Background and context

An international technology company with over 1,000 employees wanted to improve the efficiency and effectiveness of its internal training and development programmes. The challenge was that the training department was not always able to respond to individual learning needs in a timely manner and create a personalised learning environment. The standardisation of training often led to low engagement and low employee satisfaction.

Project objectives

The main objective of the project was to personalise and optimise the training and development experience for employees. This was to be achieved by automating training workflows and providing real-time support. Specific objectives included:

  • Improve personalization of training content.
  • Increase employee satisfaction and engagement.
  • Automate responses to frequently asked training questions.
  • Reduce time spent by training staff on administrative tasks.

3. Solution Implementation

To achieve these goals, AI was integrated into the company’s existing learning and development systems. The implementation process followed a structured plan:

a) Analysis of the needs and planning:
  • Identify training needs: Analyse frequently asked questions and common learning needs through feedback and employee surveys.
  • Identifying integration points: IT identified the relevant systems, including the learning management system (LMS) (e.g. Moodle) and the HR management platform (e.g. SAP SuccessFactors).
b) Development and integration:
  • Create conversational workflows: Develop specific workflows to answer frequently asked training questions and provide personalised learning paths.
  • Technical integration: Seamlessly integrated AI into the LMS and HR platform.
c) Training and knowledge database:
  • Data import and structuring: Historical training data and frequently asked questions were used to expand the AI’s knowledge base.
  • Regular updates: Planning regular updates to the knowledge base to ensure the relevance and accuracy of the information provided.

Example application and process scenario

Scenario: Individual learning support for an employee

  • Step 1: An employee interacts with the embedded chat system on the LMS to get assistance with a training task.
    – Employee: “Hi AI, I need help understanding the latest module on data security. Do you have any learning materials or tips for this?”
  • Step 2: The AI ​​processes the request and retrieves relevant learning materials and tips from the LMS.
    – KI: AI: “Hi! I’m happy to help you. The data security module contains several resources. Would you like some additional reading recommendations or an overview of the important points of the module?”
  • Step 3: The employee states exactly what he needs.
    – Employee: “Please give an overview of the important points.”
  • Step 4: The AI ​​provides an overview of the key points of the data security module with references to specific learning materials.
    – KI: “No problem. Here are the key points of the data security module:
    1. Basic principles of data security.
    2. Technical measures for data security.
    3. Legal requirements and compliance.
    You can read the details of each of these points in the resources provided. Would you like more details or additional learning materials?”
  • Step 5: The employee chooses additional learning materials
    – Employee: “Yes, please send me additional learning materials.”
  • Step 6: The AI ​​provides additional learning materials and saves the request for future recommendations.
    – KI: “Sure, here are some follow-up articles and videos on the key points. These should help you understand the module better.”

Results and benefits

After the implementation of AI, significant improvements were seen in the training and continuing education processes:

  • Personalized learning experience: Employees received customized training content and support that was tailored to their individual learning needs.
  • Increased employee engagement: Improved personalization and accessibility of learning materials led to higher engagement rates and satisfaction.
  • Efficient use of resources: Training staff were able to focus on more strategic tasks as repetitive requests were efficiently automated.
  • Faster problem resolution: Average resolution time for training questions decreased by 60% and employees were able to access the information they needed more quickly.

Conclusion

Integrating AI into the company’s training and development processes resulted in a significant increase in efficiency and satisfaction for both employees and the training department. By automating repetitive tasks and providing personalized learning paths, valuable time was freed up and the quality of the training experience was significantly improved. Future expansions could include implementing additional languages ​​to support a global team and integrating advanced analytics tools to further optimize training programs.