivery.

Key Characteristics of Modern ATPs

Across the ATP space, we see that certain defining features are rising to the top:

• Natural Language Processing: Mirroring advancements in consumer AI tools, ATPs increasingly allow users to create tests using input in plain English, making test creation more accessible to non-technical users.
• Agentic-AI Test Generation: Instead of passively executing scripts, AI agents can now proactively explore environments, identify test gaps, and auto-generate recommendations for coverage expansion.
• Risk-Based Orchestration: By evaluating application changes, ATPs can prioritize testing where failure would pose the highest risk.
• Continuous Learning: These platforms increasingly act as learning systems, refining tests and models over time to help augment system function across digital infrastructure.

We believe that the convergence of these capabilities represents more than increased market maturity; it signals a foundational shift in how enterprises think about testing. For Opkey, testing is proactive, intelligent validation aligned with business goals, not about putting out fires.

Questions Leaders Should Ask

As Forrester’s report demonstrates, identifying the need for an ATP is only the beginning. Leaders looking to align with these trends should be asking:

• How can our testing processes transform in line with increasingly autonomous development workflows?
• Are we using AI for real strategic differentiation?
• Can our current approach to testing validate business outcomes—or just input/output logic?
• Who in the organization should participate in quality assurance?

Closing Thoughts

At Opkey, we believe that autonomous testing isn’t about reducing manual labor; it’s about elevating the impact of individuals to improve software quality and ultimately make a difference in business or organizational outcomes. As AI, GenAI, and AI agents reshape how organizations build and deliver software, testing must evolve, too.

The ongoing evolution of ATPs, as captured in Forrester’s overview, reflects a clear trend: centering autonomous capabilities in software testing is no longer optional. It is integral to competing and succeeding in a shifting world.

Subscribers to Forrester Research can access the full report here.

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