VP Regulatory Affairs
Internal education and regulatory awareness
What You Do Today
Educate company leadership and operating teams on regulatory implications of business decisions. Ensure executives understand what can and can't be recovered in rates, and how operational decisions affect regulatory outcomes.
AI That Applies
AI summarizes recent commission decisions and trends in formats accessible to non-regulatory audiences, tracking how commission sentiment is shifting on key issues.
Technologies
How It Works
The system monitors regulatory data sources — rule changes, enforcement actions, and compliance records. The analytics engine aggregates data across sources, applies statistical analysis to identify significant patterns and outliers, and presents the results through visualizations that highlight what needs attention. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.
What Changes
Regulatory intelligence summaries become more timely and targeted to specific audiences within the company.
What Stays
Translating regulatory complexity into business language, advising executives on risk, and the judgment to know when a business decision will create a regulatory problem.
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.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for internal education and regulatory awareness, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long internal education and regulatory awareness 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.
Start These Conversations
Who to talk to and what to ask
your board chair or lead independent director
“What's the biggest bottleneck in internal education and regulatory awareness today — and would AI address the bottleneck or just speed up something that's already fast enough?”
They shape expectations for how AI appears in governance
your CTO or CIO
“What would have to be true about our data quality for AI to work reliably in internal education and regulatory awareness?”
They own the technology infrastructure that enables AI adoption
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.