The Data Science team at National Grid stands out for the technical sophistication of its work and the depth of its integration across the organization, its culture of collaboration, and the measurable value it delivers at scale. In a sector under mounting pressure to modernize, decarbonize, and deliver, this team is demonstrating what it truly means to operationalize AI responsibly, efficiently, and with a clear focus on outcomes.
Operating within a robust hub-and-spoke model, the team supports every facet of National Grid’s business: from core operations to customer-facing functions and innovation units. This is AI as a service, embedded into the rhythm of the organization. The structure allows the team to serve local needs while maintaining strategic alignment with the CDO’s broader goals around data governance, infrastructure, and capability development.
A defining feature of this team is its commitment to “doing AI with the business, not to it.” Their work on Safety Analytics exemplifies this ethos. By visiting sites, deeply understanding operational realities, and tailoring solutions through diverse techniques, the team has transformed safety from a reactive metric to a proactive discipline. Their insights into risk profiles by job type and location are informing policy internally and across peer utilities, thanks to knowledge-sharing at industry forums.
The team’s impact goes beyond being conceptual. Tools like RADAR deliver tangible financial results. By identifying and resolving revenue leakage from thefts or faulty meters, this application has saved millions and streamlined operations. Its success goes beyond financial metrics, with the enhanced hit rate improving employee productivity and customer satisfaction, while replacing an external vendor demonstrates the value of building internal capability.
What elevates the team from technically competent to industry-leading is its dual focus on delivery and enablement. Through initiatives like Connect AI, the AI Academy, and the DataConnect Community of Practice, the team is raising the organization’s collective AI IQ. Their commitment to peer learning via technical knowledge shares, project-based mentoring, and external conference participation ensures that excellence is scaled effectively.
Their objectives are aligned directly with National Grid’s core mission: advancing the energy transition, improving safety, and enhancing customer experiences. Every project is measured not just on deployment, but on metrics like customer Net Promoter Scores, ROI, and production job pass rates. This reflects a mature approach to AI, treating it as a sustained capability and not an experiment.
In a field crowded with pilot projects and inflated expectations, the Data Science team at National Grid has built a foundation of trust, delivered transformative results, and elevated the entire organization’s relationship with data. They are shaping what an AI-powered utility should look like, and their rigor, reach, and real-world impact has set a benchmark.
