Artificial Intelligence in Oil and Gas Market Size, Share & Trends Analysis Report By Type (Hardware, Software, Services), By Function (Predictive Maintenance and Machinery Inspection, Field Service, Material Movement, Production Planning, Quality Control, Field Services, Reclamation), By Application (Upstream, Midstream, Downstream) and By Region(North America, Europe, APAC, Middle East and Africa, LATAM) Forecasts, 2025-2033

Artificial Intelligence in Oil and Gas Market Size

The global artificial intelligence in oil and gas market size was valued at USD 16.22 billion in 2024 and is projected to reach from 18.32 billion in 2025 to USD 48.72 billion by 2033, growing at a CAGR of 13% during the forecast period (2025-2033).

The energy industry values commodities like oil and gas. Artificial intelligence (AI) has many uses in the oil and gas sector, including streamlining maintenance procedures and introducing cost-effectiveness. With multiple AI software in upstream, midstream, and downstream oil and gas industry applications, intelligent robots are replacing human labor with efficient work at offshore and onshore sites. Operational efficiency gains, cost savings, predictive intelligence capabilities, and increased safety precautions and strategies are the main benefits of artificial intelligence in the oil and gas sector. Artificial intelligence is new to all industries, but after a sluggish start in the oil and gas sector, the sector has only recently adopted it due to its many advantages. It aids businesses in maintaining lower costs while increasing efficiency. Many issues that older methods of solving constituted are lauded as being solved by AI. For instance, the offshore oil industry uses drilling rigs that are completely automated or autonomous. In the oil and gas industry, AI helps identify issues earlier and more quickly, schedule maintenance, reduce costs, boost operational effectiveness, plan safety measures, cut downtime, ensure quality, and increase output. As a result, it's also applied to enhance quality assurance, material flow, production scheduling, and equipment inspection.

Artificial Intelligence in Oil and Gas Market Growth Factors

Encourages strict security and safety measures

The upstream, midstream and downstream processes are all improved by AI. Oil and gas are hazardous due to their flammability and the release of toxic fumes. Systems using artificial intelligence can monitor toxicity levels and leaks and notify users of problems that must be fixed. Temperature variation is an additional safety risk in the oil and gas industry. AI can automatically change the cooling and heating systems to keep the product safe as the seasons change throughout the year. Additionally, artificial intelligence will alert the maintenance crew when the processing and transportation of crude oil require maintenance. The main factor influencing the growth of AI in the Oil and Gas market is the maintenance of the deteriorating pipeline infrastructure. Additionally, the market is anticipated to grow due to the increasing incidents of oil and gas leaks from storage tanks and pipelines at production facilities.

Assist in minimizing the impact of brain drain on the industry

According to a recent report, nearly 54% of its members are over 55, which suggests that the industry desperately needs young talent. Additionally, younger workers aren't replacing the older generation of workers who are retiring at the same rate. AI can automate various tasks while preserving and implementing the knowledge of seasoned workers. Machine learning is used to identify patterns in data for the practical application of data analytics, and expert insights will aid in creating the necessary complex algorithms for it. Information retrieval systems with intuitive AI capabilities can record text and voice input from retired people and experts. It uses natural language processing, which can organize the knowledge and experience of retirees in ways that any other worker could understand.

Restraining Factors

High emissions of greenhouse gases, such as carbon dioxide

Coal is to blame for more than 0.3C of the 1C rise in average global temperatures as the dirtiest fossil fuel. As a result, it is the primary cause of the rise in global temperatures. Burning oil results in significant carbon emissions; it accounts for about one-third of global carbon emissions. Additionally, there have been several oil spills in recent years that have had a catastrophic effect on the ecosystem of our oceans. As a result, it is the primary cause of the rise in global temperatures. Burning oil results in significant carbon emissions; it accounts for about one-third of global carbon emissions.

Market Opportunity

Artificial intelligence greatly improves quality assurance.

