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Lithium Ionic Reports Updated Mineral Resource Estimate at its Bandeira Lithium Project, Minas Gerais, Brazil; Significantly Increases Global Mineral Resources in the Lithium Valley

Lithium Ionic Reports Updated Mineral Resource Estimate at its Bandeira Lithium Project, Minas Gerais, Brazil; Significantly Increases Global Mineral Resources in the Lithium Valley

Business Upturn06-05-2025
TORONTO, May 06, 2025 (GLOBE NEWSWIRE) — Lithium Ionic Corp. (TSXV: LTH; OTCQX: LTHCF; FSE: H3N) ('Lithium Ionic' or the 'Company') is pleased to announce an updated mineral resource estimate ('MRE') for its 100%-owned Bandeira Lithium Project ('Bandeira' or the 'Project') located in Minas Gerais, Brazil. Bandeira is the Company's flagship property, located in Brazil's 'Lithium Valley', a rapidly emerging hard rock lithium district renowned for its significant concentration of lithium-bearing pegmatites.
Prepared in accordance with National Instrument 43-101 ('NI 43-101') by independent consultants, GE21 Consultoria Mineral Ltda. ('GE21'), the updated MRE reflects continued growth and resource conversion across the deposit, underscoring the scale, geological continuity, and long-life potential of Bandeira as it advances toward development.
Bandeira Project – Mineral Resource Estimate Highlights Measured and Indicated ('M&I') MRE of 27.27 million tonnes ('Mt') grading 1.34% Li₂O, containing 901,059 tonnes of lithium carbonate equivalent ('LCE'); with an additional Inferred MRE of 18.55Mt grading 1.34% Li₂O, or 615,432 tonnes of LCE (see Table 1).
M&I growth represents a 30% increase in tonnage compared to the MRE used in the Company's Feasibility Study announced on May 29, 2024, and a 15% increase compared to the MRE announced on April 12, 2024.
The updated MRE is based on 297 drill holes (60,301 metres), drilled between April 2022 and September 2024.
The MRE maintains consistent grade while expanding tonnage, reflecting strong continuity and growth potential.
The updated Bandeira MRE increases the consolidated, global mineral resources to 36.76 Mt grading 1.31% Li₂O in the M&I category, in addition to 31.87 Mt grading 1.19% Li₂O in the Inferred category (see Figure 1).
The Company plans to integrate the new MRE into an updated Feasibility Study, expected in H2 2025.
*See press release dated January 14, 2025, for details related to the Baixa Grande MRE (effective date of December 2, 2024; QP: Leonardo Soares, P.Geo., M.Sc., of GE21), and the NI 43-101 compliant technical reports related to the Outro Lado deposit titled 'Mineral Resource Estimate for Lithium Ionic, Itinga Project' (effective date of June 24, 2023; authored by Maxime Dupéré, B. Sc., P.Geo. and Faisal Sayeed, B. Sc., P.Geo).
Blake Hylands, P.Geo., CEO of Lithium Ionic, commented, 'Bandeira continues to grow substantially while maintaining consistent grade, further validating its robustness and scale potential. This updated resource supports our mine planning efforts and will be an important input as we work through detailed engineering and evaluate future production scalability.'
Carlos Costa, P.Geo., Lithium Ionic's VP of Exploration, commented, 'Since we first began exploration at Bandeira in April 2022, the Project has consistently exceeded our expectations. What started with just two promising rock samples has evolved into one of the largest spodumene-rich pegmatite deposits in the Jequitinhonha Valley. I am extremely proud of the capability, dedication, and achievements of our entire exploration team, and we believe there is still significant potential ahead.'
The NI 43-101 technical report for the Bandeira MRE (the 'Technical Report'), will be accessible on SEDAR+ (www.sedarplus.ca) under the Company' issuer profile, and on the Company's website, www.lithiumionic.com, within 45 days of this news release.
About the Bandeira Project
Bandeira covers 158 hectares, less than 1% of Lithium Ionic's 17,000-hectare land position, but has rapidly advanced to become one of the most promising lithium development-stage assets in Brazil. It is located adjacent to Sigma Lithium's Grota do Cirilo and Barreiro projects and directly beside Companhia Brasileira de Lítio's (CBL) long-standing underground lithium operation.
The Company has also established NI 43-101 compliant mineral resource estimates at two additional properties within the 'Lithium Valley', Baixa Grande (formerly Salinas) and Outro Lado. Together, these assets bring Lithium Ionic's consolidated global mineral resource base to 36.76 million tonnes ('Mt') (1,188,473 LCE) in the Measured and Indicated category, in addition to 31.87 Mt (936,196 LCE) in the Inferred category, with the majority of the Company's regional land package remaining largely unexplored.
