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Internal Communications Manager

Support executive communications and ghostwriting

Enhances✓ Available Now

What You Do Today

Write or edit CEO blogs, leadership messages, and executive social media posts that sound like the executive wrote them

AI That Applies

AI generates drafts matching executive voice profiles, suggests topics from industry trends, optimizes for channel

Technologies

How It Works

The system ingests industry trends as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output — drafts matching executive voice profiles — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

First drafts that already sound like the executive. More content volume with consistent voice

What Stays

Truly capturing the executive's voice (not just their words), choosing topics that reinforce strategy

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 support executive communications and ghostwriting, understand your current state.

Map your current process: Document how support executive communications and ghostwriting works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Truly capturing the executive's voice (not just their words), choosing topics that reinforce strategy. 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 Voice matching AI 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 support executive communications and ghostwriting 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 CMO or VP Marketing

What content do we produce the most of that follows a repeatable structure?

They set the AI investment priorities for marketing

your marketing automation admin

What's our current review and approval process, and would AI-generated first drafts change the bottleneck?

They know what capabilities exist in your current stack that you're not using

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.