The risk factors are high; the oil and gas industry is dynamic. The applications and uses of AI-based technologies are endless. This improves the standard of the entire procedure from the beginning of exploration to the end of natural gas and crude oil processing and purification. This is accomplished by immediately correcting any risks that are currently present or that may arise in the future. The oil and gas industry benefits from adopting artificial intelligence in several ways, including increased operational effectiveness and cost savings. The most important of these is safety during operations because the oil and gas sector is a dangerous one with a constant risk of equipment failure, gas or oil leaks, and frequently occurring toxic chemical reactions.

Regional Analysis

North america dominates the global market

North America is the most significant shareholder in the global artificial intelligence in the oil and gas market and is expected to grow at a CAGR of 12.6% during the forecast period. The U.S. and Canada are included in the analysis of artificial intelligence in North America’s oil & gas market. Because more private and public organizations are funding the development of better system suppliers in the oil and gas industry, this growth is attributed to the increasing use of AI technologies by oilfield operators as well as the widespread distribution of top AI software and system providers, particularly in the United States and Canada. One of the most well-known oil producers in the US, ExxonMobil, recently announced plans to increase production in the West Texas Permian Basin by producing over 1 million barrels per day (BPD) of oil equivalent by as early as 2024. Compared to the current production capacity, this represents an increase of almost 80%.

Asia pacific is the fastest growing region

Asia Pacific is expected to grow at a CAGR of 13.5% during the forecast period. China, India, Japan, Australia, and the rest of Asia-Pacific are all included in the analysis of the Asia-Pacific artificial intelligence in the oil and gas market. Actions are taken to meet the region's growing demand for passenger cars and the rising fuel prices. The rapid uptake of AI technologies by oilfield operators and service providers, the prevalence of top AI software and system vendors, and the combined investment of public and private organizations in R&D activities. Although artificial intelligence is increasingly being used in the oil and gas sector, overall adoption is still relatively low compared to other industries. There are many opportunities to develop advanced artificial intelligence systems in this industry sector to automate further, enhance, and optimize operational and business efficiencies. A massive opportunity for the artificial intelligence market to expand in the oil and gas industry is also created using data analytics combined with artificial intelligence.

Segmental Analysis

By type

The software segment is the highest contributor to the market and is expected to grow at a CAGR of 12.8% during the forecast period. Contributing to more than 75% of the global market for AI in the oil and gas industry, it is anticipated that it will keep the top spot throughout the forecast period. This is because numerous solutions can be used for fleet management, production planning, predictive maintenance, and quality control. Due to seamless end-to-end user experiences and the use of artificial intelligence (AI) in oil and gas services to help users achieve their goals without having to visit multiple websites, the services segment is predicted to grow.

By function

The production planning segment is the highest contributor to the market and is expected to grow at a CAGR of 13.2% during the forecast period. Offshore oil projects frequently experience problems with budget and schedule overruns. Here, weather delays, resource limitations, and scheduling risks are crucial. The numerous siloed activities that make up the build-up phase of oilfield development, including drilling and platform installation, add to the process’s complexity. Finding reliable project planning and scheduling models that consider the interdependence of these interacting components and the risks associated with it is crucial in this situation.

By application

The upstream segment is the highest contributor to the market and is expected to grow at a CAGR of 12.72% during the forecast period. In the upcoming years, it is anticipated to keep up its dominance. It involves looking for potential raw natural gas and crude oil fields underground or under the sea, drilling test wells, and then drilling and running the wells that will bring the raw natural gas or crude oil to the surface. However, midstream activities, which include the storage, processing, and transportation of petroleum products, are anticipated to experience the highest growth rate during the Al in Oil and Gas Market Forecast period. These might include firms devoted to running storage facilities, pipelines, or tanker ships.

Recent Developments

• May 2022, the world's first graduate-level artificial intelligence (AI) research center, the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), is preparing a partnership with IBM. 

• May 2022, Despite holding its developer conference I/O 2022 later than planned, Google has increased its focus on developing machine learning (ML) and artificial intelligence (AI). Both product development and research are its main priorities. PaLM is a novel approach to artificial intelligence and natural language processing. According to the most significant, it is Google's largest model and has been trained on 540 billion parameters.