Artificial intelligence in electric utilities depends on strong operational data foundations. Most successful AI initiatives begin with improvements in data integration, operational visibility, and analytics maturity. This assessment evaluates your cooperative's readiness in these areas.
How to use: For each domain, award one star for each question you can honestly answer YES to. Four questions per domain — four stars maximum. No stars = none in place — that's a valid and useful answer. Your total score updates automatically and highlights your readiness tier.
☆ Yes to none
★
Yes to one
★★
Yes to two
★★★
Yes to three
★★★★
Yes to all four
Most cooperatives score higher here than in a structured review — that gap is exactly where we help.
01
Data Foundations
Operational data quality and accessibility · ERP · GIS · AMI · OMS · CIS · SCADA
Is AMI data sufficiently complete and reliable (<2% missing interval reads)?
Are GIS asset records routinely validated and aligned with field reality?
Is at least five years of historical operational data accessible for analysis?
Are core operational systems integrated or does leadership rely on manual data consolidation?
Rating
— / 4
02
Leadership Alignment & Strategy
Executive ownership and direction
Is there a clearly identified executive responsible for AI and analytics initiatives?
Has leadership identified and prioritized specific operational AI use cases?
Is there a documented roadmap for analytics and AI adoption over the next 2–3 years?
Are success metrics defined before pilots or analytics initiatives begin?
Rating
— / 4
03
Technology & Integration Readiness
Infrastructure and system architecture
Do core systems provide APIs or integration mechanisms for analytics platforms?
Can current infrastructure support modern analytics or machine learning workloads?
Has technical debt across operational systems been formally assessed and prioritized?
Do modernization or system replacement initiatives include analytics and integration requirements?
Rating
— / 4
04
Cybersecurity & Governance
Risk, compliance, and data stewardship
Is a formal cybersecurity framework in place (NERC CIP, NIST, or equivalent)?
Do vendor agreements clearly define ownership and permitted use of cooperative data?
Does the cooperative have policies governing AI usage and data governance?
Have regulatory or reputational risks of AI deployment been assessed?
Rating
— / 4
05
Measurement & ROI Discipline
Ensuring AI initiatives deliver measurable value
Are baseline operational metrics established before analytics or AI pilots begin?
Are comparison periods or control groups defined to measure improvement?
Are financial ROI thresholds defined before scaling analytics initiatives?
Is a specific leader accountable for reporting outcomes of each pilot to executive leadership?
Rating
— / 4
Readiness Tiers — Total your 5 domain ratings (max 20 points)
Scores reflect self-assessed readiness. A facilitated evaluation typically reveals additional gaps not visible at the leadership level.
< 8
Early Stage
The earlier we engage, the more we can shape the right path forward.
8–11
Foundation Building
We help cooperatives at this stage build the right foundation from the start.
12–16
Conditionally Ready
Good progress. A structured review often surfaces gaps that accelerate results.
17–20
AI-Ready
Strong foundation. Let's validate your readiness and identify quick wins.
Total Score
—
out of 20
Bonus Questions — Not counted in your total score
How quickly can leadership answer a major operational question using reliable data?
★★★★ Same day — Leadership can quickly access integrated dashboards or reports
★★★ Several days — Data must be gathered from multiple systems before analysis
★★ Several weeks — Significant manual effort is required to assemble the data
★ Not sure — Leadership lacks consistent access to operational data
Rating
— / 4
Does the board receive regular reporting on how data and analytics are improving operational performance?
★★★★ Yes — regularly included in board reporting
★★★ Occasionally discussed when major initiatives arise
Paste your results into the Special Requests field on the booking form, and schedule a meeting to discuss your results and identify next steps.
Cooperative Leadership Series
AI & ANALYTICS READINESS ASSESSMENT
for Cooperative Leadership Teams
Artificial intelligence in electric utilities depends on strong operational data foundations. Most successful AI initiatives begin with improvements in data integration, operational visibility, and analytics maturity. This assessment evaluates your cooperative's readiness in these areas.
How to use: For each domain, award one star for each question you can honestly answer YES to. Four questions per domain — four stars maximum. No stars = none in place — tap a star to select, tap again to clear.
☆
Yes to none
★
Yes to one
★★
Yes to two
★★★
Yes to three
★★★★
Yes to all four
Most cooperatives score higher here than in a structured review — that gap is exactly where we help.
5 Domains · 20 Questions
Domain 01
Data Foundations
Operational data quality and accessibility · ERP · GIS · AMI · OMS · CIS · SCADA
Is AMI data sufficiently complete and reliable (<2% missing interval reads)?
Are GIS asset records routinely validated and aligned with field reality?
Is at least five years of historical operational data accessible for analysis?
Are core operational systems integrated or does leadership rely on manual data consolidation?
Your Rating
— / 4
Domain 02
Leadership Alignment & Strategy
Executive ownership and direction
Is there a clearly identified executive responsible for AI and analytics initiatives?
Has leadership identified and prioritized specific operational AI use cases?
Is there a documented roadmap for analytics and AI adoption over the next 2–3 years?
Are success metrics defined before pilots or analytics initiatives begin?
Your Rating
— / 4
Domain 03
Technology & Integration Readiness
Infrastructure and system architecture
Do core systems provide APIs or integration mechanisms for analytics platforms?
Can current infrastructure support modern analytics or machine learning workloads?
Has technical debt across operational systems been formally assessed and prioritized?
Do modernization or system replacement initiatives include analytics and integration requirements?
Your Rating
— / 4
Domain 04
Cybersecurity & Governance
Risk, compliance, and data stewardship
Is a formal cybersecurity framework in place (NERC CIP, NIST, or equivalent)?
Do vendor agreements clearly define ownership and permitted use of cooperative data?
Does the cooperative have policies governing AI usage and data governance?
Have regulatory or reputational risks of AI deployment been assessed?
Your Rating
— / 4
Domain 05
Measurement & ROI Discipline
Ensuring AI initiatives deliver measurable value
Are baseline operational metrics established before analytics or AI pilots begin?
Are comparison periods or control groups defined to measure improvement?
Are financial ROI thresholds defined before scaling analytics initiatives?
Is a specific leader accountable for reporting outcomes of each pilot to executive leadership?
Your Rating
— / 4
Total Score
out of 20
—
Readiness Tiers
Scores reflect self-assessed readiness. A facilitated evaluation typically reveals additional gaps.
< 8
Early Stage
The earlier we engage, the more we can shape the right path forward.
8–11
Foundation Building
We help cooperatives at this stage build the right foundation from the start.
12–16
Conditionally Ready
Good progress. A structured review often surfaces gaps that accelerate results.
17–20
AI-Ready
Strong foundation. Let's validate your readiness and identify quick wins.
Bonus Questions — Not counted in your total score
How quickly can leadership answer a major operational question using reliable data?
★★★★ Same day — Leadership can quickly access integrated dashboards or reports
★★★ Several days — Data must be gathered from multiple systems before analysis
★★ Several weeks — Significant manual effort is required to assemble the data
★ Not sure — Leadership lacks consistent access to operational data
Your Rating
— / 4
Does the board receive regular reporting on how data and analytics are improving operational performance?
★★★★ Yes — regularly included in board reporting
★★★ Occasionally discussed when major initiatives arise
★★ Discussed informally but not systematically
★ Not currently part of board-level reporting
Your Rating
— / 4
Wherever you are, we can help.
1 — Copy your results
Saves a summary to your clipboard
2 — Schedule a meeting
Paste your results into the Special Requests field and schedule a time to discuss.