Only 5.7 percent of oil and gas companies used AI in the past year. 48 percent of respondents report AI solutions implemented at some scale. The market for AI software and services in the sector is projected to reach 10.2 billion dollars.
Key Takeaways
- 5.7% of oil and gas companies used AI in the last 12 months in 2023
- 29% of oil and gas executives in 2023 reported using AI in at least one business function
- 36% of oil and gas respondents in 2023 said they were piloting AI
- $7.6 billion of AI software and services revenue was generated globally in oil & gas in 2023 (forecast based on market model)
- $4.1 billion global market size for AI in oil & gas was estimated for 2022
- $10.2 billion expected global AI in oil & gas market size by 2030 (CAGR implied by vendor forecast)
- 25% improvement in lifting accuracy reported from AI-based reservoir production forecasting models (reported 2020)
- 35% reduction in emissions intensity achievable when AI improves compressor efficiency (reported by industry analysis in 2022)
- 17% reduction in risk-costs from improved anomaly detection leading to fewer safety incidents (reported 2021)
- Up to 30% reduction in operating costs from AI-driven optimization in oilfield production (reported across industry cases, 2020)
- 2–4% reduction in annual energy costs possible via AI optimization for industrial energy systems (energy operations relevant to oil & gas, 2022)
- 15% reduction in data labeling and model-training cost via transfer learning in industrial ML deployments (study 2020)
In 2023 oil and gas AI adoption accelerated, with nearly half already implementing solutions and the market set to grow rapidly.
Related reading
01 · Category
User Adoption5 stats
01
5.7% of oil and gas companies used AI in the last 12 months in 2023
02
29% of oil and gas executives in 2023 reported using AI in at least one business function
03
36% of oil and gas respondents in 2023 said they were piloting AI
04
48% of oil and gas respondents in 2023 said they had implemented AI-related solutions at some scale
05
42% of oil and gas companies reported that AI initiatives are in the planning stage in 2023
Interpretation
User Adoption Interpretation
From the user adoption perspective, AI uptake in oil and gas looks meaningful but still early, with 48% reporting AI solutions implemented at some scale in 2023 while only 5.7% used AI in the last 12 months and another 42% are still planning initiatives.
02 · Category
Market Size14 stats
01
$7.6 billion of AI software and services revenue was generated globally in oil & gas in 2023 (forecast based on market model)
02
$4.1 billion global market size for AI in oil & gas was estimated for 2022
03
$10.2 billion expected global AI in oil & gas market size by 2030 (CAGR implied by vendor forecast)
04
AI software and services in the oil & gas segment was forecast to grow at a 27.2% CAGR from 2024 to 2030
05
Artificial intelligence in upstream oil & gas market size was forecast at $1.8 billion in 2023
06
$2.9 billion estimated market for AI-based predictive maintenance in oil & gas in 2023
07
$1.4 billion estimated market for machine learning in upstream oil & gas analytics in 2022
08
$5.2 billion global industrial AI software market projected for 2024 (oil & gas among industrial end users)
09
$20.7 billion projected global AI software market in 2024 (context for AI spend relevant to oil & gas)
10
$6.6 billion global AI in energy market projected for 2025 (oil & gas included as part of energy)
11
$4.3 billion global market size for industrial IoT platforms in 2023 (oil & gas included as an industrial end user segment)
12
$10.2 billion expected global AI in oil & gas market size by 2030 (CAGR implied by vendor forecast)
13
US$3.4 billion global investment in AI for energy and utilities in 2023 (includes oil & gas under broader energy AI spending)
14
US$2.0 billion global spend on AI-enabled software for industrial asset management in 2022 (oil & gas among key process industries)
Interpretation
Market Size Interpretation
In the market size category, global AI spending in oil and gas is projected to more than double from about $4.1 billion in 2022 to roughly $10.2 billion by 2030, while strong growth forecasts like a 27.2% CAGR from 2024 to 2030 signal a rapid scale up across the AI software and services market.
More related reading
03 · Category
Performance Metrics5 stats
01
25% improvement in lifting accuracy reported from AI-based reservoir production forecasting models (reported 2020)
02
35% reduction in emissions intensity achievable when AI improves compressor efficiency (reported by industry analysis in 2022)
03
17% reduction in risk-costs from improved anomaly detection leading to fewer safety incidents (reported 2021)
04
35% reduction in compressor emissions intensity achievable when AI improves compressor efficiency (industry analysis in 2022)
05
2% average annual reduction in energy consumption from AI-optimized industrial energy systems (system-level study)
Interpretation
Performance Metrics Interpretation
Across performance metrics, AI is delivering tangible operational gains in oil and gas, with improvements such as a 25% lift in reservoir forecasting accuracy, up to 35% reductions in compressor emissions intensity, and a steady 2% average annual cut in energy consumption.
04 · Category
Cost Analysis6 stats
01
Up to 30% reduction in operating costs from AI-driven optimization in oilfield production (reported across industry cases, 2020)
02
2–4% reduction in annual energy costs possible via AI optimization for industrial energy systems (energy operations relevant to oil & gas, 2022)
03
15% reduction in data labeling and model-training cost via transfer learning in industrial ML deployments (study 2020)
04
17% reduction in risk-costs from improved anomaly detection leading to fewer safety incidents (reported 2021)
05
35% decrease in time-to-value from commissioning AI models after integration with existing SCADA historians (reported 2022)
06
15% reduction in data labeling and model-training cost via transfer learning in industrial ML deployments (study 2020)
Interpretation
Cost Analysis Interpretation
The cost analysis trend across oil and gas use cases is that AI is delivering measurable savings of up to 30% in operating costs and around 2 to 4% in annual energy costs, while also cutting implementation and ongoing expenses such as roughly 15% in data labeling and training costs and 17% in risk related costs from fewer safety incidents.
report visual · Key figures
AI adoption and rollout in oil & gas (2023)
Use of AI spans from reported adoption to piloting and implementation, showing steady progression of AI initiatives.
5.7%
5.7% of oil and gas companies used AI in the last 12 months in 2023
29%
29% of oil and gas executives in 2023 reported using AI in at least one business function
36%
36% of oil and gas respondents in 2023 said they were piloting AI
48%
48% of oil and gas respondents in 2023 said they had implemented AI-related solutions at some scale
42%
42% of oil and gas companies reported that AI initiatives are in the planning stage in 2023
source-verifiedstatista.com2023
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Rachel Svensson. (2026, February 13). AI In The Oil Gas Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-oil-gas-industry-statistics
MLA
Rachel Svensson. "AI In The Oil Gas Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-oil-gas-industry-statistics.
Chicago
Rachel Svensson. 2026. "AI In The Oil Gas Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-oil-gas-industry-statistics.
Sources & references
30 datasets cited across this report · attribution is report-level
+12 additional datasets cited (not shown individually)