A NI 43-101 compliant feasibility study (the 'Feasibility Study', the 'Study') for Bandeira was announced on May 29, 2024, which outlined strong project economics, including a post-tax NPV 8% of US$1.31 billion and an IRR of 40%. This Study was based on a smaller MRE with a data cut-off of November 13, 2023. This Feasibility Study remains valid and will be part of the forthcoming Technical Report, however the Company intends to integrate the expanded MRE into an updated Feasibility Study in the second half of 2025. On April 2, 2025, the Company engaged the globally recognized lithium advisory firm, RTEK International DMCC ('RTEK'), to help transition Bandeira from feasibility to construction and operations.
Table 1 – Bandeira Lithium Project Mineral Resource Estimate Deposit /
Cut-Off Grade Category Resource
(Mt) Grade
(% Li2O) Contained LCE
(kt) Bandeira
(0.5% cut-off)
Measured 3.36 1.38 114.7 Indicated 23.91 1.33 786.4 Measured + Indicated 27.27 1.34 901.1 Inferred 18.55 1.34 614.7 The Mineral Resource Estimation (MRE) effective date is November 20, 2024. The MRE has been prepared by Carlos J. E. Silva (MAIG #7868) in conformity with the CIM Estimation of Mineral Resource and Mineral Reserves Best Practices guidelines. The report adheres to the Canadian Securities Administrators' NI 43-101 requirements. Mineral resources are not mineral reserves and have not demonstrated economic viability. There is no certainty that any portion of the mineral resource will be converted into a mineral reserve. Figures are rounded to appropriate levels of precision, and discrepancies may occur due to rounding. The spodumene pegmatite domains were modelled using composites with Li₂O grades exceeding 0.3%. Grade estimation was conducted using Ordinary Krigging within Leapfrog software. The MRE is confined to the Lithium Ionic Bandeira Target Claims (ANM) and includes only fresh rock domains. The MRE was constrained by the Reasonable Prospects for Eventual Economic Extraction (RPEEE) using a grade shell with a cut-off of 0.5% Li₂O for underground resources. Inferred mineral resources are conceptual in nature and can only form the basis for economic analyses with further drilling and evaluation.
Figure 1. Bandeira Project Location
View Figure 1 here: https://www.globenewswire.com/NewsRoom/AttachmentNg/e9ec0883-0725-482d-bab9-3dcf5fb433fc
Figure 2. Isometric View of the Bandeira Deposit
View Figure 2 here: https://www.globenewswire.com/NewsRoom/AttachmentNg/69390a16-e410-4e39-b72f-37068f2fb19b
Details related to the calculation of the MRE
The MRE was prepared by Carlos Silva P.Geo., M.Sc., of GE21 (the 'Author' or 'QP') with an effective date of November 20, 2024.
The MRE was prepared using the following geological and resource block modeling parameters which are based on geological interpretations, geostatistical studies, and best practices in mineral estimation.
The QP is not aware of any factors or issues that materially affect the MRE other than normal risks faced by mining projects in the province in terms of environmental, permitting, taxation, socio-economic, marketing, and political factors, and additional risk factors regarding inferred resources. The Project geology comprises Neoproterozoic age sedimentary rocks of Araçuaí Orogen intruded by fertile Li-bearing pegmatites originated by fractionation of magmatic fluids from the peraluminous S-type post-tectonic granitoids of Araçuaí Orogen. Lithium mineralization is related to concordant and discordant swarms of spodumene-bearing tabular pegmatites hosted by cordierite-biotite-quartz schists.
Drilling conducted by Lithium Ionic included diamond core drilling of NTW (64.2mm diameter).
Diamond core has been sampled in intervals of ~ 1 m where possible, otherwise intervals less than 1 m have been selected based on geological boundaries. Geological boundaries have not been crossed by sample intervals. ½ core samples have been collected and submitted for analysis, with regular field duplicate samples collected and submitted for QA/QC analysis.
Drill core samples were submitted to SGS Geosol laboratories in Brazil where they were analyzed for a 31-element suite via ICP90A (fusion by sodium peroxide and finish with ICP- MS/ICP-OES). Assay data were composited to 1 m.
The MRE was estimated from the diamond drill holes completed by Lithium Ionic from April 2022 until September 2024. Data from a total of 297 drill holes comprising 10,051 assays were included in the mineral resources model.
The 3D modelling of lithium Mineral Resources was conducted using a minimum cut-off grade of 0.3% Li 2 O within a preliminary lithological model.
