InfrastructureIssue 126 records
Utility Management
State regulators moved two utility AI and cyber resolutions forward this week. NARUC's water-cybersecurity resolution, which backs minimum requirements and an EPA-authorised standards body, and a resolution endorsing EPRI's SAFERai.power AI-risk framework both cleared committee and go to the Board on 11 Nov. An independent look at Project Watershed 250 shows why minimums alone are not enough: free assessments and AI tools expose gaps that small water systems lack the money, staff and governance to fix. On operations, Anglian Water reports control-room time savings from AI, a Reclamation-funded guidebook sets guardrails for treatment-plant ML, UAMPS and Basin Electric picked a transmission-scheduling agent, and APPA joined EPRI's AI forum. Gas, metering/billing and measured stormwater were thin.
- Evidence records
- 6
- Cross-source patterns
- 3
- Evidence classes
- 2 public-sector association guidance2 vendor claim1 independent reporting1 standards or public-body guidance
- Outcomes
- 3 emerging1 cautionary1 effective1 mixed
- Source freshness
- 5 new this fortnight1 older, newly relevant
- Research completed
- 2026-11-11
Choose a role to see its takeaway beside every record in the ledger.
Patterns across the evidence
Synthesis · Lighthouse Advisory interpretation
Water-cyber expectations are rising while free federal support shrinks, leaving remediation funding unresolved
NARUC's committee-passed WC-1 resolution backs minimum cybersecurity requirements for all water systems and records that CISA stopped six free assessments in September 2026. Industrial Cyber's review of Project Watershed 250 finds that free red-team assessments and AI tools reach some Texas utilities for six months, but remediation needs hardware, OT staff, governance and recurring money that federal programmes do not reliably fund for small systems. Together they suggest utilities will be asked to meet higher baselines with less free help. Interpretation: plan and budget remediation now rather than waiting for a standard.
Operating questionFor every open finding from a recent cyber assessment, who owns the fix, what does it cost, and which funding source pays for it after free programmes end?
Supporting evidenceNational Association of Regulatory Utility Commissioners (NARUC)Industrial Cyber (features desk); programme partners ONCD, Texas Cyber Command, Texas Governor's Office, EPA, CISA
Regulators and public power are routing utility AI governance through EPRI-led frameworks
NARUC's Executive Committee passed EX-1 commending EPRI's SAFERai.power risk framework and urging state-regulator participation, and APPA joined EPRI's APEX forum the same week to track AI use and AI-driven load for public power. Neither has produced deliverables yet. Interpretation: municipal and regulated utilities are likely to see AI expectations framed around EPRI's consequence-and-autonomy approach, so keeping an AI use-case register now will make that guidance easier to adopt.
Operating questionDoes the utility have a current register of AI tools with owner, autonomy level and override, ready to map to EPRI or regulator frameworks?
Supporting evidenceNational Association of Regulatory Utility Commissioners (NARUC)American Public Power Association (APPA) and Electric Power Research Institute (EPRI)
Operational AI in water and power is being staged: advisory first, measured, then expanded
The Reclamation-funded guidebook requires advisory trials, parallel-train benchmarks and setpoint floors before AI controls treatment. Anglian Water says its tools are field-tested under safe conditions with metrics gathered before scaling. OATI's guidance for the UAMPS/Basin agent says pilots rise or stall on NERC CIP, operator trust and data. The guidebook is the only one of the three that gives controls in detail; the other two are self-reported or concept-stage.
Operating questionWhat measured baseline and concurrent comparison will decide whether an AI tool moves from recommending to acting?
Supporting evidenceAnglian Water Services with Aiimi (Microsoft UK guidance and training subsidy); reported by H2O Global NewsCarollo Engineers, Yokogawa, National Water Research Institute and Baylor University, for the U.S. Bureau of ReclamationOATI (Open Access Technology International) with Utah Associated Municipal Power Systems (UAMPS) and Basin Electric Power Cooperative
Evidence ledger
Full record · every source keeps its link and limitations
NARUC water-cybersecurity resolution (WC-1) and EPRI SAFERai.power AI-governance resolution (EX-1) clear committees; Board vote set for 11 Nov
NARUC's 10 Nov packet lists resolutions that passed the standing committees at the 2026 Annual Meeting. WC-1 (water cybersecurity), sponsored by Commissioner Bange, was sponsored by the Committee on Water on 9 Nov. It supports minimum cybersecurity requirements for all drinking water and wastewater operators while preserving state authority. It urges Congress to reauthorize and fund CISA, to require utilities to share cyber-attack information exempt from FOIA, and to authorize an EPA-created, non-governmental Water Risk and Resilience Organization (WRRO) to set minimum requirements. Its findings: about 50,000 community water systems, only 11% under commission jurisdiction; attacks on utilities in at least 12 states in July–August 2026; CISA has lost about a third of its staff since 2025 and stopped six free assessments in September 2026. EX-1, passed by the Executive Committee on 8 Nov, commends EPRI's SAFERai.power initiative (risk framework, assessment protocols, playbooks, toolkit) and supports state-regulator participation. The Board adoption lines are still blank; the Board meets 11 Nov.
