Doha: Senior officials at energy companies emphasized that the natural gas liquefaction industry is moving toward digitalizing operational processes, but this requires some time to achieve, due to the radical changes digitalization may bring to the sector. This came during a panel discussion on digital transformation in the LNG industry, held on the final day of the 21st International Conference on Liquefied Natural Gas (LNG 2026), where participants discussed strategic innovations and future trends in digital transformation in the LNG industry, and how advanced technologies can revolutionize the sector.
According to Qatar News Agency, they also discussed the role of artificial intelligence and machine learning in improving operational processes in the LNG industry, enhancing predictive maintenance, and increasing the efficiency of supply chains, in addition to strengthening cybersecurity measures to protect critical LNG infrastructure from cyber threats and ensure the safety of digital operations.
Participants also addressed the application of digital twin technology to create virtual replicas of LNG facilities, enabling better asset management and higher operational efficiency. Vice President of Gas and Low-Carbon Energy at Technip Energies, Dominique Gadelle, noted that digitalizing the LNG industry requires time to change ways of working that have been in place for decades, stressing that the energy sector does not favor rapid change and therefore evolves gradually.
He said that it's more about educating people and explaining the importance of digitalization, as everyone needs to understand and be confident in this transition. Meanwhile, Senior Vice President of Energy Sectors for the Middle East and Africa at ABB, Bjart Pedersen, confirmed that updates in existing facilities for digitalization and AI will take time, along with the need for qualified personnel.
In the same context, Senior Vice President at ABS, Joshua Divin, explained that the energy sector is conservative and risk-averse, particularly regarding safety. This cautious approach is due to the need to focus on regulatory aspects and ensure the safe use of artificial intelligence.