O within a preliminary lithological model. The interpolation was conducted using Kriging methodology with three interpolation passes.
The block model was defined by a block size of 12 m long by 12m wide by 4 m thick and covers a strike length of approximately 1,200 m to a maximal vertical depth of 500 m below surface.
The MRE was classified as Measured, Indicated and Inferred Mineral Resource based on data quality, sample spacing, and pegmatite continuity. The Measured Mineral Resource was defined using a search ellipsoid of 50 m by 50 m by 30 m, and where the continuity and predictability of the mineralized units was reasonable. The Indicated Mineral Resource was defined using a search ellipsoid 100 m by 100 m by 50 m. The Inferred Mineral Resource was assigned to areas where drill hole spacing was greater than 100 m by 100 m by 50 m for all remaining blocks.
Classification focused on spatial relation using a minimum of five composites in at least three different drill holes for the Measured and Indicated resources. Validation has proven that the block model fairly reflects the underlying data inputs. Variability over distance is relatively moderate to low for this deposit type therefore the maximum classification level is Indicated.
Mineralization at the deposits extends to surface and is expected to be suitable for open cut mining; no minimum mining width was applied; internal mining dilution is limited to internal barren pegmatite and/or host rock intervals within the mineralized pegmatite intervals; based on these assumptions, it is considered that there are no mining factors which are likely to affect the assumption that the deposit has reasonable prospects for eventual economic extraction.
It is the QP's opinion that the current classification used is adequate and reliable for this type of mineralization and MRE.
The MRE reported is a global estimate with reasonable prospects of eventual economic extraction.
Qualified Persons
Carlos José Evangelista Silva, MSc Geo. (MAIG membership number 7868), of GE21 is a Qualified Person as defined by NI 43-101 and has reviewed and approved the technical information and data regarding the MRE included in this news release. Mr. Silva is independent of Lithium Ionic. All other scientific and technical information in this news release has been reviewed and approved by Carlos Costa, Vice President Exploration of Lithium Ionic and Blake Hylands, CEO and director of Lithium Ionic, and both are 'qualified persons' as defined in NI 43-101.
On behalf of the Board of Directors of Lithium Ionic Corp.
Blake Hylands
Chief Executive Officer, Director
About Lithium Ionic Corp.
Lithium Ionic is a Canadian mining company exploring and developing its lithium properties in Brazil. Its flagship Itinga and Salinas projects are located in the northeastern part of Minas Gerais state, a mining-friendly jurisdiction that is quickly emerging as a world-class hard-rock lithium district. The Itinga Project is situated in the same region as CBL's Cachoeira lithium mine, which has produced lithium for +30 years, as well as Sigma Lithium Corp.'s Grota do Cirilo project, which hosts the largest hard-rock lithium deposit in the Americas.
Investor and Media Inquiries:
+1 647.316.2500
[email protected]
Cautionary Note Regarding Forward-Looking Statements
This press release contains statements that constitute 'forward-statements.' Such forward looking statements involve known and unknown risks, uncertainties and other factors that may cause the Company's actual results, performance or achievements, or developments to differ materially from the anticipated results, performance or achievements expressed or implied by such forward-looking statements. Although the Company believes, in light of the experience of its officers and directors, current conditions and expected future developments and other factors that have been considered appropriate that the expectations reflected in this forward-looking information are reasonable, undue reliance should not be placed on them because the Company can give no assurance that they will prove to be correct. When used in this press release, the words 'estimate', 'project', 'belief', 'anticipate', 'intend', 'expect', 'plan', 'predict', 'may' or 'should' and the negative of these words or such variations thereon or comparable terminology are intended to identify forward-looking statements and information. The forward-looking statements and information in this press release include information relating to the prospectivity of the Company's mineral properties including Bandeira, the Company's ability to produce a NI 43-101 compliant mineral resource estimate, PEA and/or Feasibility study and the timing thereof, the Company's ability to obtain the requisite licences and permits, the economic viability of the Bandeira project, the Company's ability to obtain adequate financing, the mineralization and development of the Company's mineral properties, the Company's exploration program and other mining projects and prospects thereof and the Company's future plans. Such statements and information reflect the current view of the Company. Risks and uncertainties that may cause actual results to differ materially from those contemplated in those forward-looking statements and information. By their nature, forward-looking statements involve known and unknown risks, uncertainties and other factors which may cause our actual results, performance or achievements, or other future events, to be materially different from any future results, performance or achievements expressed or implied by such forward-looking statements. The forward-looking information contained in this news release represents the expectations of the Company as of the date of this news release and, accordingly, is subject to change after such date. Readers should not place undue importance on forward-looking information and should not rely upon this information as of any other date. The Company undertakes no obligation to update these forward-looking statements in the event that management's beliefs, estimates or opinions, or other factors, should change.
