Businesses from the Middle East and Africa’s resource industries (oil and gas mining, other mining, and agriculture) spent $5,17-billion on information and communications technology (ICT) in 2019, according to the latest insights from International Data Corporation (IDC).

The global technology research, consulting, and events firm forecasts this figure to reach $5,33-billion this year and continue rising at a compound annual growth rate of 4,1% over the coming years to reach $5,79-billion in 2023.

“The oil industry is facing unprecedented challenges,” says Gaurav Verma, oil and energy research manager at IDC Energy Insights. “Many industry experts believe that the era of ‘easy oil’ is over and that companies will have to explore new frontiers which pose more operational challenges.

“The complexities of extracting hydrocarbons in harsh and remote environments such as ultra-deep-water oil fields, coupled with uncontrollable external pressures and oil market volatility, are driving oil and gas companies to adopt digital transformation (DX) initiatives as they strive to enhance their levels of efficiency, agility, and resilience.”

This pursuit of DX is driving a shift in investment focus for oil and gas companies, with many now turning to cloud to enable the enhanced efficiency and data-driven decision-making that their new strategic priorities require.

Consequently, IDC expects that by 2021 about 75% of oil and gas companies worldwide will have moved the majority of their on-premises applications to the cloud to facilitate scalability and digital innovation across the organization.

The industry’s multifaceted transformation is also driving increased interest in artificial intelligence and machine learning as organizations look to augment employee productivity, boost business agility, and address the implications of an ever-growing skills gap.

As such, IDC expects that by 2022, 90% of oil majors worldwide will have deployed AI-powered applications to various exploration processes ranging from automated drilling to cognitive seismic data analysis to reservoir modeling.