AI Centre of Excellence – GB Industry Data Science Fellowship Scheme

Project summary

The success of the Net Zero transition requires attracting and retaining individuals with specialist data science skills and capabilities, as articulated in the UK’s National AI Strategy.

Name Status Project reference number Start date Proposed End date
AI Centre of Excellence – GB Energy Industry Data Science Fellowship Complete NIA2_NGESO071 Feb 2024 Jun 2024

 

Strategy theme Funding mechanism Technology Expenditure
Net zero and the energy system transition NIA_RIIO-2 Comms and IT £230,000
Summary

The current ESO data science talent pipeline is decentralised and lacking coordination among industry, academia, tech partners and other various stakeholders. This project will aim to establish the design of an enduring and mutually beneficial fellowship to create a steady pipeline for data science skill and capabilities for ESO and the energy sector. This will create a mechanism for industry engagement and support addressing the skills gap across private, public, and academic institutions required for the net zero transition.

Benefits

This project will develop a first of its kind, well-defined, targeting scheme that is mutually beneficial for organisations across the energy sector, building on the foundations established by the AI Centre of Excellence (AI CoE). It will test ideas, assure feasibility and de-risk delivery of the foundation scheme, while informing the design of potential future programmes and delivering against the AI CoE core functions and objectives. The project will create a mechanism for industry engagement, and support addressing the skills gap across private, public, and academic institutions. It will establish a delivery method for a fellowship programme, and placement of applicants in strategic ESO projects. Overall, the project will deliver the foundations required to ensure the energy sector has access to the data science skills necessary for the net zero transition.

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Learnings

Outcomes

  • Delivered vision, mission and ambition for the AI Centre of Excellence. 
  • Delivered an AI Use case framework and engaged with the ESO business extensively to identify over 100 AI/ML opportunities. 
  • Delivered a roadmap to deliver for MVP phase and beyond. 
  • Positive engagement with key stakeholders including ESO exec on development of the AI CoE 
  • Delivered an academic partnership framework to assess and establish partnerships with academia. 
  • Delivered an MoU and MoA framework review 
  • Delivered options paper on Funding and operating models for the AI CoHackathon launched and completed on Kaggle. We had 251 entrants and 569 submissions. 
  • Collated open data and curated it for public consumption and use in ML Hackathon. 
  • Delivered an AI knowledge hub, with a robust design to be opened up externally when required. 
  • KPIs in place and UAT sessions delivered to iterate the design 

Lessons Learnt

  • Business engagement is key, having early and consistent stakeholder engagement with ESO staff has been critical to the success of the AI Centre of Excellence so far. 
  • Strategic alignment has been critical to making sure the AI CoE serves the needs of the business and helps deliver on priorities. 
  • Knowledge hub requires significant buy in from the business to maintain, key stakeholder engagement was required and more time could have been dedicated there. 
  • Hackathon was incredibly successful, one lesson from this competition was to be firm with your goal and set expectations ahead of time and be explicit with them. We were clear with the goal of a hackathon to provide a dataset and problem for people outside of the energy industry to engage and get excited.