Information and links in this press release relating to other mineral resource companies are from their sources believed to be reliable, but that have not been independently verified by the Company.
Neither the TSXV nor its Regulation Services Provider (as that term is defined in the policies of the TSXV) accepts responsibility for the adequacy or accuracy of this press release.
Disclaimer: The above press release comes to you under an arrangement with GlobeNewswire. Business Upturn takes no editorial responsibility for the same.
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Additionally, recycled bottle-grade plastics are highly valued for their ability to be converted back into food-grade packaging, textile fibers, and other consumer products. Their consistent supply and compatibility with existing recycling technologies make bottles a reliable and efficient source of post-consumer recycled plastic, reinforcing their dominance in the market. The non-bottle rigid plastics segment is emerging as the fastest‑growing source within the post‑consumer recycled plastics market, driven by several key factors. Non‑bottle rigid items such as containers, packaging trays, crates, lids, pallets, and automotive components are increasingly valuable as recycling feedstock due to their widespread industrial and consumer use. Rising demand for durable, reusable plastics in sectors like foodservice, logistics, automotive, and electronics is prompting greater recycling of these items. Technological advances in sorting and recycling, especially AI-enhanced optical sorters and more efficient mechanical and emerging chemical recycling, are improving the recovery and processing of complex rigid plastics that were previously difficult to recycle. Additionally, polypropylene, commonly used in non‑bottle rigid formats, is seeing fast uptake owing to its versatility and recyclability, further propelling this segment's growth. Environmental pressures and corporate sustainability mandates are pushing manufacturers to incorporate recycled rigid plastics into products and packaging, making this segment increasingly significant in volume and value. The non‑bottle segment is the fastest-growing source segment in the post-consumer recycled plastic market, expanding uptake in applications previously reliant on virgin resin. Type Insights The polythene segment, especially polyethylene (PE) and notably high-density polyethylene (HDPE), dominates the post‑consumer recycled plastic market due to its superior recyclability, widespread application, and reliable feedstock availability. Polyethylene accounts for a substantial share of post-consumer recycled plastics, supported by its extensive use in durable goods, packaging films, and containers. Within PE, HDPE holds the largest market share thanks to its strength, chemical resistance, and high-value applications like bottle-to-bottle recycling and food-grade containers. PE products enjoy high recycling rates globally, facilitated by mature collection systems, deposit-return schemes, and efficient mechanical recycling infrastructure. Moreover, recycled polyethylene is versatile, suitable for packaging, automotive parts, construction materials, and industrial products, making it a preferred recycled polymer for manufacturers. Standards and certifications further ensure quality and traceability, reinforcing its reliability in circular supply chains. The polystyrene segment is emerging as the fastest-growing type segment in the post‑consumer recycled plastics market due to several significant developments. Expanded polystyrene (EPS) is increasingly attractive as a recyclable feedstock thanks to its widespread use in packaging, insulation, electronics, and construction materials, which yields abundant waste for reuse. Recent technological progress, including chemical recycling, thermal densification, and solvent-based depolymerization, has dramatically improved recovery rates and material quality, making recycled EPS viable for high-value applications. Artificial intelligence‑enhanced sorting adds precision, reducing contamination costs and boosting purity levels. Regulatory momentum, such as extended producer responsibility laws and bans on polystyrene disposal, is elevating recycling volumes and corporate interest. Meanwhile, commercial demand is growing for recycled EPS in green construction and cold‑chain packaging, further supporting adoption. Together, these factors position polystyrene especially EPS as the fastest-growing recycled polymer Breakthroughs in the Global Market: In May 2025, Project by Ameripen, financed by the Plastics Industry Association's Recycling, is an actual effort that is carried out with consultation. Circular Matters examined post-consumer recycled content targets. By states, businesses, or trade groups throughout the plastic, paper, and metallic materials. It contrasted these objectives with the material supply that was available and recycling capabilities throughout the U.S. In February 2025, Berry Global Group, Inc. partnered with Mars, a leader in snacks and treats, to switch to 100% recycled plastic packaging for its pantry jars for the M&M'S, SKITTLES, and STARBURST brands, excluding jar lids. This accomplishment promotes Berry and Mars' continued partnership to create packaging with