Before artificial intelligence (AI) can be utilized to efficiently expedite the energy transition, the energy sector must overcome a lack of faith in the technology, according to a DNV assessment.
DNV’s research found that while AI is currently being employed throughout the industry, corporations are often wary of its novel and unproven uses. This conclusion was based on interviews with top officials from energy companies around the United Kingdom. Interviewees include business representatives from, among other organizations, the National Grid Electricity System Operator (ESO), the Centre for Data Ethics and Innovation, EnQuest, National Gas, and the Net Zero Technology Hub.
The report “AI insights: Rising to the challenge across the UK energy system” explains how AI may aid in the energy transition and that, in order to fully realize its potential, an industry-wide approach to standards and best practices is necessary.
The research found that while building the foundations for trust in the providers of AI solutions and the outputs of those solutions must be prioritized in light of recent geopolitical events highlighting the need for countries to have energy sustainability, security, and affordability – in effect, a parallel trilemma for AI as it is increasingly democratized and used. Despite the fact that AI can be essential to advancement and innovation in energy supply chains, the research found that this is not the case. It was also discovered that there are major impediments to its wider implementation due to data rules and industry culture.
Data sharing has been highlighted as the area in the sector that needs the most development. It was discovered that the technical community has a poor tolerance for error and a high level of risk aversion.
It’s imperative that this technology be trusted in order to fully reap the benefits of AI in the energy sector, according to Hari Vamadevan, Executive Vice President and Regional Director UK and Ireland, Energy Systems at DNV. In order to do this, there are two major obstacles to overcome: gathering data to assess an AI system’s credibility, and communicating evidence that enables consumers to place their trust in the systems.
The most recent in DNV’s collection of “digital twins” recommended practices now encompasses AI-enabled systems, offering a framework to ensure that systems are reliable and responsibly managed over their full lifecycle. DNV has extensive experience with AI.
With rising geopolitical tensions and an increase in the use of digitally connected infrastructure, the emergence of artificial intelligence also brings with it hazards to the sector’s cyber security. These risks include industry weaknesses to online threats.
Digital technologies and AI tools must be accurate, accessible, dependable, and relevant if we are to trust them, according to Shaun Reardon, Head of Section, Industrial Systems, Cyber Security at DNV. However, they must also be safe. In the energy sector, where safety is crucial, digital technologies are being linked to operational technology, which will be improved by AI. The sector needs to control the risk of cyber security and foster confidence in the security of these crucial technologies.
