Meeting the challenges of growth with AI – the smart way
How JobRad GmbH effectively meets the challenges of rapid growth with artificial intelligence
JobRad GmbH is Germany's leading provider of company bike leasing and supports companies, public institutions, and self-employed individuals in implementing sustainable mobility concepts. With a digital portal, a nationwide network of specialist dealers, and comprehensive services, JobRad makes it easy to integrate bicycles and e-bikes as tax-deductible employee benefits. As part of JobRad Holding SE, based in Freiburg, the company actively promotes the transport revolution and positions itself as a reliable partner for modern, environmentally friendly mobility solutions.
The project at a glance
- Strategic clarity and anchoring of company-wide AI usage
- Adoption rate of over 85% for new JobRadGPT
- Anticipated time savings of 0.5-1 hour per employee per day thanks to JobRadGPT
- 30% more tenders processed with the same number of staff
- Improved customer satisfaction thanks to faster response times in customer service
- Higher employee satisfaction thanks to a reduction in monotonous tasks
Background
JobRad has experienced rapid growth in recent years. However, this success has also brought with it numerous growing pains: Process automation has not kept pace with growth, leading to a heavy reliance on manual work and rising costs. The company recognized the potential of generative AI, but faced the challenge of identifying specific use cases with clear business value and embedding the benefits of the technology throughout the organization.
The biggest challenges were:
- Lack of process automation: Many processes were not sufficiently digitized and automated.
- High manual workload: Employees spent too much time on repetitive tasks.
- Rising costs: Rapid growth led to rising operating costs.
- Lack of AI strategy: There was no clear strategy on how AI technologies could be used profitably.
Solution
JobRad approached codecentric and asked for help in finding and implementing AI-based solutions. codecentric then supported JobRad for about a year and developed a holistic approach to AI integration at JobRad. This approach comprised three core phases:
Phase 1: Use case identification and implementation
The most promising use cases were identified and prioritized in intensive workshops and deep-dive interviews with the specialist departments. While the workshop was conducted in one working day, the deep-dive interviews were carried out and elaborated over a period of six weeks. A particular focus was placed on automating the analysis of tender documents and faster and better processing of customer inquiries in customer service.
Phase 2: Introduction of JobRadGPT
Within a month, a GDPR-compliant private ChatGPT was introduced, allowing every employee to use various LLMs to submit queries to JobRad's knowledge base. JobRadGPT was developed and customized specifically for JobRad's requirements. JobRad employees were then trained in the application over a period of two months.
Phase 3: Development of an AI strategy
In order to create a solid basis for the use and implementation of AI solutions, a long-term AI strategy was developed for JobRad. To this end, an analysis of the current situation was first carried out and a target vision was formulated based on six areas of action:
- potential & use cases
- data management
- technology
- operating model
- competencies
- regulatory & risk management
A roadmap with concrete measures in all fields of action was created and the economic added value for the entire company was quantified. After only three months, JobRad had a solid foundation and a vision of how to integrate artificial intelligence into the company.
Throughout the project, prototypes were continuously developed, tested, and optimized. Close collaboration with the specialist departments, management, and the product tech organization ensured that the solutions were optimally tailored to the needs of the end users.
Result
The integration of AI at JobRad has led to impressive results. Above all, there is now strategic clarity and anchoring across the company in terms of how AI is used. The resulting JobRadGPT now has an adoption rate of over 85% and has the potential to save employees an average of 30 to 60 minutes of manual work every day.
In addition, 30% more tenders can now be processed with the same number of staff. Response times for customer inquiries in customer service have been significantly reduced, increasing customer satisfaction thanks to faster response times. Employee satisfaction has also increased as a result of the reduction in monotonous tasks.
Thanks to the project carried out in collaboration with codecentric, JobRad is now well positioned for the future and has also been able to build up internal AI expertise for future projects.
Markus Rebbert
SVP Technology at JobRad
The introduction of AI solutions has fundamentally changed the way we work. Today, we can achieve significantly more with the same team while improving the quality of our services. The AI strategy developed in collaboration with codecentric gives us a clear roadmap for the coming years and will help us to further expand our market position.
Markus Rebbert
SVP Technology at JobRad
Any questions about the project?
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Product Consultant
Further reference projects
Find out about other successful projects that we have completed with our customers. Perhaps you will find inspiration for a use case in your company here.
Marc Pudelski
Product Consultant