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VP Regulatory Affairs

Grid modernization and clean energy regulatory strategy

Enhances◐ 1–3 years

What You Do Today

Shape the regulatory framework for grid modernization investments, clean energy mandates, and performance-based regulation. Position the utility to earn returns on new technology investments while meeting policy objectives.

AI That Applies

AI benchmarks peer utility approaches to grid modernization cost recovery and models the financial impact of different regulatory frameworks (cost-of-service vs. performance-based).

Technologies

How It Works

The system monitors regulatory data sources — rule changes, enforcement actions, and compliance records. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What Changes

Benchmarking and framework analysis becomes more comprehensive with AI-powered research across jurisdictions.

What Stays

Crafting the regulatory narrative that connects technology investments to customer benefits, and navigating the political dynamics of energy transition.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for grid modernization and clean energy regulatory strategy, understand your current state.

Map your current process: Document how grid modernization and clean energy regulatory strategy works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Crafting the regulatory narrative that connects technology investments to customer benefits, and navigating the political dynamics of energy transition. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support PLEXOS tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long grid modernization and clean energy regulatory strategy takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your board chair or lead independent director

What's our current capability gap in grid modernization and clean energy regulatory strategy — and is it a people problem, a tools problem, or a process problem?

They shape expectations for how AI appears in governance

your CTO or CIO

If we automated the routine parts of grid modernization and clean energy regulatory strategy, what would the team do with the freed-up time?

They own the technology infrastructure that enables AI adoption

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.