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1、Oil and gas in the AI eraDrilling deep for business opportunitiesIBM Institute for Business Value|Research BriefForewordThe oil and gas industry stands at the intersection of two transformative forces:opportunities coming from the rapid evolution of AI and the global shift toward more sustainable,se

2、cure,and affordable energy sources.These dynamics are inextricably linked,and success will belong to organizations that harness the synergy between them.This synergy will accelerate operational efficiencies and business model innovation for growth and build more agile capabilities in response to evo

3、lving markets.In a new IBM Institute for Business Value(IBM IBV)survey,we see that industry leaders understand these dynamics and place AI at the heart of their strategy.59%expect AI to contribute significantly to their revenue within three years.75%say that AI investments will deliver a measurable

4、competitive advantage in this same timeframe.For an industry defined by market volatility,leveraging AI marks a fundamental shift in how oil and gas companies can gain an edgebut it requires a balance between investments in productivity and innovation.Today,many organizations target operational effi

5、ciency.Current AI spend in this area outpaces spend on innovation by three to one.64%of executives say they are significantly revamping workflows to enhance process efficiencies and reduce manual effort.Initiatives include automating seismic data interpretation in upstream operations,using AI for re

6、al-time drilling optimization,enhancing predictive maintenance in midstream pipeline networks,and optimizing refinery yields in downstream operations.Streamlining processes is essential,but building a competitive edge lies in AI-powered business model disruption.Many companies are positioning themse

7、lves to capitalize on these opportunities.67%of executives say they are actively rearchitecting how they work to capture the full potential of AI,and 58%report AI can create significant value through new revenue streamssuch as data-driven services,digital operations platforms,and AI-powered trading

8、tools.These views pave the way for the industry to not only optimize operations but also reimagine itself for the future.This report looks ahead at AIs role in shaping the oil and gas industry,including concrete actions you can take now to help your organization compete.We explore where AI already d

9、elivers business outcomes and where opportunity lies across upstream,midstream,and downstream operations.Realizing AIs full value requires an intentional,enterprise-wide strategy,focused on execution and partnerships built for transformationwhether the goal is to optimize workflows,drive service inn

10、ovation,or reengineer entire business models.At IBM,were proud to be a trusted partner to many of the worlds leading oil and gas companies as they embrace AI to fuel growth,improve profitability,and navigate a changing energy landscape.With extensive AI expertise,deep industry insight,and robust con

11、sulting capabilities,we help organizations accelerate AI journeys and mine value from uncharted territories.Zahid Habib Vice President,Global Industrial Sector Leader,Global Energy and Resources Industry Leader IBM Consulting2Oil and gas in the AI era3Oil and gas in the AI eraKey takeawaysAI is an e

12、merging catalyst across the oil and gas value chainAI adoption is accelerating across upstream,midstream,and downstream activities.Currently,44%of upstream organizations use AI in exploration.Another 45%plan to do so within three years.In downstream operations,41%apply AI in refining;another 52%expe

13、ct to do so in three years.AI is already delivering concrete results Oil and gas executives report a 27%improvement in production uptimefor example,through AI-based predictive equipment maintenanceand a 26%improvement in asset utilization optimization by better matching asset deployment with demand.

14、AI is redefining the future of energy From optimizing renewable energy generation to managing distributed energy resources and market integration,AI enables the agility and intelligence needed to lead in new energy business models.56%of oil and gas executives say AI will enable new technology capabi

15、lities that fundamentally transform their business model.4UpstreamExplorationDrillingProduction44%40%28%85%90%89%TransportationStorageProcessing28%30%28%85%85%77%MidstreamRefiningRetail and marketing41%93%31%66%DownstreamOil and gas in the AI eraAs oil and gas companies optimize current operations a

16、nd transition toward a low-carbon future,AI is emerging as a catalyst across the value chain.From identifying untapped reserves,to preventing equipment failure through predictive maintenance,to boosting production process efficiencies,AI drives unprecedented outcomes and smarter,more agile operation

17、s.AI adoption is growing rapidly across upstream,midstream,and downstream activities.Currently,44%of upstream organizations use AI in exploration.Another 45%plan to do so within three years.In downstream operations,41%apply AI in refining;another 52%expect to do so in three years(see Figure 1).Enabl

