The energy sector is undergoing a huge transformation towards green transition, efficiency improvements and digitalization. The use of artificial intelligence and advanced forms of data analysis is constantly increasing in scope and will be crucial to the success of the changes.
The opportunities associated with artificial intelligence and data analytics in the energy sector are enormous. The technology has the potential to drastically cut costs, streamline the entire oil and gas value chain, help reduce risk and downtime while increasing control and profitability. Not least, intelligent data analytics gives energy companies the ability to make informed decisions, for example by utilizing seismographic data that leads to better predictions of where to drill - the technology automates many processes and increases profitability.
Significant efficiency gains
Energy companies are currently using artificial intelligence and data analysis to achieve a number of efficiency gains. The most advanced players are using the technology to plan projects better, make better decisions than before and automate a number of tasks. Operating and maintenance costs are reduced while profitability increases.
Here are three concrete examples of how energy companies are achieving gains with artificial intelligence and data analytics:
- Quality inspections are improved with intelligent video analysis based on photos and video from drones and ROVs (remotely operated vehicles).
- Data patterns based on logs from operational, sensor and machine data, IoT and data on how different performance of different suppliers are used to improve the quality of services and operations.
- Artificial intelligence and data analytics improve demand forecasting and reduce downtime and downtime and losses in projects. This by using data from digital twins, remote operations, control centers, assets and other condition-based monitoring.
So how do you realize AI?
To reap the benefits of artificial intelligence and advanced data analytics, companies depend on a modern data ecosystem and a digital core. This is something leaders in both global and Norwegian companies have realized. The change involves migrating data and systems to the cloud, creating cohesive stories by tearing down data silos and enriching new data sources, applying unused dark data and using industry-specific machine learning models and image analysis tools.
Combining local knowledge with global best practice
As one of the world's largest artificial intelligence and data analytics consultancies, with over 400 AI experts in the Nordics alone, Cognizant works to operationalize and implement data, AI and analytics solutions at some of the world's largest companies. We help our customers modernize technology, redefine processes and transform experiences so they can lead in a changing world. Together, we make everyday life better.
Five steps to becoming AI-ready
Everyone is talking about AI, but what is actually required of businesses that want to adopt this powerful technology?
To succeed with AI initiatives, businesses need to take several major steps. Based on our analysis and experience, we have created five overarching pieces of advice for businesses that want to embrace the technology.
1) Modernize your data infrastructure so that data resources can be better utilized, provide new insights and contribute to better decisions.
2) Get rid of technical debt. Legacy systems with complex integrations and a lack of standardized APIs struggle to keep up with the demands and real-time computing needs of AI.
3) Invest in talent with not only AI skills, but also the motivation and capacity for continuous learning.
4) Prioritize the responsible use of AI to achieve positive outcomes for customers, employees and society as a whole.
5) Cultivate an AI-friendly culture that embraces change and dispels misconceptions and fears.
