AI-Informed Testing

Artificial intelligence’s impact on software testing goes beyond simple automation — it’s creating an entirely new paradigm for how testing services are conceived, delivered, and optimized. A new frame of mind is emerging: “AI-Informed Testing”. Where, the test results of autonomous AI Testing Agents are used to inform, improve and influence the execution of testing.

During recent discussions with Phil, CEO of XBOSoft, about the future of testing services, we coined the term “AI-Informed Testing” to describe this emerging approach. As the industry grapples with how to meaningfully incorporate AI into testing practices, this term captures a crucial insight: AI’s role isn’t just about automation, but about informing and enhancing the entire testing process. This new paradigm represents the next evolution in software quality assurance, providing a framework for how testing services can harness AI’s potential while maintaining the crucial role of human expertise.

The AI-Informed Testing Opportunity

Testing services vendors, and internal teams, have built robust foundations through decades of expertise, proven methodologies, and continuous innovation in automation. These organizations have consistently adapted to meet the growing demands of software development, establishing themselves as crucial partners in delivering quality software.

AI-Informed Testing creates powerful new opportunities for testing teams and services to deliver unprecedented value to their customers:

• Accelerated Results: AI testing agents provide immediate insights, allowing testing teams to deliver value from day one and dramatically reduce time-to-results for new versions of software
• Intelligent Coverage Prioritization: AI identifies high-risk areas and potential issues, enabling testing teams to focus their human expertise and context where it matters most
• Broader Testing Scope: AI agents test for a wide range of quality issues — more than most teams even have expertise in, such as performance, privacy, security, accessibility, automation, UI/UX design, usablity — not just functionality.
• Strategic Resource Allocation: Areas where AI indicates strong stability can receive lighter human testing, allowing teams to concentrate on complex scenarios requiring human insight
• Cost Optimization: The combination of AI efficiency and targeted human testing creates significant cost savings while improving overall quality
• Risk Reduction: Continuous AI testing provides early warning of potential issues, allowing testing teams to prevent problems before they impact users or the business

This AI-Informed Testing approach creates an unprecedented opportunity for testing teams and services vendors. Early adopters of AI-Informed Testing can dramatically expand their value proposition, strengthen their strategic role with managment and clients, and capture new revenue streams.

The Rise of AI Testing Agents

AI Testing agents mark a fundamental shift in automated testing capabilities. Unlike traditional automation tools that execute predefined scripts, AI agents actively explore applications, identify potential issues, and generate comprehensive test coverage autonomously. This represents a quantum leap in testing capabilities:

Technical Advantages
- Dynamic test case generation based on actual application behavior
- Continuous learning and adaptation to application changes
- Automatic identification of regression issues
- Broad coverage of edge cases and unusual scenarios
- Real-time analysis of test results
- Bug and issue reporting that also identifies the motivation to fix the issue, and the fix!

Business Benefits
- Dramatic reduction in test automation/maintence overhead
- Faster time to market with increased confidence
- Lower total cost of testing operations
- More efficient resource allocation
- Improved risk management and quality metrics
- Better alignment with agile development practices — the testing can keep up with the fast pace of Agile

AI-Informed Testing: The New Standard

AI-Informed Testing transcends both traditional manual testing and basic test automation. By combining AI testing agents with expert human testers, organizations create a multiplier effect that transforms testing operations:

How It Works

1. AI agents continuously explore applications, generating vast amounts of test data and insights
   2. Machine learning algorithms analyze testing patterns and results
   3. Human experts receive prioritized insights and recommendations
   4. Testing strategies are dynamically adjusted based on AI-generated data
   5. Resources are automatically allocated to high-risk areas
   6. Quality metrics are tracked and predicted in real-time

It is worth noting, and reinforcing the reality that “AI” cannot do most all testing tasks today, or tomorrow. Consider that even the best development teams — have testers. Testing is a difficult, humanistic and variable activity. Even if development is fully automated by AI, testing will still be an acute problem solved by humans, helped by AI.

The Strategic Imperative

For organizations facing mounting pressure to incorporate AI into their testing strategy, AI-Informed Testing offers a clear, immediate path forward. Rather than building AI testing capabilities from scratch — a complex, time-consuming, and expensive proposition — companies can rapidly deploy proven AI testing solutions through established testing service providers. This approach allows organizations to:

- Immediately demonstrate a concrete AI testing strategy to leadership
- Rapidly implement AI-powered testing without internal development
- Show measurable AI-driven quality improvements within weeks
- Meet emerging organizational mandates for AI adoption
- Stay ahead of competitors in the AI transformation curve
- Achieve immediate ROI through improved testing efficiency

The beauty of this approach lies in its simplicity: organizations can effectively implement an AI testing strategy through a single partnership, rather than embarking on a multi-year internal development journey with multiple fragmented point solutions.

Industry Transformation in Action

The partnership between Checkie.AI and XBOSoft exemplifies this transformation. Having known Phil, XBOSoft’s CEO, for years through the software testing community and his leadership of the PNSQC testing conference, this collaboration represents more than just a business arrangement — it’s a commitment to advancing the entire testing industry.

XBOSoft’s decades of testing expertise combined with Checkie.AI’s advanced testing agents creates a new model for testing services that delivers unprecedented value:

Immediate Benefits
- Faster test execution and feedback cycles
- More comprehensive test coverage
- Reduced costs through efficient resource allocation
- Improved accuracy and consistency
- Better risk management and quality predictions

Long-term Advantages
- Continuous improvement through machine learning
- Scalable testing operations
- Predictable quality metrics
- Future-proof testing strategies
- Competitive advantage through superior quality

The Road Ahead

The testing industry’s future is clear. AI-Informed Testing will quickly become the dominant approach for delivering testing services, driven by its superior results and economic advantages. Organizations that embrace this transformation early will gain significant competitive advantages. the good news is that this is now an easy and quick step to make.

Take Action Today

XBOSoft and Checkie.AI are actively collaborating to accelerate the adoption of AI-Informed Testing across the industry. We’re inviting forward-thinking organizations to be part of this transformation. Here’s how you can get started immediately:

1. Schedule a Live Demo: See AI-Informed Testing in action with a personalized demonstration. You’ll witness real-world quality assessments and testing insights generated through our combined approach. Schedule Now
2. Quick Start Program: Getting started requires minimal effort from your team. Simply provide access to your web application, and our AI testing agents will begin generating insights immediately while our experts craft your customized testing strategy.
3. Strategic Partnership: Work directly with Phils team and Jason Arbon to influence the future of AI-Informed Testing. Early adopters get priority access to new capabilities and direct input into the roadmap.

Many organizations are scrambling to check the “AI strategy” box for their testing operations. This partnership offers an immediate, proven path forward with practically zero implementation overhead. You can literally transform your testing approach through a single meeting.

Conclusion

AI-Informed Testing represents more than just an improvement in how we test software — it’s a fundamental reimagining of what’s possible in software quality assurance. The combination of AI testing agents and human expertise creates a new paradigm that delivers better results faster and more cost-effectively than any previous approach.

The transformation is already underway, and the results speak for themselves. Organizations that adapt to this new reality will thrive, while those that cling to traditional methods will struggle to compete and maintain relevance. The future of testing is here, and it’s powered by AI. The future of testing is AI-Informed.

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*Jason Arbon is the founder of Checkie.AI and has been working at the intersection of AI and software testing for over a decade. Through innovations in AI testing agents, he continues to drive the evolution of software quality assurance.*