Skip to content

Executive Assistant

Supporting special projects and strategic initiatives

Automates✓ Available Now

What You Do Today

Take on project management for your executive's priority initiatives — tracking deliverables, coordinating teams, managing timelines, and ensuring nothing falls behind.

AI That Applies

AI tracks project milestones, sends automated status requests, generates progress dashboards, and flags items at risk of falling behind schedule.

Technologies

How It Works

The system ingests project milestones as its primary data source. The automation engine executes each step in the process sequence — validating inputs, applying business rules, generating outputs, and routing exceptions to human review queues. The output — progress dashboards — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

Project tracking is more systematic and visual. Status collection is automated rather than chasing people for updates.

What Stays

Driving accountability and removing obstacles. When a deliverable is late, you're the one who follows up with just the right amount of urgency.

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 supporting special projects and strategic initiatives, understand your current state.

Map your current process: Document how supporting special projects and strategic initiatives works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Driving accountability and removing obstacles. 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 project management platforms 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 supporting special projects and strategic initiatives 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 data do we already have that could improve how we handle supporting special projects and strategic initiatives?

They shape expectations for how AI appears in governance

your CTO or CIO

Who on our team has the deepest experience with supporting special projects and strategic initiatives, 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 supporting special projects and strategic initiatives, what would we measure before and after to know it actually helped?

Their lessons learned are worth more than any consultant's framework

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.