recycled materials and expands on the 2022 introduction of pantry jars made of 15% recycled plastic. Across the nation, the updated jars are currently being distributed. The three sizes of pantry jars, 60, 81, and 87 ounces, are widely recyclable. Top Post-Consumer Recycled Plastic Market Players SABIC BASF SE Sumitomo Chemical Co, Ltd Evonik Industries AG Arkema LyondellBasell Industries N.V Celanese Corporation Chevron Phillips Chemical Company Eastman Chemical Company SUEZ SA Covestro AG Exxon Mobil Corporation Post-Consumer Recycled Plastic Market Segments By Source Bottles Non-Bottle Others By Type Polypropylene (PP) Polystyrene (PS) Polyethylene (PE) Polyvinyl Chloride (PVC) Polyurethane (PU) Polyethylene Terephthalate (PET) Others By Region North America U.S. Canada Europe Germany UK France Italy Spain Sweden Denmark Norway Asia Pacific China Japan India South Korea Thailand Latin America Brazil Mexico Argentina Middle East and Africa (MEA) South Africa UAE Saudi Arabia Kuwait Invest in Premium Global Insights @ If you have any questions, please feel free to contact us at sales@ About Us Towards Packaging is a leading global consulting firm specializing in providing comprehensive and strategic research solutions. With a highly skilled and experienced consultant team, we offer a wide range of services designed to empower businesses with valuable insights and actionable recommendations. We stay abreast of the latest industry trends and emerging markets to provide our clients with an unrivalled understanding of their respective sectors. We adhere to rigorous research methodologies, combining primary and secondary research to ensure accuracy and reliability. Our data-driven approach and advanced analytics enable us to unearth actionable insights and make informed recommendations. We are committed to delivering excellence in all our endeavours. Our dedication to quality and continuous improvement has earned us the trust and loyalty of clients worldwide. 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AI in Oil and Gas Market Size Worth USD 25.24 Bn by 2034 Driven by Predictive Maintenance and Operational Automation
AI in Oil and Gas Market Size Worth USD 25.24 Bn by 2034 Driven by Predictive Maintenance and Operational Automation

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AI in Oil and Gas Market Size Worth USD 25.24 Bn by 2034 Driven by Predictive Maintenance and Operational Automation

According to Precedence Research, the AI in oil and gas market size is expected to be worth USD 25.24 billion by 2034, increasing from USD 7.64 billion in 2025 and is projected to grow at a solid CAGR of 14.2% from 2025 to 2034. Oil and gas firms accelerate their digital transformation, and artificial intelligence (AI) is emerging as a game-changer in the sector. Ottawa, Aug. 04, 2025 (GLOBE NEWSWIRE) -- In terms of revenue, the global artificial intelligence (AI) in oil and gas market was valued at USD 6.69 billion in 2024, grew to USD 7.64 billion in 2025. It is predicted to rise from USD 8.73 billion in 2026 to approximately USD 25.24 billion by 2034. This surge is driven by the need for enhanced safety, predictive maintenance, and cost-efficiency in high-stakes operations. In terms of CAGR, the market of AI in oil and gas is expanding at a double-digit CAGR of 14.2% from 2025 to 2034. The growing demand for enhancing operational efficiency in the sector drives the market growth. Note: This report is readily available for immediate delivery. We can review it with you in a meeting to ensure data reliability and quality for decision-making. Try Before You Buy – Get the Sample Report@ Artificial Intelligence in Oil and Gas Market Overview & Insights: The AI in Oil and Gas Market is rapidly evolving as energy companies seek to enhance operational efficiency, safety, and profitability in a volatile and resource-intensive industry. AI technologies such as machine learning, computer vision, natural language processing, and predictive analytics are being integrated across upstream, midstream, and downstream segments to improve decision-making, reduce human error, and lower costs. In upstream exploration and drilling, AI is enabling faster seismic data interpretation, reservoir modeling, and real-time drilling optimization. In midstream operations, AI supports predictive maintenance of pipelines, logistics optimization, and failure detection in transport systems. In the downstream segment, AI enhances refining processes, automates quality control, and personalizes customer engagement at retail fuel stations. AI is no longer a luxury but a necessity in the oil and gas industry,' said Shivani Zoting, Principal Consultant at Precedence Research. 