Schaeffler Academy & Schaeffler Digitalization Departments

AI Masterclass@ Operations

Empowering Schaeffler teams to understand AI technologies, develop and evaluate AI models, and explore strategic AI portfolios collaboratively.

Overview Learning Journey Concept – "AI Masterclass"

A comprehensive training program designed to build AI competencies across Operations

Live Training

Interactive sessions with experts

Hybrid Training

Online and on-site sessions

Roundtable / Workshop

Group work and discussions

Podcast

Self-paced learning content

Key Takeaways

Grasp basic AI methods, prerequisites for data projects, and gain insight into AI@Schaeffler's strategy and operational fundamentals
Understand AI use cases, develop and evaluate AI models, and explore strategic AI portfolios collaboratively
Comprehend AI technologies, grasp AI legality and ethics, and explore practical AI applications
Apply, evaluate and present AI techniques on a given use-case while working collectively

Agenda Online

Online training sessions overview

Session	Duration	Details	Responsible
Podcasts 1	0:50	Listen to Podcasts 01 – AI Basics, 02 – Buzzwords, 03 – Use Cases individually	Participants
AI Basics AI Basics & Schaeffler Strategy	Introduction & Podcast Recap 1:30	Brief introduction of Learning Journey, Agenda and Trainer Recap of podcasts: Comparing human and artificial intelligence Understand possibilities and limitations, areas of cooperation and complementarity	Explorate AI
	AI@Schaeffler Overview 0:30	Overview AI@Schaeffler: Opportunities & Risks, Schaeffler AI Strategy, Focus Topics at Operations, AI Competencies	Schaeffler / Explorate
	Transformation Map Group Work 0:45	Group work Transformation Map for AI	Participants
Technical Deep Dive Empowering Operations through AI Technical Deep Dive	1:15	Outline generic AI project workflows using the CRISP-DM standard Focus on important quality gates and common pitfalls Highlight the importance of data quality Demonstrate unsupervised learning to find groups and anomalies in data	Explorate AI
Podcasts 2	0:45	Listen to Podcasts 04 – Data Quality and 05 – Managing successful AI Projects individually	Participants

Agenda On-site

On-site training sessions overview

Session	Duration	Details	Responsible
Podcasts 3	0:40	Listen to Podcasts 06 – Generative and Agentic AI and 07 – Best Practices individually	Participants
Technical Deep Dive Empowering Operations through AI Technical Deep Dive	1:00	Develop a machine learning pipeline using a no-code environment such as KNIME Learn (three questions) to evaluate supervised model performance Derive a business case and specification	Explorate AI
	0:30	Examples from Schaeffler for unsupervised and supervised learning use-cases	Schaeffler / Explorate
GenAI Workshop How to unlock the full potential of GenAI?	1:30	Recap LLM Basics with focus on capabilities and limitations, live-demos and hands-on experience	Explorate AI
GenAI Workshop How to unlock the full potential of GenAI?	0:45	Legal, Policy & Ethics (e.g. AI Act) + Governance at Schaeffler	Schaeffler / Explorate
Hackathon Development of a Use Case - Hackathon	1:45	Participants work in small hackathon groups with realistic use-case and datasets Visualize data to answer business questions Prepare data and train models Evaluate model quality, decide on deployment	Explorate AI
Practice & Application Put into practice – Integrate our People	2:00	Recap of learning journey, participants' key moments and insights Put into Practice: define actionable steps, timelines, cooperation and responsibilities Conclusion and Feedback	Participants
Podcasts 4	0:15	Listen to 12 – Optional – Explainable AI	Participants

Session 1

Group Work: Transformation Map for AI

A structured approach to assess and plan your AI transformation journey

What is the Transformation Map?

The Transformation Map is a strategic planning tool that helps teams assess their current AI readiness and plan a roadmap across four key dimensions. This group work session allows participants to reflect on their organization's status quo and develop actionable steps for AI adoption.

Four Aspects of Digital Transformation

People and Culture

Employees, roles, mindset, know-how

What AI skills do our employees currently have?
How open is our team culture to AI-driven change?
What training needs exist for AI adoption?
Who could champion AI initiatives in your area?

Data

Sources, quality, availability

What data sources are currently available in your area?
How would you rate the quality of this data?
Is data easily accessible for analysis?
What data would be valuable but is not yet collected?

Technology

(Data) infrastructure, standardization, partnerships

What IT systems and tools are currently in use?
How standardized are data formats across systems?
What technology gaps exist for AI implementation?
Are there existing partnerships with AI vendors?

Processes

Responsibility, reporting, integration into business processes

Which processes could benefit most from AI?
How are decisions currently made in these processes?
What would change in daily workflows with AI support?
Who is responsible for process optimization?

Roadmap Timeline

Current

What is your status quo today?

Short-term

Quick wins in the next 3-6 months

Mid-term

Strategic initiatives in 6-18 months

Long-term

Vision for 2+ years ahead

Facilitation Guide

Step-by-step instructions for leading the group work

Introduction (5 min)

Explain the purpose of the Transformation Map and the four dimensions. Share that the goal is to assess where you are and where you want to go with AI.

Individual Reflection (10 min)

Ask participants to individually think about and note down observations for each of the four aspects in their area of work.

Group Discussion (20 min)

In small groups of 4-5, share observations and identify common themes. Use sticky notes on Conceptboard to capture ideas.

Roadmap Planning (10 min)

For each aspect, identify 1-2 actions for short-term, mid-term, and long-term. Focus on realistic, achievable goals.