A4Q AI Scheme
The A4Q AI Scheme is a comprehensive, vendor-neutral certification program designed to equip professionals with the knowledge and confidence to work effectively with Artificial Intelligence. Developed to meet global industry needs, the scheme provides a structured learning path that supports individuals as they build foundational understanding, deepen their expertise, and ensure responsible and compliant AI adoption.
A4Q AI Essentials
A4Q AI Essentials introduces professionals to the core concepts of Artificial Intelligence, including machine learning, neural networks, natural language processing, and ethical considerations. This entry-level certification enables learners to build a solid understanding of AI fundamentals and make informed decisions about AI use in their roles or organizations.
A4Q AI Foundation
A4Q AI Foundation expands on the Essentials level by exploring AI technologies, methodologies, and applications in greater depth. It provides professionals with a more advanced understanding of how AI solutions are developed, evaluated, and integrated into business processes, supporting more strategic and technical decision-making.
A4Q AI Compliance
A4Q AI Compliance focuses on responsible, trustworthy, and regulation-aligned AI adoption. This certification helps organizations and professionals navigate emerging legal requirements, ethical frameworks, and governance practices to ensure AI systems are implemented and managed with accountability and transparency.
Target Audience:
IT and Quality Professionals
Testers and Automation Engineers
Business Analysts and Project Managers
Developers and Data Professionals
Anyone Exploring AI for Career Growth
As the Product Manager for the ISTQB® CT-GenAI certification, I led the vision, development, and launch of this cutting-edge qualification, designed to equip software testing professionals with the skills to effectively integrate Generative AI (GenAI) into their workflows.
In this role, I oversaw the full product lifecycle—from market research and syllabus design to stakeholder alignment and global rollout. Key focus areas include:
AI-Powered Test Design: Enabling testers to leverage Generative AI and Large Language Models (LLMs) to generate test cases, acceptance criteria, and synthetic data.
Prompt Engineering & Optimization: Developing guidance on designing effective AI prompts to improve testing accuracy and efficiency.
Risk Management for AI Testing: Incorporating strategies to handle AI-specific risks, including bias, hallucinations, and data privacy concerns.
Integration & Tools: Guiding the adoption of LLM-powered tools like Retrieval-Augmented Generation (RAG) and AI agents within enterprise test environments.
Strategic Impact: Ensuring the certification addresses the growing demand for AI competency in software testing and aligns with industry best practices.
By managing cross-functional teams of subject matter experts, instructional designers, and technical reviewers, I ensured that CT-GenAI delivers a practical, globally recognized certification that empowers testers, test managers, and developers to adopt AI-driven testing strategies confidently.
Learn more here: CT-GenAI Certification