Webinar series: Explainable AI for decision makers

Artificial intelligence is rapidly transforming every industry, from automotive and healthcare to manufacturing and energy. AI models are increasingly embedded in critical decision‑making 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 cross‑industry online masterclass that lays the foundations for turning AI models into understandable, reliable, and trusted tools, both by technical teams and by decision makers.

Recording

If you couldn’t 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, you can now watch the recording:

Why Explainable AI matters across industries

High‑performing 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 non‑technical 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 industry‑specific applications, this first masterclass takes a cross‑industry 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 decision‑making.

What you will learn

By the end of this session, participants will understand how to move beyond accuracy alone and design AI systems that are:

Transparent: their behavior can be understood and inspected.
Explainable: predictions can be justified in human‑interpretable terms and traced in a way that models can be accountable.
Trustworthy: results can be confidently used in real‑world 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
Case‑driven walkthrough: Mosaic Factor XAI Workflow

The focus remains firmly on practical decision‑making and model reliability, not abstract theory.
At the end of the session, our Chief Data Scientist, Burcu Kolbay, will host a live Q&A.