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ChallengeUpdated on 16 January 2026

Harnessing Knowledge to Boost Technician Productivity at Alliander

Business Developer Corporate Venturing at Alliander Next Grid

Arnhem, Netherlands

About

Alliander is facing an increasing shortage of technical personnel. That’s why it’s important that our technicians are as productive as possible. Our experienced technicians possess extensive knowledge and expertise in work content/processes, electrical engineering, and safety. Analyses show that experienced technicians spend 20% of their time supporting and answering questions from other technicians.

At the same time, there is a clear aging trend within Alliander: by 2030, approximately 700 technicians will retire. These colleagues hold specific practical and experiential knowledge that plays an important role in Alliander’s operations. This knowledge is only partially documented in formal knowledge sources.

We’re therefore looking for innovative solutions that help extract, capture and safeguard experiential knowledge , and can also unlock it. Hands‑free solutions  in  the flow of work, and fully compatible with Personal Protective Equipment need in the field,  so technicians can access what they need anytime and anywhere. As a result, they can perform their work better, more safely, and more efficiently. This should result in experienced technicians gaining more time for their core tasks and new technicians being able to start working independently more quickly and safely.

Solutions could include (a mix of) AI, mixed reality and image recognition. Consider, for example, a voice-controlled, AI based digital coach that provides field technicians with relevant information and real time data proactively and projects supportive visual information onto smart glasses. This system can watch along during the work—both proactively providing information and data, and capturing the work itself, thereby preserving experiential knowledge as part of the workflow.

Topic

  • Artificial Intelligence
  • Machine Learning
  • Edge/Cloud computing
  • Natural Language Processing
  • Robotics
  • Image analysis and tagging
  • Text analysis and tagging
  • VR/AR/MX
  • Audiovisual
  • Computer vision
  • Video processing, encoding, tagging
  • Voice / Audio

Type

  • Proof of concept/pilot testing
  • Co-development
  • Client-provider collaboration (commercial agreement)

Organisation

Alliander Next Grid

Corporation

Arnhem, Netherlands

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