Latest Digital Technologies to Create Paradigm Changes in the Energy Sector
The energy sector has long pioneered the use of transformational technologies. And now with the increasing potential of AI that enables unlimited amount of data to be ingested, interpreted and acted upon, this sector faces a wave of change. With such potential, AI will enable operations to run the energy sectors more efficiently and productively at an ever lower cost. Mckinsey estimates that by 2035,data analytics and robotics alone could produce between $290m and $390bn in annual productivity savings for oil, natural gas, thermal coal, iron ore and copper producers across
“A couple of years ago what we’re doing now would have been very expensive because computer storage and processing power was cost prohibitive. A reduction in the cost of technology and an increase in the availability of data is a key factor here,” says Harry Bloch, CFO of start-up VROC AI which provides predictive maintenance solutions to the oil and gas sector. With cost falling rapidly and easy availability of data processing paraphernalia, new area of computer science has emerged- from symbolic learning involving image processing and robotics to more complex algorithm-based pattern recognition and reinforced machine learning using neural networks—that will lead to a rapid acceleration in the use of AI across the sector. Developments in quantum computing are set to take cognitive computing to an even more advanced level.
For an industry based on technological transformation, energy companies have been surprisingly slow to recognise the potential of AI.According to Global Human Capital Trends 2018 report , Deloitte notes that AI, robotics and automation alone are still rated relatively low by the energy industry, despite robotics in particular taking a significant foothold over the past 1218 months.
One of the major factors that constrains the use of AI in the oil and gas sector is the shortage of qualified individuals. According to Element AI, fewer than 10,000 people globally have the required skills to undertake significant research in this area.As AI evolves, the skill sets required to drive it into the future will also adjust. “The industry is changing from being one that had an element of human capital to one that now has central processing unit (CPU) power. AI combined with machine learning and algorithms means the roles for data scientists are rapidly changing,” VROC’s Bloch says. Currently to overcome the immediate recruitment hurdles, many energy companies are opting to outsource AI work.