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Identify Use Cases to Inform AI Strategy for Oil and Gas

Choose relevant and feasible initiatives to maximize business impact.

Leaders must:

  • Build an AI strategy that aligns with oil and gas business drivers is time-consuming and complex.
  • Balance speed to adoption with a low tolerance for operational disruption and downtime.
  • Select AI initiatives that deliver measurable impact while remaining feasible within legacy IT-OT environments is difficult.
  • Demonstrate ROI is challenging amid volatile market conditions and capital-intensive operations.

Our Advice

Critical Insight

  • AI initiatives must be value-led, not technology-led, to succeed in oil and gas environments.
  • Use cases that align to priority business capabilities and market conditions are more likely to achieve adoption and ROI.
  • A structured, feasibility-aware prioritization approach helps organizations avoid stalled pilots and wasted investment.

Impact and Result

  • Create a clear, defensible shortlist of AI use cases aligned to strategic business goals.
  • Improve executive confidence and buy-in through transparent prioritization and value framing.
  • Build faster progression from ideation to execution by focusing on initiatives with the highest impact-to-feasibility ratio.

Identify Use Cases to Inform AI Strategy for Oil and Gas Research & Tools

1. Identify Use Cases to Inform AI Strategy for Oil and Gas Deck – This storyboard helps oil and gas leaders identify, assess, and prioritize AI use cases that align with business drivers, operational realities, and market conditions.

This storyboard guides organizations through a structured approach to building a value-driven AI use case roadmap tailored to the oil and gas industry. It includes industry-specific challenges, feasibility considerations, capability-aligned use cases, and prioritization frameworks that help leaders confidently select initiatives that balance impact, risk, and operational stability.

2. AI Use Case Library for the Oil and Gas Sector – This deliverable helps organizations explore, sort, and evaluate a curated library of oil and gas–specific AI use cases to inform AI strategy and roadmap decisions.

The Oil and Gas AI Use Case Library provides a structured inventory of existing AI, ML, and generative AI use cases mapped to industry capabilities and value drivers. It allows teams to filter, compare, and document candidate initiatives based on business impact, feasibility, and strategic fit, serving as a practical foundation for prioritization and roadmap development.

Choose relevant and feasible initiatives to maximize business impact.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

Need Extra Help?
Speak With An Analyst

Get the help you need in this 2-phase advisory process. You'll receive 6 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Identify Candidate Use Cases and Impact
  • Call 1: Scope requirements, objectives, and your specific challenges.
  • Call 2: Identify business-aligned AI goals.
  • Call 3: Identify candidate AI use cases.

Guided Implementation 2: Prioritize Use Cases by Impact and Feasibility
  • Call 1: Assess the organization’s current-state capabilities for managing AI and your strategic investment path.
  • Call 2: Prioritize the business AI initiatives.
  • Call 3: Assess the value and feasibility of the business AI initiatives.

Author

Evan Garland

Contributors

  • 1 anonymous contributor, Director of Sales, Oil Field Production Software
  • Scott Holland, Managing Partner, Info-Tech Research Group
  • George Goodall, Executive Counselor, Info-Tech Research Group
  • Chris Key, Executive Counselor, Info-Tech Research Group
  • Becky Lynn, Executive Counselor, Info-Tech Research Group
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