18、ing a more profitable low-carbon futureFigure 1Implementation of AI across the oil and gas value chainTodayTotal in 3 years44%40%28%85%90%89%TransportationStorageProcessing28%30%28%85%85%77%MidstreamDownstreamRefiningRetail and marketing41%93%31%65%5improvement in production uptime27%improvement in

19、asset utilization optimization26%increase in throughput15%Oil and gas in the AI eraAgentic AI represents the next frontier in industrial automation as organizations pilot this technology across key oil and gas functions.Autonomous agents can take real-time actions based on environmental feedback and

20、 transform how decisions are made and executed.In upstream operations,29%of organizations are at least piloting agentic AI for drilling and production optimization,such as dynamically adjusting mud weight to prevent blowouts.In the midstream segment,23%are at least testing AI agents in pipeline moni

21、toring,leveraging sensor data and satellite imagery to proactively detect and resolve anomalies before they lead to critical failures.AI is already delivering concrete results across the oil and gas value chain(see Figure 2).Industry executives report a 27%improvement in production uptime,such as th

22、rough AI-based predictive equipment maintenance,and a 26%improvement in asset utilization optimization by better matching asset deployment with demand.29%of oil and gas companies are piloting agentic AI to optimize drilling and production in upstream operations.improvement in production uptimeFigure

23、 2Benefits of using AI in the oil and gas industryProduction and output27%improvement in asset utilization optimization26%increase in throughput15%6Oil and gas in the AI eraFigure 3Benefits of using AI in the oil and gas industryOperational performanceincrease in employee productivity18%decrease in

24、operational cost18%decline in capital expenditure15%These operational improvements translate into meaningful financial impact.Decreased downtime,automated inspections,and more efficient supply chains are reducing operational costs as much as 18%and improving other key operational performance metrics

25、(see Figure 3).And executives attribute around 5%of current revenue to AI-driven initiatives,with projections rising to more than 7%in the next three years.For a$20B oil and gas operator,thats roughly$1B todaygrowing to$1.4B as AI scalesrepresenting a$400M+business opportunity.AI is also reshaping t

26、he role of oil and gas companies in a decarbonized energy landscape.From optimizing renewable energy generation to managing distributed energy resources and market integration,AI enables the agility and intelligence needed to lead in new energy business models.More than half(56%)of executives say AI

27、 will enable new technology capabilities that fundamentally transform their business model,and 70%agree it will improve their ability to navigate market disruptions,such as demand shifts,geopolitical instability,and the emergence of green hydrogen and other lower carbon alternative fuels and product

28、s.For example,AI models can track shipping data,satellite imagery,and global market indicators to forecast short-term supply-and-demand trends and optimize cargo routing or hedging strategies.AI could also help analyze long-term risk-adjusted returns on hydrogen and biofuels versus traditional asset

29、s to enable smarter capital deployment in new energy assets.7Oil and gas in the AI eraIndeed,AI also enables core business decarbonization.13%deploy agentic AI for carbon capture optimization,including pressure and flow control to enhance CO2 injection efficiency in carbon capture,utilization,and st

30、orage(CCUS)projects.14%use it for environmental and emissions monitoring,leveraging satellite imagery,IoT sensors,and computer vision for fugitive methane detection and real-time flare monitoring.These executives also report a 29%drop in operational incidents,especially through anomaly detection and

31、 safety compliance monitoring,and a 22%gain in energy efficiencyoften through AI-optimized control systems in processing and compression facilities(see Figure 4).These innovations create new service opportunities.Within three years,72%of organizations anticipate offering AI-powered carbon capture op

32、timization as a service,especially in regions where regulatory carbon pricing is emerging.This service could target major emitters such as steel and cement companies or independent CCUS operators that own or operate capture and sequestration infrastructure but lack in-house AI expertise.And 78%expec

33、t to provide environmental monitoring as a service,creating new revenue streams while advancing ESG performance.This service could be offered to industrial companies,mining firms,and infrastructure owners with environmental liabilities.Figure 4Benefits of using AI in the oil and gas industrySafety a

34、nd sustainabilitydecrease in operational incidents29%improvement in energy efficiency22%reduction in carbon emissions15%decrease in operational incidents29%improvement in energy efficiency22%reduction in carbon emissions15%8Case studyWintershall Dea thinks big and small with AIScale1“You must have a

35、 business problem.And you need to understand the challenges in your area and make sure you have access to high-quality,relevant data and then prepare the data so you can actually do something with it.”Ulrich Lorang Vice President of Data Science,Data Governance,and Data Hub,Wintershall DeaOil and ga

