Date:
15-min read
Q1: What inspired the creation of the AI Testing training program at Exactpro?
Iosif: We’ve been testing complex software like exchange, matching engines, clearing and settlement platforms or banking platforms for over 16 years. We’ve learned to see the patterns in distributed and non-deterministic systems behaviour and we are uncovering better ways of testing them. Some of our tools and methods are readily applicable to AI-enabled systems and we heavily rely on machine learning in our day-to-day work. To support our own business and our clients and partners, we decided to launch our AI Testing Training programs. We wanted to provide a clear, structured path for professionals of all levels to develop and refine their testing skills – from foundational principles to advanced techniques – with a strong focus on AI.
The program is designed to guide business and technology professionals from diverse backgrounds and levels of expertise on their journey toward informed, intelligent testing. The course is accredited by the International Software Testing Qualifications Board (ISTQB®), providing a recognised benchmark for competencies in the field of AI testing. In 2024, the A-Team Group Innovation Awards recognised Exactpro’s AI Testing Training course as the Most Innovative Professional Development Initiative.
Q2: What does the AI testing Training program include?
Anna-Maria: The course is intended for those looking to learn the basics of AI systems and their quality assessment. It suits both the specialists already using AI who want to consolidate their knowledge or increase confidence, and professionals planning to take the official ISTQB® Certified Tester AI Testing (CT-AI) certification for academic, professional or other purposes.
In as little as 44 class hours, participants acquire an understanding of key aspects of AI and ML systems, along with a practical toolkit for their responsible implementation and testing. The course follows the structure of the ISTQB® syllabus and brings it to life through a highly visual and interactive format designed to accommodate different learning styles. The course is flexible and accommodates different learning styles and schedules. It is offered in four formats:
- Autonomous – structured, self-paced learning.
- Guided – focused on training AI models and managing big data.
- Accelerated – a fast-tracked AI program.
- Enterprise – designed to develop in-house AI literacy and expertise.
From the very first session, participants — individually or in groups — gain a structured, in-depth view of the types of AI and the unique quality characteristics of AI-based systems. Beyond theory, the program equips participants with practical resources and structured exercises. They explore data handling and model training for ML, the methods, test oracles, performance metrics, acceptance criteria and test environments relevant for AI systems, including neural networks, and learn how to integrate AI into software testing workflows. Real-world examples drawn from our field experience further reinforce learning. Within the Enterprise Plan, teams are guided to approach AI transformation strategically through identifying suitable use cases and learning to manage potential risks effectively. To support organisations further, we help establish AI Testing Centres of Excellence, aligning people, processes and platforms to integrate AI safely and responsibly.
By the end of the program, whether participants are new to AI or are already applying it in their work, they gain the confidence and frameworks to approach AI quality assurance in a structured and responsible way.
We have aggregated our expertise in our recent book – ‘Introduction to AI Testing: Guide to ISTQB® CT-AI Certification’ – that complements the course. It is co-authored by our team of Iosif Itkin, Dmitrii Degtiarenko, Iuliia Emelianova, and myself and is now available on the BCS Bookshop and Amazon. The book turns our hands-on knowledge into an easy-to-use guide for certification preparation or for strengthening AI testing skills.
Last month, the authors of our book presented a webinar with the BCS Chartered Institute of IT publishing team to walk through the book’s key concepts and real-world applications of AI testing. We hope it helps teams and organisations see how to apply these principles effectively in their own projects. The recording is now available on YouTube.
Q3: How can the course contribute to advancing reliable testing practices across the wider industry?
Iosif: Our AI Testing course provides a benchmark for the professional competencies required to build and operate ML and AI systems and to explore their quality.
There’s a clear dichotomy in how AI-technologies impact mission-critical systems in high-availability domains. On one hand, it can reduce human effort through automating, accelerating and scaling tasks that once required large teams. On the other hand, they introduce new risks and challenges that must be carefully managed.
We are trying to help with establishing a common foundation for the teams working with a variety of AI technologies. While providing a thorough review of the challenges such as explainability, adaptability and transparency, among others, the course helps professionals move from proof-of-concepts toward structured, scalable testing practices that can withstand real-world pressures.
Q4: How does Exactpro apply these training programs in client engagements?
Anna-Maria: While each client is unique, they share the same goal — ensuring compliance, reliability and continuous operation in an environment of constant change. Capital markets firms, in particular, face pressures to modernise, digitise and optimise their systems, and every system upgrade or protocol change introduces risks that demand thorough testing.
To help clients tackle their systems’ challenges, we offer our combined expertise at the intersection of finance, technology and artificial intelligence. We offer several collaboration opportunities with industry organisations:
- pilot test engagements – short, controlled projects where QA, DevOps and engineering teams get hands-on experience with AI, from test case generation to intelligent defect analysis and continuous model improvement. The pilots are launched in high-impact, low-risk areas to minimise potential operational disruption.
- test strategy development and review of existing strategies – defined early, test strategies can help shape system design, embed testability and address regulatory and architectural risks, creating scalable, adaptable guidelines covering tools, data, environments and non-functional needs.
- workshops and hands-on training – we use our AI Testing course and hands-on workshops to address clients’ skills gaps in applying AI for software testing and testing AI-enabled systems.
- establishing AI Testing Centres of Excellence – we help reinforce enterprise-level AI integration and adoption and build a comprehensive, risk-aware practice aligned with industry-recommended practices, including a four-pillar strategy from the Zero Outage Industry Standard (People, Processes, Platforms and Security).
- AI literacy and governance – we help develop AI literacy across business and technical teams, prepare for holistic workflow changes and embed ethics, testing, security and compliance from the start.
- guiding organisations from AI experimentation to enterprise-scale adoption, helping ensure reliability, transparency and resilience at every step.