Assess and Prioritize Agentic AI Use Cases in Oil and Gas

Agentic AI has the potential to yield cost and efficiency improvements in the oil and gas industry but is difficult to implement amid structural boundaries. As AI use cases get closer to operational environments, risk tolerance decreases and the value and viability must increase to counterbalance. Determining the optimal level of agentic AI autonomy, based on your organization’s needs and maturity, further complicates the decision process.

Our Advice

Critical Insight

Oil and gas organizations should prioritize agentic AI to strengthen production, operational efficiency, and commercial performance while establishing boundaries to maintain auditability and alignment with safety, OT, and regulatory constraints.

Impact and Result

A clear, defensible shortlist of agentic AI use cases aligned to strategic business goals.
Time savings through the evaluation process and a seamless input into AI strategy and piloting initiatives that follow.
Established autonomy ceilings and agentic role fit for each capability domain, identifying where regulatory operational constraints limit defensible autonomous decision-making and what activities are most readily supported by AI.
Evaluated use cases using a structured value-vs.-viability framework, allowing organizations to prioritize initiatives where agent behavior is both operationally useful and risk-appropriate.

Assess and Prioritize Agentic AI Use Cases in Oil and Gas Research & Tools

1. Assess and Prioritize Agentic AI Use Cases in Oil and Gas Storyboard – This storyboard helps oil and gas leaders align their agentic AI needs to their business drivers and evaluate the most suitable and valuable use cases to champion for implementation.

This research outlines the fundamental concepts of agentic AI, how it can be used in alignment with the organizational priorities of the oil and gas space, and how to assess individual use case for suitability and value to your organization. By using it organizations can expect to effectively shortlist options based on their priorities and realities and be prepared to pilot and implement specific initiatives and a broader AI strategy with confidence.

2. Agentic AI Use Case Tool for Oil and Gas – This deliverable provides an example-filled and structured template for categorizing and scoring agentic AI use cases specific to Oil and Gas.

This tool allows users to select criteria for value and feasibility that suits their organization’s goals and maturity, and to use them to score agentic AI use cases for fast and effective prioritization. It contains examples that span each of the Oil and Gas domains and fields to allow for the effective categorization of each use case based on domain, autonomy level, and place within business operations.

3. Agentic AI Capability Map Templates for Oil and Gas – This deliverable supports the organization of Oil and Gas capabilities as organizations assess drivers of business goals and risk tolerance for agentic AI usage by domain.

Aligning agentic AI use cases with capabilities that drive business KPIs and outcomes maximizes the benefits they can yield. This supporting document allows for organizations to outline where these opportunities exist in their business operations. It allows capabilities with low-risk tolerance to be highlighted and inform the autonomy levels of explored use cases.

Align autonomy with value, risk tolerance, and viable domain to maximize impact.

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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.

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Speak With An Analyst

Get the help you need in this 4-phase advisory process. You'll receive 7 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Pre-Work

Call 1: Scope requirements, objectives, and your specific challenges.

Guided Implementation 2: Identify Use Cases That Align to Your Drivers and Capabilities

Call 1: Anchor AI capability to business context and drivers.
Call 2: Explore agentic AI in practice.

Guided Implementation 3: Characterize AI by Purpose and Scale

Call 1: Establish agentic AI capability patterns.
Call 2: Optimize the balance of autonomy and risk within use cases.

Guided Implementation 4: Score and Validate Prioritized Use Cases

Call 1: Score use cases for prioritization.
Call 2: Review and validate use case portfolio.

Author

Evan Garland