Director AI Training for Real Estate

AI training for real estate directors.

Understand AI in real estate, see where it can reduce admin, speed up follow-ups, support agents, and reveal practical bespoke solutions tailored to your company's actual needs.

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Real estate AI workflows

human reviewed

Connected appsGmail, WhatsApp, calendar, sheets, presentations

Scheduled tasksInbox scans, viewing follow-ups, offer updates

Prompt packsCopy-paste prompts for everyday director tasks

How teams use it

AI through familiar tools, scheduled jobs, and copy-paste prompt packs.

One simple setup: the team uses AI through connected apps, timed tasks, approved templates, and prompts they can copy.

Team AI workspace

no technical knowledge

Connected apps

Gmail

Outlook

Calendar

Sheets

Excel

CRM

Portals

DocuSign

Drive

Maintenance

Presentation

One assistant. The app changes behind the task.

Schedulerautomatic

12369

7:45amScan inbox automatically

12:00pmFollow up with viewing bookings

4:00pmUpdate latest offers in the source of truth

Prompt packs

1 / 3

Ready-made director prompts with placeholders for the property, dates, policy, and output.

Director offer briefingSummarise all new offers for [property / portfolio] from [date range]. Group by property. For each offer include buyer name, amount, funding status, chain position, conditions, source email or WhatsApp thread, and whether the offer is above the current highest logged offer. Finish with three recommended next actions for the director.Output: short executive brief + offer table.

Viewing follow-up packDraft follow-up messages for everyone who viewed [property] between [dates]. Use the approved agency tone: helpful, concise, no pressure. Ask for feedback, buying position, mortgage approval status, property-to-sell status, and whether they would like to make an offer. Separate warm leads from low-priority leads.Output: ready-to-send messages + lead notes.

Policy and brand checkReview this [agreement / email / advert] against [policy or tone guide]. Flag wording that promises sale timelines, implies guaranteed outcomes, accepts offers without written vendor instruction, or sounds off-brand. Rewrite the risky lines and explain the reason for each change in plain English.Output: flagged risks + corrected draft.

Example one

Email and WhatsApp enquiry reply.

An enquiry comes in. AI checks the property sheet, drafts a reply, asks about the inquirer's own sale status, then stores the captured information.

Property enquiry workflow

New email enquiryreceived

From: Sarah Murphy

14 Oakfield Road enquiry

Hi, is 14 Oakfield Road still available? What offers are currently on it, and what viewing times do you have this week?

Source of truth: property sheetscanning

Asking price	�495,000
BER rating	B3
Current offers	3 offers logged
Highest offer	�508,000
Viewing times	Thu 5:30, Sat 10:30

AI draft and saved lead informationready for review

Draft reply

Hi Sarah, yes, 14 Oakfield Road is still available.

The asking price is �495,000, the BER rating is B3, and the current highest offer is �508,000.

We currently have viewing slots on Thursday at 5:30pm and Saturday at 10:30am.

Do you have a property to sell, and if so, is it on the market, sale agreed, or already sold?

Lead sheet update

Name	Property	Need	Status
Daniel R.	Oakfield	Viewing	Booked
Sarah M.	Oakfield	Offers + viewing	Sale status asked
Aoife K.	Rathmines	Valuation	Follow-up

Example two

Director chatbot for inbox scanning.

The director asks for an update. AI scans inbox context and summarises offers, leads, and maintenance issues, then asks before sending anything externally.

Director AI assistant

permission before sending

Director chat

Scan the inbox and update me on latest offers, new leads, and maintenance issues.

I found 3 new offer emails, 7 buyer leads, and 4 maintenance items since yesterday.

Highest new offer: �512,000 on 14 Oakfield Road. Two leads are mortgage approved and asking for viewings.

There are 4 maintenance issues. Should I prepare a list for the maintenance contractor?

Ask about offers, leads, maintenance...

Latest offers

14 Oakfield Road: new highest offer �512,000. 22 Brook Lane: two offers awaiting vendor feedback.

New leads

7 enquiries found. 2 mortgage approved, 3 asking for viewing times, 1 valuation request, 1 landlord query.

Maintenance issues

Boiler fault, leaking tap, broken gate latch, and extractor fan issue. Contractor list can be prepared for review.

Example three

Agreement draft with policy guardrails.

The director asks for an agreement. AI drafts it, but first reminds them of the agency policy on offers, sale promises, and buyer qualification.

Agreement assistant

policy checked

Team chat

Draft a vendor agreement for 14 Oakfield Road. Add that we can guarantee a sale in 30 days and accept the first strong offer.

Policy reminder: we cannot guarantee sale timelines or accept any offer without written vendor approval.

Agency policy: log every offer, qualify the buyer, then get written vendor instruction before progressing.

Policy-aligned agreement draftready

Sales route: We will recommend a marketing route and review progress weekly, without guaranteeing a sale date.

Offer handling: Every offer will be logged, qualified, and shared with the vendor before any response is issued.

Vendor approval: No offer will be accepted or progressed without written instruction from the vendor.

Example four

Audit trail spreadsheet.

Every AI action is stored in a simple operational log: what happened, which source was used, who reviewed it, and the final status.

AI action log

stored properly

Time	Action	Source used	Human review	Status
09:14	Drafted reply to property enquiry	Inbox + property sheet	Manager review required	Drafted
09:16	Stored buyer requirements	Email conversation	Auto-saved, visible to team	Logged
10:05	Summarised latest offers	Inbox scan	Director reviewed	Reviewed
10:08	Prepared maintenance list	Inbox maintenance emails	Awaiting director approval before sending	In review

Video overview

See the training approach in action.

A short overview of how practical AI training helps teams spot useful workflows and bespoke solutions.

Director training outcome

Simple AI workflows around real agency operations.

The training is about giving teams simple AI workflows through connected apps, schedulers, templates, prompt packs, source-of-truth sheets, human review, and visible audit logs.

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Connected apps

Scheduled tasks

Prompt packs

Human review and audit trail