Why it matters, evidence and limitations
- Why it matters
- Follow-up to the archived 3 Nov draft: both resolutions have now cleared committee and go to the Board. If adopted, state regulators formally back minimum water-cyber requirements and an EPRI-led approach to assessing utility AI by consequence and autonomy. Utilities and their partners should expect commissions to ask about both.
- Evidence and measured results
- Primary association document. The figures (50,000 systems, 11%, 12 states, CISA staffing) are the resolution's own findings, not separately sourced in the text. No vote count. Packet says resolutions are not NARUC policy until the Board passes them and may change.
- Limitations and uncertainty
- Not yet adopted; text could change at the Board. NARUC resolutions are advocacy and carry no regulatory force. WC-1 addresses Congress; EX-1 concerns electric utilities only.
Project Watershed 250: free red-team and AI tools for Texas water utilities expose a remediation and funding gap once the six-month pilot ends
Feature on Project Watershed 250, a six-month pilot launched 31 Aug 2026 by ONCD and Texas Cyber Command with EPA and CISA. Participating utilities get red-team assessments, AI tools, threat intelligence, training, remediation help and defensive tools free. Texas has more than 7,400 public water systems and 3,000 wastewater facilities. Practitioners from West Yost, I&C Secure, Dispel and the Roosevelt Group say finding vulnerabilities is easy but fixing them needs hardware, scarce OT staff and money. They note six months is barely enough to start, tools carry recurring licence fees, and governance and team friction often stall fixes. Texas Cyber Command bars automatic conversion to paid services after the pilot. Federal funding is fragmented: SRF loans need a 20% state match; SDWA 1433(g) and 1459G expired unfunded; resilience grants reach only systems serving 10,000+ people; EPA's $11.75M in August grants went to 10 midsize and large systems.
Why it matters, evidence and limitations
- Why it matters
- Independent scrutiny of the dominant federal response to the 2026 PLC attacks, published the day the NARUC water-cyber resolution is pending. It shows that free assessment and AI tooling without remediation funding and governance may not change outcomes for small municipal systems.
- Evidence and measured results
- Feature with named experts and programme facts; no measured outcomes from the pilot yet. Funding figures are attributed to EPA announcements and a Roosevelt Group adviser. Author opinion ('the pilot will almost certainly work') is commentary.
- Limitations and uncertainty
- Trade press with commentary; includes a vendor executive (Dispel). Pilot is ongoing with no published results. Texas-specific programme.
Anglian Water and Aiimi report first AI Accelerator results: control-room dashboard saves two hours per person per day; pollution-response assistant used on live incidents
Anglian Water and Aiimi published first results from their AI Accelerator. The Situational Awareness Solution, an AI dashboard for control-room teams, is said to save two hours per person per day on shift handovers (about 62.5 working days a year), to have helped mitigate pollution events and improved compliance scores; it is now deployed across the business as a microservice. The Surfacing Historic Mitigating Actions assistant analyses hundreds of thousands of past events to surface root causes, lessons and knowledgeable colleagues; within two months it helped heavily mitigate one potential pollution event and reduced another to zero environmental impact. A steering group has identified 50+ use cases; tools field-tested 'under safe conditions' with security, data protection, model risk management and explainability built in, and metrics gathered throughout. Runs on a Microsoft stack; part of a multi-million-pound deal of up to eight years.
Why it matters, evidence and limitations
- Why it matters
- One of few water-utility AI programmes reporting operational time savings and incident outcomes, with a stated use-case pipeline and governance approach. U.S. municipal utilities can borrow the operating model (steering group, staged field tests, metrics), though regulatory context (AMP8) differs.
- Evidence and measured results
- Company-reported results relayed by trade press. No baseline method, sample size, or how the two-hour saving was measured; pollution outcomes are two anecdotes. Compliance-score improvement is not quantified.
- Limitations and uncertainty
- Vendor and client self-reported; vendor commercial interest; UK regulatory context; no independent evaluation; measurement method undisclosed.
