Energy & Utilities

Shadow AI in Energy: Critical Infrastructure at Risk

Control room operators paste SCADA alarms into AI tools. Engineers share grid configurations with AI assistants. Energy traders upload market positions to AI analysers. Your EMS and ADMS log none of it. A DNS log audit does.

Why Energy Shadow AI Threatens Grid Security

Energy companies operate critical national infrastructure. Network configs, SCADA data, generation capacity and market positions are all high-value targets. Every unsanctioned AI tool creates NERC CIP violations and national security exposure.

Control Systems

Operators paste SCADA alarms, DCS parameters and control logic into AI for troubleshooting. Real-time process data and control configurations reach external AI platforms outside your CIP boundary.

Grid Engineering

Engineers share relay settings, substation configurations and transmission topology with AI tools. Critical infrastructure architecture becomes accessible to commercial AI providers.

Energy Trading

Traders paste market positions, hedging strategies and price forecasts into AI analysis tools. Proprietary trading algorithms and position data leak through AI chat sessions.

Field Operations

Maintenance crews use AI to interpret work orders, draft safety procedures and access equipment manuals. Asset condition data and maintenance schedules reach unvetted AI vendors.

Environmental Compliance

Environmental teams use AI to draft emissions reports, model dispersion patterns and prepare EPA filings. Emissions data, permit details and compliance gaps reach external servers.

Customer Data

Utility customer service teams paste account data, usage patterns and billing details into AI assistants. Smart-meter data and customer PII flow to unvetted AI vendors.

Regulatory and Compliance Mapping

RequirementSourceShadow AI RiskWhat the Audit Produces
CIP-004 PersonnelNERC CIPStaff using AI to access/process BES dataAI tools in CIP-scoped network segments
CIP-011 InformationNERC CIPBES Cyber System Information in AI toolsAI services handling BES-related data flagged
TSA Pipeline SecurityTSA directivesPipeline SCADA data in unvetted AI servicesAI tool inventory for pipeline security assessment
FERC Market RulesFERC / ISO tariffsMarket-sensitive data in AI toolsAI tools used by trading desks identified
Environmental DataEPA / Clean Air ActEmissions and compliance data in AI toolsAI tools handling environmental data listed
Customer DataState PUC regulationsSmart-meter and usage data in AIAI services handling customer data identified

What Your Energy Audit Report Shows

Sample excerpt from a shadow AI audit of a regional electric utility (3,500 employees, 1.2M customers).

SHADOW AI AUDIT - ELECTRIC UTILITY
Scan Period14 days (DNS + proxy)
Total AI Tools Found28 unique AI services
Tools with IT Approval3 of 28
Tools Training on Input11 of 28
TOP FINDINGS
ChatGPT (Free Tier)1,876 queries - engineering and trading
AI Code Assistant634 sessions - SCADA/OT integration team
AI Data Analysis312 uploads - load forecasting data
AI Document Tool287 sessions - compliance reporting
RISK BY DEPARTMENT
Grid Operations / Control Room
Energy Trading
Engineering / IT
Customer Service / Admin
Operational map

Where shadow AI appears in energy and utilities work

AI adoption rarely begins as a formal platform project. It begins when a person finds a faster way to finish a familiar task. For grid operators, engineers, field crews, traders, environmental teams and contractors, that convenience can put network diagrams, operational data, asset conditions, market positions and critical-infrastructure information into services the organization has not assessed.

Grid and plant engineering

Engineers ask assistants about protection settings, diagrams and operating procedures that reveal critical asset details.

Field maintenance

Crews upload equipment photographs and error codes from mobile devices, often outside the managed engineering workflow.

Energy trading

Analysts use AI on forecasts and positions, risking disclosure of market strategy or material operational facts.

Outage response

Teams summarize incident channels and draft updates while an event is active, when details are especially sensitive.

Environmental compliance

Staff process sampling data, permit language and draft reports whose accuracy and lineage must be defensible.

Contractor access

Engineering and maintenance partners bring their own tools, making segment and identity attribution essential.

Read the signal carefully. A domain match proves that an identity or network resolved an AI service during the audit window. It does not reveal a prompt or prove that regulated data was uploaded. Use the result to focus interviews, vendor review and technical investigation where they are most likely to matter.
Decision framework

Turn an inventory into defensible decisions

A useful program does more than count domains. It connects observed use to data, purpose, identity and vendor terms. That context lets the CISO, operations, reliability, compliance, legal and asset leadership choose a proportionate action and explain it later.