'With growing pressure to optimize costs and reduce downtime, companies are aggressively adopting AI for predictive maintenance and operational automation. How is AI Being Utilized in Oil & Gas Industry? Artificial intelligence in the oil & gas sector is a process of using AI technologies in the oil & gas sector to enhance sustainability, efficiency, and safety. Artificial intelligence is used in various processes like distribution, exploration, refining, and many more in the oil & gas sector. AI helps in identifying potential oil & gas reserves by analyzing seismic data. AI is widely used in various applications like defect detection, drilling optimization, and supply chain optimization in the oil & gas sector. AI helps in increasing efficiency, enhancing productivity, reducing energy consumption, improving safety, making better decisions, and enhancing sustainability. Artificial Intelligence Use in Oil & Gas Companies Company Name AI Use ExxonMobil Predictive Maintenance Reservoir Management Safety Monitoring Royal Dutch Shell Predictive Maintenance Oil & Gas Exploration Chevron Predictive Maintenance Optimizing Cargo Loads and Routes During Transportation British Petroleum Increase Operational Efficiency Producing Geological Data Saudi Aramco Field Monitoring Flare Monitoring Reservoir Modelling ➤ ️ Case Study: Chevron's Predictive AI Transformation in Oilfield Operations Chevron Corporation, a global energy giant, has long been at the forefront of technological innovation in the oil and gas sector. Faced with challenges including fluctuating oil prices, aging infrastructure, and a mandate for enhanced safety and environmental compliance, Chevron invested heavily in Artificial Intelligence starting in 2021. Their goal: to transform upstream operations through predictive insights, real-time monitoring, and optimization. AI Deployment Strategy Chevron partnered with tech leaders such as Microsoft (Azure AI) and to build an enterprise AI platform capable of ingesting real-time data from thousands of IoT sensors embedded across its wellheads, compressors, pipelines, and rigs. Key AI Technologies Used: Predictive Maintenance via machine learning to detect early signs of equipment wear and tear. Digital Twin Models for simulating oilfield performance. Natural Language Processing (NLP) to extract insights from unstructured technical reports. Deep Learning Algorithms to enhance seismic data interpretation and reservoir modeling. Implementation and Impact Pilot Deployment:In 2022, Chevron deployed AI-driven predictive maintenance at its Permian Basin field—a highly productive but complex oilfield in Texas. Measurable Outcomes: Reduced unplanned equipment downtime by 25% in the first year. Extended equipment life cycles by 18%, saving millions in deferred capex. Achieved 15% improvement in overall production efficiency through real-time optimization. Reduced methane leaks and improved compliance by using AI-powered drone inspections and infrared imaging. Broader Transformation The success in the Permian Basin led to enterprise-wide rollout by 2024: AI is now integrated into cargo route optimization, refining processes, and supply chain demand forecasting. Chevron reports an estimated $900 million in operational savings over 3 years, directly attributed to AI initiatives. 'AI allows us to make better decisions, faster—turning billions of data points into actionable insights that protect people, the planet, and profitability.'— Jay Johnson, EVP, Upstream, Chevron Lessons for the IndustryAI is not a plug-and-play solution; it requires robust data infrastructure, skilled talent, and change management. The highest ROI is seen when AI is aligned with core operational KPIs like uptime, safety, and yield. Partnerships with tech vendors and open data ecosystems accelerate innovation. AI is Reshaping the Future of Oil & Gas—Are You In? Join the wave of innovation transforming the energy industry.➡️ Become a valued research partner with us ➢ Artificial Intelligence in Oil and Gas Market Opportunity: What is the Opportunity for Artificial Intelligence (AI) in Oil and Gas Market? Supply Chain Management Unlocks Opportunity The increasing focus on transforming the supply chain management of the oil & gas sector increases the adoption of AI. It provides insights into logistic planning, demand forecasting, and inventory management that help in optimizing supply chain operations. The focus on better customer satisfaction, improving efficiency, and reducing costs fuels demand for AI. The need for identifying disruption in the supply chain increases the adoption of AI's predictive analysis. It analyses market trends, past data, and weather patterns, and helps in avoiding shortages. It helps in supply chain management from upstream operations to distribution, which supports market growth. The growing need for resource allocation, optimization of transportation routes, and scheduling requires AI. The increasing focus on real-time visibility of supply chains fuels demand for AI. Supply chain management creates an opportunity for the growth of the artificial intelligence oil & gas market. Artificial Intelligence (AI) in Oil and Gas Market Challenges and Limitations: What is the Limitation for Artificial Intelligence (AI) in Oil and Gas Market? High Implementation Cost Limits Adoption of AI in Oil & Gas Market Despite several benefits of AI in the oil & gas sector, the high implementation cost restricts the market growth. Factors like the requirement of data management, acquisition, & integration, need for specialized expertise, cybersecurity challenges, and integration with systems require high implementation cost. The analysis, collection, and storage of data requires a data management & infrastructure system that increases the implementation cost. The need for expertise in software development, data science, and machine learning leads to higher implementation