Executive Offices.
6 real jobs AI can take on for a executive offices team - most of them inside the licence you already pay for. The colour on each card is the kind of AI; the line at its foot is what it takes to get it.
THE COLOUR IS THE KIND OF AI — AUTONOMY RISES LEFT TO RIGHT
The line at the foot of each card is what it takes to get it - a free chatbot, the licence you already pay for, or a build.
If these words are new, the homepage walks the whole spectrum →
Internal communications optimization.
Communications teams must ensure consistent and effective communication within large or distributed teams. AI can help to reduce long cycle times to draft and review content to ensure optimal timing of message delivery. AI-driven analytics can assess engagement with internal messages and suggest improvements.
A consistent company-wide message is researched, scripted, presented and followed up in a fraction of the usual time.
Try it in your own AI
- Context: I'm preparing [leader]'s all-hands for [date] at [company]. The quarter's story is [one line, e.g. good results, hard change coming]; the risk is a speech that lists announcements instead of telling it.
Objective: From the results and announcements below, script the briefing: the through-line first, then the quarter's evidence, then what happens next and what we're asking of people. Include the two questions the room will be thinking, with honest answers. [Paste the results and announcements.]
Style: A spoken script, [length] minutes, short sentences, a clear landing.
Tone: [The leader]'s - [one line on how they talk]. No corporate triumph.
✓ In the licence you already pay for
Day in the life.
See how people can use your AI assistant to perform common tasks throughout their day to save time, generate value, and improve their wellbeing.
A chief executive moves through meetings, decisions and correspondence faster while staying on top of every priority.
Try it in your own AI
- Context: I'm the [CEO/MD] of [company]. The papers below arrived overnight for today's decisions; my scarce resource is attention, not information.
Objective: For each paper: the decision being asked, the recommendation and its weakest assumption, and what I'd want to know before saying yes. Then tell me which of today's items shouldn't need me at all. [Paste or attach the papers.]
Style: Half a page per paper, the weakest assumption in bold, the delegation list at the end.
✓ In the licence you already pay for
A leader keeps a live deal on track by capturing calls, surfacing key facts and acting on next steps without delay.
Uses your suite's meeting AI - how this lands varies by licence.
Try it in your own AI
- Context: I'm leading [an acquisition / a live deal] at [company] - stage: [where it is]. Calls are moving faster than the paper trail and details are starting to slip.
Objective: From the call notes and threads below, maintain the deal picture: what's agreed, what's open, what changed this week, who owes what by when - and flag anything said in one thread that contradicts another. [Paste the notes and threads.]
Style: A running deal sheet - agreed, open, changed, owed - contradictions flagged at the top.
✓ In the licence you already pay for
A technology chief absorbs dense information quickly and reaches well-grounded decisions with sharper confidence.
Try it in your own AI
- Context: I'm CTO at [company]. The paper below wants a decision on [topic]; it's dense, and my job is judgement, not reading stamina.
Objective: Give me the argument's skeleton: the claim, the evidence it rests on, the assumptions doing the heaviest lifting, what would have to be true for the recommendation to be wrong, and the two questions to ask its author. [Paste the paper.]
Style: One page. Not a summary of the summary - the skeleton.
✓ In the licence you already pay for
An information leader directs and supports their team with less admin and clearer oversight of every workstream.
Try it in your own AI
- Context: I lead [n] teams as [CIO / IT director] at [company]. The updates below are this week's; my failure mode is discovering in week six what a team knew in week two.
Objective: Cross-read them: what each team says, what they're not saying (slipped dates mentioned casually, risks in the passive voice), where two teams' plans quietly conflict, and the three conversations I should have this week. [Paste the updates.]
Style: By team, two lines each; the unsaid flagged in its own list.
✓ In the licence you already pay for
A data leader reviews initiatives at pace, spotting progress, gaps and risks across the portfolio in one sweep.
Try it in your own AI
- Context: I review the data portfolio at [company] - [n] initiatives. The updates below are due today and I need the portfolio's shape, not each project's story.
Objective: Across all initiatives: which are delivering against their original case, which have drifted from it, where the same blocker appears twice, and the one initiative I should look at hardest. [Paste the updates.]
Style: Portfolio view as a table, then the hard-look case argued in a paragraph.
✓ In the licence you already pay for
Most of these run on the licence you already pay for.
The gap is that nobody's pointed it at the job yet. That's the work we do, and it starts with a half-hour call - bring the one that looked most like your week and we'll tell you whether it's a quick win or a proper build. No licence yet? We'll help you pick one first.
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