QuestionWhy it mattersPractical outcome
Is the tool approved?Approval confirms that ownership, terms and intended use were reviewed. A familiar brand is not evidence that the account or feature in use is sanctioned.Label the service approved, restricted, under review or blocked. Record the account tier and approved purpose, not only the vendor name.
What data could reach it?The same assistant can be low risk for public research and high risk for network diagrams, operational data, asset conditions, market positions and critical-infrastructure information.Define prompt examples by data class. Give users concrete red lines and a safe route for the useful workflow.
What do the terms say?Training, retention, subprocessors, location, deletion and administrative controls vary by plan and can change over time.Capture a dated vendor decision. Recheck material services on renewal and whenever the report shows a new domain or product.
Who is using it?Ten hits from one lab, practice or branch call for a different response than ten hits spread across public-research roles.Start with the highest-risk identity cluster. Ask about the task before deciding whether to coach, migrate, investigate or block.
Does an existing tool cover the need?Shadow adoption often signals that an approved platform is unavailable, difficult to use or poorly communicated.Remove friction, publish the approved route and measure whether users migrate during the next comparable audit window.
Six-step playbook

Run the first review without creating panic

The strongest first audit is narrow enough to explain and repeat. Use a normal operating period, preserve the source details and state the limits of DNS or proxy evidence in the report.

Choose a representative window

Start with 14 to 30 days that avoid a shutdown, migration or major outage. Record the dates, networks, identity coverage and exclusions. That scope statement makes comparisons honest and prevents a partial export from being mistaken for an enterprise census.

Export the minimum useful fields

From corporate DNS, IT/OT boundary resolvers, secure gateways, remote access and managed field devices, retain timestamp, hostname, action and the most useful identity field available. Do not add URL paths, request bodies or prompt content. Inventory work needs enough attribution to act, not the maximum amount of personal data.

Validate the largest clusters

Remove known test traffic, shared resolvers and infrastructure identities before interpreting user counts. Look for repeated use over several days and clusters within a team. A single lookup may be an email link or background process; a stable pattern deserves a conversation.

Add business context

Meet the relevant team with neutral questions: what task is being completed, what information is entered, which account tier is used and why the approved route does not work. Document the answer beside the technical observation so reviewers can distinguish evidence from inference.

Assign a proportionate action

Block services built for abuse or those with unacceptable terms. Migrate useful work to an enterprise product when controls can make it safe. Coach occasional low-risk users, and escalate suspected disclosure through the existing incident process rather than inventing an AI-only procedure.

Re-run and close the loop

Use the same source and similar window after remediation. Compare tool prevalence, active identities and sanctioned share. A decline supports closure; persistent traffic can reveal browser extensions, mobile devices, alternative domains or a workflow the replacement failed to solve.

Shared ownership

Give every function a clear part in the control

Shadow AI crosses technical, contractual and operational boundaries. A central policy works only when each function knows which decision it owns and where to send an exception.

Security and IT

Maintain discovery coverage, investigate technical anomalies and operate access controls. Security should explain what the logs prove and where visibility ends. It also checks whether sanctioned services support identity, logging, retention and configuration standards.

Privacy and legal

Translate observed workflows into data, confidentiality and notification questions. Review terms for training, retention, location and subprocessors. When facts suggest a disclosure, use the established legal and privacy assessment process rather than deciding from a domain count.

Procurement and vendor risk

Prioritize services that employees actually use. Confirm the exact plan, contracting entity and product features because one vendor can offer several materially different data practices. Preserve the assessment date and schedule a review for important services.

Business owners

Explain the task, data and reason for adoption. Decide whether the workflow is valuable enough to sanction, redesign or replace. Owners also nominate local guidance, test approved alternatives and confirm that remediation works in daily practice.

People and communications

Give employees examples they recognize, a simple approved-tool directory and a route to request new uses. Communications should avoid implying that DNS reveals prompts. Training is more credible when it solves the workflow that led users to the tool.

Internal audit and assurance

Test whether scope is documented, findings have owners, exceptions expire and follow-up runs verify change. Assurance can sample the chain from source export to final disposition without needing access to every identity in the operational report.

Evidence pack

What to preserve for audit, legal and leadership review

In energy and utilities, the relevant obligations can include NERC CIP where applicable, critical-infrastructure directives, market conduct rules, environmental reporting duties, records requirements. A domain inventory does not satisfy those frameworks by itself. It supplies a dated factual layer that existing governance processes can use.

Scope statement

Identify the log source, dates, included networks and available identity types. List known blind spots such as unmanaged mobile data, direct IP connections or sites that use a different resolver.

This keeps later readers from giving the numbers more certainty than the collection method supports.

Observed-tool register

Keep the service name, matched domains, category, first and last observation, identities and sanctioned status. Store dated vendor-term research beside the observation rather than silently overwriting old decisions.

The result becomes a practical subset of the wider AI system inventory.