costs. The integration with legacy systems requires modifications and upgrades, which increases the cost. The risk of cybersecurity requires monitoring and robust security measures, leading to higher implementation costs. The need for high costs for system integration, hardware, and software directly affects the market. The high implementation cost hampers the artificial intelligence (AI) in the oil & gas market. AI in Oil and Gas Market Coverage: Report Attributes Key Statistics Market Size in 2024 USD 6.69 Billion Market Size in 2025 USD 7.64 Billion Market Size in 2030 USD 14.84 Billion Market Size in 2032 USD 19.35 Billion Market Size by 2034 USD 25.24 Billion Growth Rate (2025 to 2034) CAGR of 14.2% Leading Region in 2024 North America (captured 39.13% of market share) Base Year 2024 Forecast Period 2025 to 2034 Segments Covered Component, Function, Application and Region Regions Covered North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa Key Players Microsoft Corporation, FuGenX Technologies Pvt. Ltd, IBM Corporation, Google LLC, NVIDIA Corp., Royal Dutch Shell PLC, PJSC Gazprom Neft, Huawei Technologies Co. Ltd, Intel Corporation, Neudax, Infosys Limited, and Others. ➡️Become a valued research partner with us - Artificial Intelligence in Oil and Gas Market Key Regional Analysis: Which Region Dominated the Artificial Intelligence (AI) in Oil & Gas Market? North America dominated the Artificial Intelligence (AI) in Oil & Gas Market in 2024. The well-established infrastructure for the extraction of oil & gas increases demand for AI solutions. The growing private companies and government investment in research & development in the oil & gas sector for the implementation of AI help the market growth. The growing production of oil & gas increases demand for AI solutions. The focus on enhancing operational efficiency and optimizing production and exploration in the oil & gas sector fuels demand for AI, driving the overall growth of the market. U.S. AI in Oil and Gas Market Size and Forecast 2025 to 2034 How Big is the U.S. AI in Oil and Gas Market? According to Precedence Research, the U.S. artificial intelligence (AI) in oil and gas market size was valued at USD 1.84 billion in 2024 and is estimated to grow from USD 2.12 billion in 2025 to USD 7.34 billion by 2034. The market is poised to grow at a CAGR of 14.8% from 2025 to 2034. Why U.S. Stands Out: Dominated by innovation and early AI adoption across upstream, midstream, and downstream operations. Proven applications include predictive maintenance, real-time drilling analytics, reservoir modeling, and operational automation. Leading contributions from tech-forward energy companies such as Chevron, ExxonMobil, SLB, and early rollout of platforms like IBM Watsonx in 2024. Adoption and Industry Impact in the U.S. The oil industry is allocating approximately USD 3.1 billion in AI spending in 2024, representing under 5% of total capital expenditures. AI investment is projected to increase up to 80% within five years. (Source: At CERAWeek 2025, U.S. firms like BP, Devon Energy, and Chevron showcased improved productivity thanks to AI: Devon reported a 25% increase in well lifespan, while Chevron uses AI‑driven drones for maintenance and monitoring. (Source: The Complete Study is Now Available for Immediate Access | Download the Sample Pages of this Report@ Interested in how AI can transform your oil & gas operations? Schedule a personalized briefing or request custom data insights tailored to your business goals. ✚ Contact us at or visit ➤ Why is Asia Pacific Growing in the Artificial Intelligence (AI) in Oil & Gas Market? Asia Pacific is experiencing the fastest growth in the market during the forecast period. The increasing production activities and exploration in the oil & gas industry increase demand for AI solutions. The focus on digital transformation in the oil & gas sector fuels the adoption of AI solutions to improve operational efficiency. The increasing demand for cost savings and productivity gains helps in the market growth. The demand for reducing downtime, potential equipment failures, and proactive maintenance increases the adoption of AI solutions. The increasing optimization of operations like refining, drilling, and production increases demand for AI solutions. The growing adoption of AI across applications like downstream, upstream, and midstream drives the overall growth of the market. Artificial Intelligence (AI) in Oil and Gas Market Segmentation Analysis Component Analysis: Why did Software Dominate the Artificial Intelligence (AI) in Oil & Gas Market? The software segment dominated the Artificial Intelligence (AI) in oil & gas market in 2024. The presence of large amounts of data through diverse sources like seismic surveys, sensors, and drilling operations increases demand for software to identify correlations, patterns, and anomalies. The need for automating repetitive tasks like equipment monitoring, data entry, and report generation in the oil & gas sector increases demand for AI software. The focus on extending critical equipment lifespans, preventing unexpected downtime, and reducing maintenance costs requires AI software. The growing demand for software for applications like ensuring compliance, monitoring worker safety, and detecting potential