Your industry runs on complex knowledge. Give AI clear boundaries around what it may know, which models it may use, and what actions need human review.
AI governanceContext governanceExecution governance
Industry illustration · Governance for enterprise knowledge and advisory workflows
Across the energy value chain
Upstream
Midstream
Downstream
Oilfield services
Energy trading
01 / The challenge
Complex knowledge. Clear accountability.
Establish boundaries for sensitive operational context and enterprise knowledge before extending AI adoption.
01
Engineering knowledge silos
Documents and expertise span teams, assets, and organizations. AI needs explicit source ownership and access scope.
02
Sensitive operational context
Commercial, engineering, and operational information require deliberate handling and retention expectations.
03
Complex authorization
Employees, contractors, and partners need access appropriate to their roles and responsibilities.
04
Provider sprawl & execution risk
Model choices and agent tools need approved boundaries, review paths, and accountable owners.
02 / Potential applications
Useful AI. Governed workflows.
These are engagement scenarios to assess together, rather than claims of packaged industry features or existing customer deployments.
Engineering
01
Engineering document assistants
Explore assistance grounded in approved engineering documents, with source attribution and expert review.
Approved sources · Expert review
Enterprise knowledge
02
Governed enterprise RAG
Retrieval-augmented generation (RAG) brings enterprise knowledge into AI responses. Define retrieval scope, permissions, and provenance first.
Retrieval scope · Provenance
Operations
03
Maintenance knowledge search
Help teams find approved procedures and historical knowledge for human-led maintenance planning.
Approved procedures · Human planning
Commercial
04
Procurement & contract analysis
Review commercial documents within confidentiality boundaries, with accountable approval of recommendations.
Confidentiality · Accountable approval
Trading
05
Energy trading decision support
Explore research and analysis with controlled information access and human validation of trading decisions.
Controlled access · Human validation
Business workflows
06
Back-office agent orchestration
Set tool permissions, approval gates, and review expectations for administrative workflows.
Tool permissions · Approval gates
03 / Governance model
Policy follows the context and the action.
Define identity and policy, source permissions, approved model access, tool execution boundaries, human approvals, and tracing and audit requirements for each workflow.
Conceptual governance architecture
Enterprise
People & applications
Identity, roles, and business purpose
InfoDump / Governance layer
01
AI Governance
What AI may be used
02
Context Governance
What AI may know
03
Harness Governance
What AI may do
Approved destinations
Models, agents & systems
Access and actions within agreed boundaries
Across every layer
Human approvals
Tracing
Evaluation
Audit
Deployment boundaries
A design framework for discussing requirements. This diagram does not represent a live system or a guarantee of feature availability.
04 / IT and OT boundaries
Advisory intelligence. Human operational authority.
Enterprise IT / Advisory workflows
Support the people making decisions.
Research, document retrieval, planning, and analysis can support qualified teams within approved knowledge and permission boundaries.
Operational technology / Safety-critical systems
Preserve operational authority.
These scenarios do not imply autonomous operation of industrial equipment or direct control of safety-critical systems. Operational decisions remain subject to qualified human review and established safety processes.
Start a conversation
Bring governance to your energy AI strategy.
For enterprise architects, platform and security leaders, and energy operations stakeholders: discuss the boundaries your AI needs before expanding adoption.