36、s in the AI eraA leading European oil and gas company,Wintershall Dea is positioning itself as an industry leader by leveraging AI for operational improvements and innovation.It has trained more than 100 employees in AI and data science and established a Center of Competence(CoC)through an initiativ

37、e called AIScale.The company has prioritized two types of AI projects:smaller“fireflies”quick,scalable solutions to simple problems such as automating data extraction from PDF documentsand large-scale projects,including an AI application to monitor well integrity for better leak detection.So far,Win

38、tershall Dea has identified more than 80 AI use cases and is actively pursuing 20 more.The well integrity project is already in production.9Oil and gas in the AI eraRealizing AIs transformative potential in the oil and gas industry requires creating the right conditions for success.Industry executiv

39、es cite critical barriers,including a shortage of AI skills,the integration of complex data for AI training,and inappropriate legacy IT infrastructures.Addressing these challenges will require a broader transformation effort,starting with the following actions:Action guideHarness existing capabiliti

40、es,break down silos,and build enterprise capability.Conduct a focused audit of current digital and AI-related roles across operations.Identify AI skill gaps in areas such as data science,machine learning ops,and digital twin modeling.Prioritize hiring high-impact roles such as AI and machine learnin

41、g engineers,data scientists with time-series modeling experience,and digital twin engineers.Partner with specialized recruiters or academic institutions to access talent.Set up an AI bootcamp for existing technical teams focused on practical,oil-and-gas-specific use cases such as predictive maintena

42、nce or reservoir modeling.Enable the whole enterprise with role-appropriate training,all the way up to coaching executives.Equip board members and senior leaders to act as visible champions for AI adoption.Target sessions to help executives articulate AIs strategic value and bust common myths,such a

43、s“AI will replace jobs entirely.”Govern investment and drive value realization.Create a joint governance body that includes stakeholders from business operations,finance,and IT/OT to define and prioritize AI initiatives based on business impact.Build robust business cases for AI projects with financ

44、ial metrics such as cost savings,productivity gains,or safety improvements.Track and quantify value realization.Reinvest gains strategically by allocating savings from efficiency improvements or cost reductions to scale successful pilots or fund more advanced AI capabilities.Establish an investment

45、flywheel:successful AI deployments lead to measurable returns,which fund further AI innovationaccelerating your digital transformation without constantly seeking new capital.10Oil and gas in the AI eraNurture AI pilots where the potential for value is high and maintain a pipeline of initiatives.Sele

46、ct one to two pilot projects for AI deployment based on ROI and feasibilityoptions could be predictive equipment failure in drilling rigs or AI-driven reservoir simulations.Develop a digital twin of one asset,such as a pump station or compressor unit,using real-time sensor data.Bring together subsur

47、face engineers,data scientists,and IT to scope and design AI-driven simulations and digital twins.Measure the reduction in unplanned downtime or efficiency gains,such as percent increase in uptime or production optimization.Uncover innovative,AI-driven revenue streams.Run a design sprint with busine

48、ss unit leaders and data teams to explore AI-based monetization opportunities,such as dynamic pricing,emissions trading,or carbon capture optimization.For midstream or downstream players,consider offering digital asset monitoring,AI-based predictive analytics,or emissions tracking services to third-

49、party operators.For upstream players,assess the potential to monetize subsurface and performance data sets,possibly through secure data exchanges or industry consortia,and agentic AI approaches versus workflow-driven automation,depending on use case maturity and operational criticality.Unleash your

50、datas value for AI with a targeted technology modernization program.Establish an AI readiness task force to tackle integration of legacy systems and define a roadmap to modernize data and infrastructure.This roadmap will help you build mature data management processes as you tackle use cases that re

51、ly on this information.Perform a maturity assessment of data platforms across business units and facilities.Identify integration issues,such as siloed SCADA systems or lack of real-time data flow.Make data quality a strategic priority.Assess and address key dimensionsaccuracy,currency,consistency,an

52、d completenessacross critical data sources.Target one to two key legacy systems for API and interface modernization,such as incorporating legacy refinery control systems into modern APIs to enable AI-based performance monitoring.Implement a data lake or warehouse optimized for AI training and real-t

