Nearly a third of all oil and gas jobs in Canada could shift to automatic mode in the next 20 years. The report came from EY Canada and the Petroleum Labour Market Information Division of Energy Safety Canada.
New technologies driving the change include robotic process automation, artificial intelligence, natural language processing, and machine learning.
Lance Mortlock, EY Canada Oil & Gas Lead commented on the subject. He said that black swan events are pushing oil and gas companies to drive down operating costs. It is also transforming work processes to improve margins. “Unfortunately, these cuts have resulted in job layoffs,” said Lance Mortlock, EY Canada Oil & Gas Leader.
Many companies had already begun the transition. However, the COVID-19 pandemic created a new sense of urgency, Mortlock said.
In addition, 50% of the oil and gas jobs in Canada and their competencies upstream will be automated. So workers must develop skills in emotional intelligence, critical thinking and data analysis to be competitive. Upstream refers to stages that involve exploration and production for oil and gas. Downstream refers to activities that are closer to the consumer.
The automation of oil and gas jobs in Canada
The automation and AI impact on an oil and gas organization can be considered from multiple perspectives. For example, understanding the impact on competency types can help individuals, organizations and educators retool skill-sets as the shift gradually takes place. Understanding the impact on individual jobs and job families provides valuable insight into planning the workforce of the future.
Besides, competencies have been grouped into five broad categories based on their characteristics: Leadership, Foundational, Behavior, Knowledge and Technical. Individual roles have been grouped into one of 14 families considering multiple factors. So this includes competency profiles, American Petroleum Institute groupings and groupings that are commonly popular in industry.
The competency analysis shows the expected impact on competencies by the year 2040. Technical competencies have the most potential for automation due to the high level of predictability and social feasibility. Additionally, many organizations have already begun digitizing technical competencies and the economic feasibility is likely to improve in the coming years. On the other end of the spectrum, leadership competencies have the least potential for automation. A common characteristic of leadership competencies is that their automation is unlikely to be socially feasible for the foreseeable future.
Read the full report here