VP Regulatory Affairs
Data request management
What You Do Today
Manage the flood of data requests from commission staff and intervenors during proceedings — coordinating responses across departments, ensuring accuracy, and meeting deadlines while protecting confidential information.
AI That Applies
AI categorizes incoming data requests, routes them to appropriate departments, tracks deadlines, and flags requests that may require confidentiality claims or legal objections.
Technologies
How It Works
For data request management, the system tracks deadlines. 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
Data request tracking and routing becomes automated — no more spreadsheet-based deadline management.
What Stays
Reviewing response accuracy, making strategic decisions about how much to disclose, and crafting objections to overbroad requests.
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 data request management, 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 data request management 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 data do we already have that could improve how we handle data request management?”
They shape expectations for how AI appears in governance
your CTO or CIO
“Who on our team has the deepest experience with data request management, and what tools are they already using?”
They own the technology infrastructure that enables AI adoption
a peer executive at a company further along on AI adoption
“If we brought in AI tools for data request management, what would we measure before and after to know it actually helped?”
Their lessons learned are worth more than any consultant's framework
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.