53、ime analytics.Define metadata standards,ownership models,and access policies.Zahid HabibVice President,Global Industrial Sector Leader,Global Energy and Resources Industry LeaderIBM ConsultingDriving industry solutions and go-to-market strategies at scale,Zahid has over 35 years of experience in man

54、agement consulting,capital projects,business transformation,AI and IoT solutions,trading systems implementation,mergers and acquisitions,and enterprise application SpringSenior Partner,EMEA Energy and Resources Industry LeaderIBM ConsultingWith over 30 years of experience across the value chain,Phil

55、 has particular focus on clean energy.He and his teams provide technology and consulting services to help major energy,chemical,resources,and power and utilities companies navigate transformation and explore and embrace change with new,technology-enabled business Deborah WalkerSenior Partner,Austral

56、ia Distribution and Industrial Sector Leader,Business Transformation ServicesIBM ConsultingDeborah leads the Australia Distribution and Industrial Sector,with a particular focus on natural resources.She works at the intersection of business strategy,technology,and innovation,designing and leading su

57、ccessful transformation programs that address immediate business needs while enabling fundamental and sustainable ShimadaSenior Partner,Japan Industrial Products Industry LeaderIBM ConsultingYoshihiro leads the Japan Industrial Products Industry sector,including Chemicals and Petroleum,Manufacturing

58、,and Aerospace and Defense.For more than 20 years,he has been consistently committed to digital transformation and business contribution through the integration and operation of large-scale mission-critical core systems with business process re- Satoshi NagataAssociate Partner,Global Industrial Cent

59、er of Excellence Industry Diamond,Industrial ManufacturingIBM ConsultingFor over 25 years,Satoshi has driven digital transformation at manufacturing sites including the petroleum and chemical sectors.He has led numerous projects leveraging AI and IoT analytics to enhance factory productivity and sup

60、port technology transfer.He also promotes sustainability and digital transformation in Japan and Muhammad Ali RaziAssociate Partner,Middle East and Africa,Chemicals and Petroleum Industry and IBM Aramco Innovation Hub LeaderIBM ConsultingSyed leads engagements focused on strategic partnerships,merge

61、rs and acquisitions,digital transformations,SAP transformation,and long-term application management and modernization services.As a trusted business advisor,he partners as a thought leader on modern industrial platforms including AI,sustainability,cybersecurity,IoT for industry,and digital Shannon W

62、ilsonCanada Sector Leader,Communications,Industrial,and DistributionIBM ConsultingShannon is a dynamic energy industry leader who drives transformative change and delivers exceptional value to clients.She has successfully steered numerous projects toward groundbreaking solutions and positioned clien

63、ts as industry frontrunners.Her approach is grounded in deep understanding of client needs and leveraging cutting-edge technologies to address them Spencer LinGlobal Research Leader,Chemicals,Petroleum,and Industrial ProductsIBM Institute for Business ValueSpencer is responsible for market insights,

64、thought leadership development,competitive intelligence,and primary research on industry agendas and trends.He has more than 30 years of experience in financial management and strategy Authors11Oil and gas in the AI eraResearch methodologyIBM IBV,in partnership with Oxford Economics,surveyed 105 exe

65、cutives from the oil and gas industry in the US,UK,Germany,and Australia to understand their current use and expectations about AI and innovation in their industry.Participants were asked a range of questions in various formats(multiple choice,numerical,and Likert scale).They were asked about their

66、organizations expectations,results,concerns,and barriers for the industrys movement toward using AI,and the key opportunities for the industry.Respondents were equally distributed across the following roles:CEO,CIO,CTO,COO,and CFO.The survey was conducted in March and April 2025.In addition,the insi

67、ghts and recommendations in this paper draw on case studies and direct extensive work with clients in the oil and gas industry.12Oil and gas in the AI era13Oil and gas in the AI eraNotes and sources1.“Drilling down into data to transform the oil and gas industry.”IBM case study.Accessed April 29,202

68、5.https:/ IBM can helpIBM works with energy and resources companiesincluding power and utilities,oil and gas,and natural resources industriesto responsibly scale AI and build a clean energy transition.Learn how our energy solutions can help your company create a data-driven strategy that streamlines

69、 digital transition and prepares your company for a sustainable future.For more information,please visit: and gas in the AI eraSubscribe to our IdeaWatch newsletterJust the insights.At your fingertips.Delivered monthly.Brought to you by the IBM Institute for Business Value,ranked#1 in thought leader

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