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Director of Communications

Draft executive communications

Enhances✓ Available Now

What You Do Today

Write speeches, earnings call talking points, internal memos, and LinkedIn posts for C-suite leaders. Match their voice, anticipate audience questions, and stay on message.

AI That Applies

AI-assisted writing — generative AI produces first drafts in the executive's voice, adapting for audience and channel.

Technologies

How It Works

For draft executive communications, the system draws on the relevant operational data and applies the appropriate analytical models. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output — first drafts in the executive's voice — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

First drafts are ready in minutes instead of hours. The AI captures the executive's voice patterns and key messages, giving you a solid starting point to refine.

What Stays

The editorial judgment — knowing what the CEO can and can't say, managing the political subtext, ensuring legal and compliance sign-off — that's your expertise.

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 draft executive communications, understand your current state.

Map your current process: Document how draft executive communications works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: The editorial judgment — knowing what the CEO can and can't say, managing the political subtext, ensuring legal and compliance sign-off — that's your expertise. 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 Writer 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 draft executive communications 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.