Decision record

For each material tool, name an owner, intended use, permitted data, account requirement and disposition. Include the reason for approval, restriction or blocking in language a business user can follow.

A short rationale is more useful than a color with no explanation.

Remediation evidence

Attach tickets, procurement decisions, configuration changes, user guidance and incident references where applicable. Link each artifact back to the finding it addresses.

This traceability shows that discovery led to controlled action rather than a report that was filed and forgotten.

Exception register

Some teams need a restricted tool temporarily. Record the business reason, data limits, accountable owner, compensating controls and expiry date.

Time-bound exceptions prevent urgent workarounds from becoming permanent, invisible policy.

Follow-up comparison

Preserve a comparable later report and explain major changes in scope. Track whether targeted identities moved, whether alternative domains appeared and whether approved services gained adoption.

Trend evidence makes the control testable instead of merely aspirational.

Worked example. A utility audit identifies consumer chatbot traffic from engineering laptops and a mobile image service from a contractor network. Neither result proves sensitive data moved, but both identify where to ask. The utility confirms the workflows, restricts critical information, offers an approved alternative and retains before-and-after reports as evidence.
Management view

Metrics that show control is improving

A large raw hit count is rarely a useful board metric because DNS caching and automated traffic distort volume. Favor stable measures tied to coverage, decisions and follow-through.

Inventory coveragePercentage of in-scope networks and identities represented in the export, with missing locations named.
Sanctioned adoptionShare of active AI identities using approved services during the period, tracked against the same population.
Unreviewed servicesNumber of newly observed tools with no owner or documented decision, plus their age since discovery.
High-risk identitiesDistinct identities reaching services marked for restriction or blocking, counted without implying confirmed disclosure.
Time to dispositionMedian days from first observation to approve, restrict, migrate, block or close as benign technical traffic.
Remediation persistencePercentage of targeted findings absent in the next comparable run, with bypasses investigated separately.
Program questions

Questions Energy and utilities teams ask

Does a DNS match prove that sensitive information was uploaded?

No. It proves that a covered identity or network resolved a domain during the selected period. Confirm the workflow through interview, endpoint evidence or the vendor’s administrative logs before making a disclosure finding.

Why not block every public AI service immediately?

Immediate blocking can interrupt legitimate work and push users to personal devices or less visible services. Discovery first lets the organization protect urgent risks, preserve useful workflows and provide an approved alternative users will actually adopt.

Can this replace vendor risk assessment?

No. The inventory tells vendor risk which services are actually present and which deserve priority. Procurement, privacy, legal and security still need to assess terms, controls, subprocessors, location, retention and the intended data.

How often should the organization repeat the audit?

Quarterly is a practical baseline for a stable environment. Monthly review suits fast adoption, active remediation or higher-risk groups. Repeat after major policy, network or approved-tool changes, using comparable scope whenever possible.

What if the logs identify a device rather than a person?

Keep the device identity and map it through the asset system only when investigation requires it. Network-level attribution is still useful for locating a site or function, and the report should state that it does not represent a unique-user count.

How should employee communications describe the review?

Explain the business purpose, data sources, fields used, retention, who can see results and how findings will be validated. Clear notice supports trust and prevents a domain observation from being presented as surveillance of prompt content.

What belongs on the approved AI list?

Name the product and account tier, approved purposes, permitted data classes, required settings, owner and review date. A vendor-level approval is too broad when consumer and enterprise plans have different training and administrative controls.

When does a finding become an incident?

Use the organization’s existing incident criteria. Escalate when validation indicates that protected information entered an unauthorized service, credentials were exposed or contractual and regulatory duties may apply. The domain match alone is a lead, not the final conclusion.

Related Resources

Energy Shadow AI FAQ

Does the audit connect to our OT or SCADA network?
No. The audit analyses DNS and proxy log exports only. It does not connect to your operational technology network, SCADA systems, DCS or any control equipment. You export the logs from your IT-side DNS resolver or web proxy.
How does this relate to NERC CIP compliance?
NERC CIP-011 requires protection of BES Cyber System Information. If staff use AI tools to process data about bulk electric system assets, that information leaves your CIP boundary. The audit identifies which AI tools are accessed from CIP-scoped network segments so you can assess and remediate before your next CIP audit.
Can we scope this to our CIP-regulated facilities only?
Yes. If your DNS or proxy logs include subnet or facility identifiers, the audit segments results by location. This lets you focus on AI tool usage at generation plants, transmission substations and control centres within your NERC CIP boundary.
What about AI features in our EMS or ADMS?
AI features embedded in energy management systems, distribution management systems and other OT platforms generate DNS traffic to their AI service endpoints. The audit identifies these, letting you verify that your vendor agreements cover AI-specific data handling within your CIP compliance boundary.
Sector list

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