hazards drives the market growth. Function Analysis: How Predictive Maintenance Segment Held the Largest Share in the Artificial Intelligence (AI) in Oil & Gas Market? The predictive maintenance segment held the largest revenue share in the Artificial Intelligence (AI) in oil & gas market in 2024. The focus on minimizing unplanned downtime in the oil & gas sector increases demand for predictive maintenance. The increasing demand for extending the lifespan of equipment and identifying issues of equipment early increases the adoption of predictive maintenance. The focus on minimizing disruptions during planned downtime requires predictive maintenance. The increasing demand for predictive maintenance for optimizing maintenance schedules and enhancing operational efficiency in the oil & gas sector supports the overall growth of the market. Application Analysis: How Application Segment Dominates Artificial Intelligence (AI) in Oil & Gas Market? The upstream segment dominated the Artificial Intelligence (AI) in oil & gas market in 2024. The growing demand for predictive equipment failures, improving operational efficiency, optimizing drilling, and reducing downtime in upstream applications increases demand for AI. The growing focus on extracting and finding oil & gas fuels adoption of AI. The growing utilization of AI functionalities like predictive maintenance in the upstream applications supports the market growth. Related Topics You May Find Useful: ➡️ Oil and Gas Analytics Market: Uncover how data-driven insights are optimizing operations and reducing costs ➡️ AI in Energy Market: Explore how artificial intelligence is transforming grid efficiency and demand forecasting ➡️ Oil and Gas Security Market: See how digital threats are reshaping risk management in critical energy infrastructure ➡️ Oil and Gas Carbon Capture and Storage Market: Track how decarbonization mandates are driving CCS technology investments ➡️ Digital Oilfield Market: Analyze how automation and IoT are redefining exploration and production workflows ➡️ Geospatial Analytics & AI Market: Discover how satellite data and AI are enhancing environmental and asset intelligence ➡️ Industry 4.0 Market: Understand how smart manufacturing is accelerating digital transformation across sectors ➡️ AI in Renewable Energy Market: Gain insight into how AI is powering forecasting, grid stability, and green energy adoption Artificial Intelligence (AI) in Oil and Gas Market Top Companies Microsoft Corporation FuGenX Technologies Pvt. Ltd IBM Corporation Google LLC NVIDIA Corp. Royal Dutch Shell PLC PJSC Gazprom Neft Huawei Technologies Co. Ltd Intel Corporation Neudax Infosys Limited Recent Developments In September 2024, Huawei launched an AI application for oil & gas upstream. Innovation aims to increase production & reserves, achieve high-quality development, enhance industrial quality with intelligence, and ensure safe operations. The focus is on enhancing security, reducing cost, and boosting operational efficiency. (Source: In September 2024, APA Corporation collaborated with Palantir to use AI technology for oil & gas operations. The Palantir focuses on the development of software for supply chain management, production optimization, operational planning, maintenance planning, and contract management. The company's AI solution helps in optimizing raw material logistics, improving equipment reliability, and AIP in invoice & contract documents. (Source: In July 2024, Indosat launched AI solutions for the upstream oil & gas industry. The solution is cloud-based and helps in predictive maintenance for equipment and condition-based monitoring. The solution is used to improve collaborations among workers and monitor workplace safety. (Source: Artificial Intelligence (AI) in Oil and Gas Market Segments Covered in the Report By Component Software Hardware Services By Function Predictive Maintenance Machinery Inspection Material Movement Production Planning Field Services Quality Control Reclamation By Application Upstream Midstream Downstream By Region North America U.S. Canada Europe Germany UK France Italy Spain Sweden Denmark Norway Asia Pacific China Japan India South Korea Thailand Latin America Brazil Mexico Argentina Middle East & Africa South Africa UAE Saudi Arabia Kuwait Thank you for reading. You can also get individual chapter-wise sections or region-wise report versions, such as Immediate Delivery Available | Buy This Premium Research Report@ You can place an order or ask any questions, please feel free to contact at sales@ | +1 804 441 9344 Stay Ahead with Precedence Research Subscriptions Unlock exclusive access to powerful market intelligence, real-time data, and forward-looking insights, tailored to your business. From trend tracking to competitive analysis, our subscription plans keep you informed, agile, and ahead of the curve. Browse Our Subscription Plans@ About Us Precedence Research is a worldwide market research and consulting organization. We give an unmatched nature of offering to our customers present all around the globe across industry verticals. Precedence Research has expertise in giving deep-dive market insight along with market intelligence to our customers spread crosswise over various undertakings. 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