Intelligent Quality Engineering: The AI-led Revolution

Today, AI is revolutionizing every facet of software development, and Quality Engineering (QE) is at the forefront of this transformation. Organizations are rapidly integrating AI-driven QE solutions to enhance software quality, accelerate time-to-market, and minimize reliance on manual testing. According to the World Quality Report (2024-25), 68% of organizations have transitioned from experimentation to actively adopting AI-powered QE solutions, significantly improving IT efficiency.

With AI adoption rising, software testing has evolved beyond mere automation—it has become intelligence-driven. AI-led QE empowers businesses to predict failures, optimize test coverage, and expedite releases, making it a pivotal force in modern software development.

Innominds' Quality Engineering Practice: Pioneering AI-led Strategies

Innominds' Quality Engineering practice is at the cutting edge of AI-led innovation, implementing transformative strategies for our customers. Our focus areas include:

1. Development of In-house Accelerators

• Tailored accelerators address critical challenges across the Software Testing Life Cycle (STLC) and Software Development Life Cycle (SDLC).
• These accelerators facilitate the rapid conversion of user stories into comprehensive test cases, followed by seamless automation of manual test cases, significantly reducing turnaround time.
• Our Accelerators are getting evolved through continuous enhancements, guided by customer feedback and a strategic roadmap, where in we incorporate advanced features such as Figma file support to further streamline efficiency.

2. Industry-leading AI Tools’ Expertise

• Innominds has built deep expertise in cutting-edge AI-powered test automation tools, including Tricentis TOSCA, testRigor, and ACCELQ.
• The successful implementation of TestRigor,Accelq have been accelerated automation adoption by leveraging AI capabilities such as self-healing and intelligent locators, enabling domain SMEs to drive automation with ease.

3. Strategic Partnerships with AI Tool Vendors

• Innominds actively fosters strategic alliances with AI tool vendors, including Tricentis and testRigor, to drive enterprise adoption of AI-led automation.
• Feasibility studies and Proof of Concepts (POCs) enable customers to transition seamlessly from traditional automation to AI-driven automation.

4. Enhancing Full-Stack Automation with GitHub Co-Pilot

• GitHub Co-Pilot has been successfully integrated into enterprise automation projects, significantly improving productivity and code quality.
• Additionally, Innominds is expanding GitHub Co-Pilot adoption into full-stack automation projects to enhance efficiency and deliver exceptional value to customers.
  
  

Embedding AI into STLC

At Innominds, AI is seamlessly integrated into STLC to redefine quality engineering. Our AI-powered solutions enhance every stage of testing, ensuring accelerated releases, optimized test coverage, and reduced maintenance efforts.

Enhancing Software Quality with AI:

• Predictive Analytics – AI-driven models analyse historical defects to anticipate failures before they occur, reducing production issues.
• Data Analysis & Pattern Recognition – AI continuously extracts insights from test executions, detecting anomalies and optimizing test efficiency for informed decision-making through integration of Report portal developed using open source tech-stack like Extent/Allure reports

By embedding AI into STLC, Innominds enables businesses to implement self-improving test strategies, shorten time-to-market, and enhance software reliability with minimal manual intervention.

Roadmap: AI-Led Quality by Design

AI adoption in Quality Engineering is no longer just a trend—it is a strategic necessity for organizations seeking high-quality, rapid, and cost-effective software delivery. Our AI-driven roadmap includes:

• Intelligent analytics for predictive defect detection and optimized regression test selection based on code changes.
• Automated tool recommendations for enterprise customers, accelerating the evolution from traditional automation to the next phase of automation-of-automation.
• Strengthening AI expertise through certifications and hands-on POCs to proactively address customer challenges in automation.
  
  
  

The Future of Software Testing: AI-Led, Data-Driven, and Automation-First

As AI continues to advance, businesses that integrate AI-driven QE will gain a competitive edge by enhancing test efficiency, accelerating release cycles, and ensuring scalable, high-quality software.

Innominds, with its cutting-edge AI-driven QE solutions, is empowering organizations to navigate this transformation and achieve their quality engineering goals. Our commitment to excellence is underscored by our recent recognition as a "Major Contender" in Everest Group’s Quality Engineering (QE) Services for AI Applications and Systems PEAK Matrix® Assessment 2024.

Ready to revolutionize your software testing with AI?

Contact Innominds today!

I will be talking more about ‘Automating Quality by Design with AI” in my upcoming blog.