AI Business Manager
About this Training
The AI Business Manager training provides participants with a proven methodological approach from idea generation to evaluation, technical and business-related feasibility, competence & team settings, data testing and agile implementation methods. Using self-selected and company-individualized use cases, participants learn how to develop new data-driven business models, assess the maturity of AI use cases, and strategically manage data-driven decision-making. The program also covers key topics such as process automation, economic feasibility, and regulatory frameworks.
Why this Training is right for you
The AI Business Manager training is designed for specialist and managers who want to approach the topic of artificial intelligence from a business perspective, learn in-depth, field-tested approaches for implementing AI solutions, and gain hands-on experience with key agile AI implementation methodologies. Participants gain valuable tools for developing and scaling AI applications, managing cross-functional teams, and identifying automation opportunities.
Training Goals & Training Plan
After this training, you will be able to apply the field-tested methods of the AI Navigator and data-driven business model canvas to identify and evaluate economically logical AI use cases. You will understand how to use data as a driver for new business models, structure AI teams effectively, and optimize business processes. Additionally, you will gain insights into technology scouting, data governance, and a solid understanding of Prompt Engineering, learning how to interact effectively with AI systems to maximize their efficiency and align them with business objectives.
Within five days, the focus is on case studies and exercises in which the participants concretize and apply the theoretical & methodological basics of the AI Navigator. With the help of the field-tested AI Navigator, a structured approach is possible to identify AI-enabled projects and to guide them from idea generation to evaluation and data testing to successful implementation. In addition to lectures and practice-oriented exercises, there are numerous opportunities for professional and personal exchange as well as networking during joint evening events.
Day 1
- Introduction into Artificial Intelligence
- Data-Driven Business Model Canvas
- Introduction of AI Navigator
- Identification of AI Use Cases
- Jobs-to-be-done Analysis
Day 2
- AI Teams: Competences & Roles
- Maturity Assessment of AI Use Cases
- Data as Enabler for new Business
- Developing Data-Driven Business Models
Day 3
- Economic and Technical Feasibility of AI Use Cases
- Introduction Generative AI
- Overview of Application Fields of Machine Learning, Deep Learning & Large Language Models (LLM)
- Importance of Clearly Defined Processes
- Networking Event
Day 4
- Prompt Engineering - How do I Communicate with an AI?
- Instruction Tuning - Working more Efficiently with AI
- Process Automation with AI Agents
- Technology Scouting - Approach for quick Solution Identification
Day 5
- Data Governance
- Outline: Regulatory Framework for AI
- Business Model Stress-Test
- Exam
- Wrap-Up & Feedback
Customer Voices
"The training was an educational and intensive experience that provided valuable knowledge about the strategic use of AI in various industries. The content was extremely informative and helped to develop a deeper understanding of data-driven business models. The cross-industry exchange with other participants was particularly positive, offering new perspectives and inspiration."
Robert Kohlhaupt - Project Manager & BIM-Manager @ KVL Group
"The intensive training week with a lot of input gave a deep insight into the development of data-driven business models. I look forward to using the experience gained to promote data-driven decisions and strategies."
Frank Peterlein - Head of IT & AI @ KVL Group
Requesting Inhouse Training?
The course, or parts of it, would also be interesting for your entire team/your company? We would be happy to advise you on the possibility of an inhouse training. Give us a call or write to us - we will tailor your further training to suit your needs!
Learn more about
- AI Navigator
- Ideation – Use case browsing
- AI Use Case Assessment
- Prompt Engineering & Instruction Tuning
- KI-Teams & Competence Roles
- AI Organization
- Data-driven Business Models
- Technical feasibility
- Regulatory Frameworks & Data Governance
- Best Practices
Our Partners
Speakers
Anne Loos is a dedicated business leader in the manufacturing industry, passionately driving growth and innovation. With extensive expertise in advanced AI and digital transformation, coupled with over 14 years of hands-on experience in pioneering technologies, she implements strategies to sustainably strengthen companies' competitiveness. Through successfully diversifying international business, creating new business models, and crafting customer-centric strategies, she has established herself as a trusted partner. Her global impact extends to significant data-driven projects on a global scale.
Anne Loos
Toni Drescher is an experienced engineer and entrepreneur who has been involved in the implementation of technology-based innovations for the past 20 years. He gained practical experience in various leading management and consulting positions. He set up and commercialized new companies for several cutting-edge products and services and stands for the successful implementation of innovations. As the owner and CEO of the INC Innovation Center Group, he focuses on implementing and scaling innovations from idea to market launch to secure growth opportunities and competitiveness of large enterprises.
Toni Drescher
Tim Schroeder studied Electrical Engineering & Information Technology as well as Business Administration and General Management at RWTH Aachen University. As the Head of Artificial Intelligence at the INC Innovation Center, he led multiple bilateral and multilateral projects in the areas of Industry 4.0, Logistics 4.0, and Artificial Intelligence. Through technology scouting, data analysis, and AI assessments, he assists companies in successfully implementing new innovations.
Tim Schroeder
Dr. Olaf Enge-Rosenblatt studied automation engineering at Chemnitz University until 1986. He worked at the Institute for Mechatronics in Chemnitz, specializing in modeling mechatronic systems. Since 2005, he has been with Fraunhofer Institute in Dresden, initially as a research assistant. In 2007, he became a group leader, and in 2015, he took over the Data Analysis Systems group. Dr. Olaf Enge-Rosenblatt manages projects in condition monitoring, predictive maintenance, energy efficiency, big data, and AI. He also conducts training courses on predictive maintenance and AI implementation in production and maintenance since 2017.
Dr. Olaf Enge-Rosenblatt
Antonela Germek brings over 5 years of experience in leading and managing innovation projects across diverse industries. As the Head of Innovation Excellence at the INC Innovation Center, her primary responsibilities include developing, coordinating, and overseeing initiatives centered on methodical innovation management, new business development, and strategic alignment with current and emerging technologies. Supporting companies in identifying and systematically implementing the most suitable innovation approaches is just one aspect of her diverse focus.