Reclamation-funded AI & ML Guidebook for Potable Reuse sets staged, guardrailed validation for treatment-plant ML; newly promoted to U.S. utilities on 10 Nov
The guidebook, from a Reclamation-funded project on data-driven fault detection and process control for potable reuse, gives utilities a staged path from desktop ML to full-scale use. It warns ML is 'extremely site-specific': models trained on one membrane or filter were inaccurate on others in the same plant, so tools proven at a demonstration facility need retraining at full scale. Safeguards: semi-autonomous trials (AI recommends, operators act) before automation, keep all prior alarms, trial on one parallel train, divert AI-controlled water to sewer for direct potable reuse, and program floors so AI cannot set treatment intensity below the old control system until months of validation. It flags data leakage (suspicious >99% accuracy) and calls for time-based splits. Case studies: a three-week full-scale dissolved-oxygen digital twin with 23% lower aeration energy per kg ammonia versus adjacent weeks; a modelled NDMA soft sensor where a two-standard-deviation safety factor halves UV energy savings from 26% to 13%.
Why it matters, evidence and limitations
- Why it matters
- Why now: ASCE promoted the guidebook to U.S. utilities on 10 Nov, quoting its author on phased implementation and data readiness. It is a rare U.S. federally funded, practitioner-written control framework for operational AI in treatment plants, directly usable in procurement and pilot design.
- Evidence and measured results
- Technical guidebook drawing on project work and cited studies. The 23% figure is a three-week, before/after comparison with adjacent weeks (no randomisation); the 26%/13% figures are modelled, not observed. ASCE's 'at least 10%' energy figure for a Southern California facility was not located in the extracted guidebook text and is attributed to ASCE only.
- Limitations and uncertainty
- Focus is potable reuse; transferability to conventional plants is asserted by authors. Engineering-firm authors with commercial interest; not peer-reviewed as a document. Older than the last run; included because it was newly promoted on 10 Nov.
UAMPS and Basin Electric win OATI AI use-case challenge for an agent that chooses book-out vs physical flow, buys transmission and builds e-Tags
At OATI Energy Conference 2026, UAMPS (wholesale supplier to 50 community-owned systems in seven states) and Basin Electric (G&T owned by 138 member co-ops in nine states) jointly won an AI use-case workshop with an agent concept: decide whether a transaction should be a financial book-out or physical flow under current market conditions, find and buy transmission on the right path, build the e-Tag, and pre-build an alternative route and tag in case of curtailment. OATI will develop it with schedulers and traders on its OASIS and e-Tagging systems; each organisation gets a year of complimentary service. OATI's guidance lists constraints that make pilots 'rise or stall': NERC CIP, operator trust and data availability.
Why it matters, evidence and limitations
- Why it matters
- A concrete agentic-AI use case owned by a municipal joint action agency and a co-op, areas thin in recent editions. It is a concept, not a deployment, but shows where public power sees agent value: frequent, time-pressured, data-heavy scheduling decisions.
- Evidence and measured results
- Vendor announcement; no prototype, accuracy or time-saving data. Winning idea will be developed; complimentary service creates a commercial relationship.
- Limitations and uncertainty
- Concept stage; vendor marketing; no independent assessment; results may not apply to distribution-only municipal utilities.
APPA joins EPRI's invitation-only AI-Power Exchange (APEX) to track AI use and AI-driven load for public power
APPA has joined EPRI's AI-Power Exchange (APEX), unveiled in early November as a global, invitation-only forum on AI capabilities and AI-driven electricity demand and their effect on reliability, resilience and affordability. The advisory panel kicked off in Orlando alongside EPRI's DCFlex data-centre flexibility meeting. APEX brings together regulators, national labs, universities and public-benefit organisations to reduce duplication and explore AI use cases, power-system constraints and regulatory alignment. APPA's representative is Michael Coe, VP of Physical and Cyber Security Programs, who says APPA will act as a bridge to keep members informed on AI for power operations. APEX complements DCFlex and EPRI's Open Power AI Consortium.
Why it matters, evidence and limitations
- Why it matters
- Public power now has a formal seat in an EPRI AI forum, the same week state regulators consider endorsing EPRI's SAFERai.power framework. Municipal utilities can expect AI-use guidance and large-load expectations to flow through these EPRI channels.
- Evidence and measured results
- Association announcement; no outputs, membership list or deliverables yet. Invitation-only, so individual municipal utilities may not participate directly.
- Limitations and uncertainty
- Announcement only; no deliverables; relevance to small municipal utilities depends on how APPA relays outputs.
How to read this edition
Source findings, measured results and limitations come from the cited publications. Patterns, operating questions, role takeaways and implementation considerations are Lighthouse Advisory interpretation, stated as questions to validate locally rather than guaranteed outcomes. Vendor and operator claims are labeled as claims. Full research method.
- Public-sector association guidance
- Practitioner guidance or an association-supplied case; not independent outcome evidence.
- Vendor claim
- A supplier-provided assertion that has not been upgraded to independent evidence.
- Independent reporting
- Independent reporting with attributable sources but without a formal evaluation design.
- Standards or public-body guidance
- Normative or advisory guidance from a standards body or public institution.