đ Tuesday, 26th May, 2026
â° 11:00 h â 12:00 h
Artificial intelligence is rapidly transforming every industry, from automotive and healthcare to manufacturing and energy. AI models are increasingly embedded in critical decisionâmaking processes, influencing operational efficiency, product performance, and strategic direction.
As AI systems become more powerful and complex, one fundamental question moves to the forefront: How can we trust AI models enough to rely on them for real business and engineering decisions?
To launch our new Explainable AI (XAI) webinar series, we are pleased to introduce a crossâindustry online masterclass that lays the foundations for turning AI models into understandable, reliable, and trusted tools, both by technical teams and by decision makers.
Why Explainable AI matters across industriesÂ
Highâperforming AI models are no longer sufficient on their own. Across industries, organisations are facing similar challenges:
- Complex models that deliver predictions but not understanding.
- Difficulty explaining results to nonâtechnical stakeholders.
- Limited visibility into model behavior, assumptions, and limitations.
- Low trust in AI outputs when decisions carry operational or strategic risk.
Explainable AI provides the tools and frameworks to bridge these gaps. When applied correctly, XAI helps organisations:
- Understand why a model behaves the way it does.
- Improve model robustness during development and iteration.
- Detect hidden issues, biases, or data dependencies early.
- Communicate AI insights clearly to product owners, managers, and executives.
- Build shared trust between data teams and decision makers.
Explainability is, therefore, not just a technical feature, it is a critical enabler of reliable AI adoption at scale.
The First Session in a Webinar Series
This session opens a broader webinar series on Explainable AI. While future editions will explore industryâspecific applications, this first masterclass takes a crossâindustry perspective, focusing on the decision makers and common principles that apply regardless of sector.
The objective is to establish a shared language and mindset around XAI that aligns technical development with business decisionâmaking.
What you will learnÂ
By the end of this session, participants will understand how to move beyond accuracy alone and design AI systems that are:Â
- Transparent: their behavior can be understood and inspected.
- Explainable: predictions can be justified in humanâinterpretable terms and traced in a way that models can be accountable.
- Trustworthy: results can be confidently used in realâworld decisions.
During the session, we will cover:
- Why Explainable AI Matters to Decision Makers
- Explainable AI Foundations, without the Technical overhead
- Where Explainable AI creates Business Value
- Explainability across AI approaches
- Operationalizing XAI in the organisation
- Communicating AI Decisions with confidence
- Caseâdriven walkthrough: Mosaic Factor XAI Workflow
The focus remains firmly on practical decisionâmaking and model reliability, not abstract theory.
At the end of the session, our Chief Data Scientist, Burcu Kolbay, will host a live Q&A.
Who should attendÂ
This masterclass is designed for professionals working (or willing to work) with AI across industries, including:Â
- Decision makers who rely on AI outputs (C-level)
- Product Owners and Technical Managers
- Innovation and Digital Transformation Leaders
No legal or compliance background is required. The session prioritises applied, developmentâfocused, and communicationâdriven perspectives.
Event Details
đ Tuesday, 26th May, 2026
â° 11:00 h â 12:00 h
- Format: Online (live)
- Duration: 60 minutes
- Level: Basic to Intermediate
- Language: EnglishÂ
Registration
Join this first session of our Explainable AI webinar series to ensure your AI solutions are not only powerful but also understandable, reliable, and trusted by those who use them to make decisions.
đš Click here to register now to secure your place.Â


























