“AI is always a team sport. We are thrilled to bring together technical, business and strategy experts of Infineon with appliedAI change makers behind one goal: Bringing AI Innovation to the next level at Infineon Austria and beyond!” - Nico Kelling, Head of Infineon's AI Center of Excellence
The program was brought to life by Infineon's AI Center of Excellence Team in Munich together with Infineon Austria (IFAT). The success was made possible by the strong endorsement of Sabine Herlitschka, Infineon Austria’s CEO, and facilitated through Infineon’s innovation accelerator program.
Infineon approached appliedAI with the idea to offer an AI innovation program at its Austrian site in Villach. Jointly, appliedAI and Infineon came up with the concept for a hands-on training program piloted at Infineon Austria.
The resulting training program, AI Heroes, aims to accomplish the following three objectives:
Upskill a heterogeneous group of employees at IFAT on the topic of AI.
Enable participants to systematically innovate on AI use cases to accelerate AI at Infineon.
Enable participants to become AI ambassadors at Infineon Austria and worldwide.
The following case study gives insights into this innovative educational offer and its results. Learn about an efficient and holistic way to upskill a diverse set of employees in your organization on the topic of AI.
The novel educational program was developed by appliedAI with the learners’ needs in mind. As a first step, an interdisciplinary team, including instructional designers, AI engineers, and AI strategists, was formed to guarantee diverse perspectives contributing to the project. The first milestone was accomplished through the development of an extensive learning journey tailored to Infineon Austria’s (IFAT) ideas and requirements.
The envisioned learning journey consists of three main phases including various areas of interest. The resulting curriculum is described in detail below.
The first phase of the AI Heroes training program is laying the knowledge foundation for the participants to understand AI. This is a prerequisite for the following phases of the training. The areas of interest are AI strategy, AI technology, and AI project management.
AI Strategy: This module gives an introduction to AI and AI strategy. It focuses on the AI strategy house and the importance of a holistic AI strategy within a company.
AI Technology: This module gives an introduction to the technology driving AI and Machine Learning (ML). Here, topics such as ML learning types, neural nets, and ethical considerations, are covered. In addition, trainers guide the participants through an AI use case implementation on the topic of Natural Language Processing (NLP).
AI Project Management: In this module, the basics of AI project management are covered. Starting from well-known approaches such as SCRUM and Kanban, specific uncertainty-based approaches to managing ML projects are covered. Participants learn agile project management methods through a hands-on exercise. Furthermore, this module covers the ML-Lifecycle in great detail.
Equipped with lots of AI knowledge, participants form smaller groups and start to ideate multiple AI use cases. The goal is to find use cases that fit with Infineon’s strategic AI ambition. Following the ideation, participants assess and prioritize said use cases.
Use Case Ideation: Participants learn how to find relevant AI use cases that are in line with the company’s AI ambition. They get to practice different ideation approaches on a case study, before applying the methods to find Infineon-relevant use cases.
Use Case Assessment: Participants learn how to assess AI use cases along the dimensions of value and ease of implementation. They apply these assessment techniques to the ideated use cases from the previous session.
Use Case Prioritization: Participants learn how to choose (prioritize) from their ideated and assessed AI use cases. The goal: Each group selects one use case to proceed with to phase 3.
The accelerator sprint is a deep dive into every group’s AI use case. It entails the detailed planning of the AI use case, a suggested ML-pipeline for implementation, measures to deal with uncertainty, and an implementation plan along project phases.
Project Planning: Participants work in groups on the AI use case they chose in phase 2. In this session, participants are confronted with many questions that are relevant to be answered before the use case implementation. The questions are organized along the ML-Lifecycle.
Uncertainty and ML-Pipeline: Participants design a suiting ML-Pipeline for future implementation. For that purpose, a no-code environment is simulated. Furthermore, participants are exposed to events that could potentially happen during implementation. They have to find solutions in order to be prepared for such uncertain events.
Project Phases: Participants define a roadmap based on the ML project phases for implementation. They derive a rough timeline for the implementation of the AI use case.
After completing the primary training program participants present their developed use cases in front of a jury, which consists of representatives of Infineon’s AI Center of Excellence and the Infineon Austria division. The jury votes on the best use case idea.
Format
”AI Heroes” was conceptualized utilizing a blended learning approach. Blended learning describes a teaching method that blends asynchronous and computer-mediated self-studying with synchronous face-to-face sessions. This opens the opportunity for participants to come prepared for the live sessions, which increases learner success and engagement. More concretely, learners were given reading materials ahead of time and some guiding questions to answer in an online forum. In the face-to-face sessions, these answers were discussed and put into context. During live sessions, participants had the chance to individually learn new information and teach it to their peers.
While training materials were developed by appliedAI’s instructional designers with various subject matter experts, the actual live sessions were delivered by AI engineers and AI strategists. Hence, participants had the opportunity to interact with experts in the field of AI. Infineon organized events to strengthen the AI community and inspire AI-related discussions in the company. For example, Infineon organized fireplace talks, Q&A sessions, and an elaborate welcome day for their future AI heroes.
As a result of their AI strategy development project, MTU has established an AI Center of Excellence (AI CoE), which is considered part of their group-wide corporate development. The team aims to create a link between AI use cases and enabling factors (talent, infrastructure, organization, etc.) to ultimately develop the technology with long-lasting impact within the company. Therefore, the AI CoE will provide an overview of the possibilities of AI, advise MTU’s business units on potential AI use cases, and actively manage the existing portfolio of AI projects to support them during implementation and scaling.
The AI Center of Excellence will also enhance execution models, implement training concepts, and increase awareness of AI across the company through targeted communication measures. To complement the comprehensive internal activities, it will establish a network with relevant external stakeholders and join the appliedAI network, thus conjoining the vast wealth of experience of all partner companies.
Three main factors were responsible for the success of the project:
First, the project started with an introduction to artificial intelligence for all stakeholders. Often, a discussion about AI is held in organizations with no clear understanding of exactly what is behind the "buzzword"
Second, the various stakeholders from all relevant departments and divisions, including senior management, were involved in the entire project. This ensured that all areas relevant to the use of AI could be examined, and a joint understanding of the goal could be created
Third, the experiences of similar companies in the appliedAI network were incorporated into the project. This helped MTU to avoid common mistakes and to establish efficient structures based on the company’s AI maturity level
Pilot delivery
The training was first delivered as a pilot program on nine training days over a span of nine weeks in spring 2022. Overall, the feedback was very positive both from Infineon and the participants themselves. Needless to say, participants gave insightful and constructive feedback.
In summary, participants left the program with the following feedback:
The program gave a good overview of AI and its different aspects
Interactive elements were highly appreciated
Trainers were appreciated for their in-depth knowledge
The jury present at the final presentation day attested a very high quality of the ideated and planned AI use cases: They ranged across different domains, e.g. anomaly detection in manufacturing, smart project planning as well as AI for sustainable battery management. Four of the ideated use cases will be continued after the program and have already secured funding for the next phase – this testifies to the excellence and relevance of the participants’ work in bringing these ideas to life!
Overall, the program created a vibrant community of future AI ambassadors who will be the best advocates and multipliers for AI throughout Infineon.
In partnership with
Infineon Technologies AG
