The pattern we keep seeing.
A leader puts the whole team through a foundations workshop and waits. Three weeks later, sales reps are using AI to write LinkedIn posts and ops is still doing the Monday status update by hand. Generic capability doesn't move function metrics. Function-level capability does.
Generic training doesn't move a function's day-to-day.
Sales reps don't need to write better limericks. They need their CRM updated and their follow-ups drafted in the rep's voice.
The bottleneck is rarely the obvious task.
Most teams point at the junior; the real friction is usually the senior review step nobody redesigned.
AI capability is sitting in one person's head.
Your most AI-fluent rep has a private prompt list. When they leave, capability resets, and the team has to rebuild from zero.
What is Role-Based AI Workflow Training?
Function-by-function AI workshops that rebuild your team's most-repeated workflow with AI, so the work runs faster, looks the same every time, and doesn't depend on one person.
Foundations get everyone speaking the same language. Role-based training is where the hours come back. Pick the function. We rebuild its slowest weekly workflow with AI in the room, on the function's real work, with the function's real stack.
Edison AI runs function-specific AI training for sales, marketing, operations, finance, admin and customer support teams across Australia. Each engagement rebuilds the function's most time-consuming workflow with AI, end-to-end, in a 3–4 hour workshop. Deliverables include a 15–25 prompt library, a one-page workflow standard owned by the function lead, and a 60-day adoption check-in.
The shifts you can't postpone.
Three shifts function leaders can't postpone, and the function that productises its workflow first is the one that compounds first.
- 01
Function leaders are now expected to have an AI answer.
Boards and owners are asking 'what's your function's AI roadmap?' The right answer is workflow-level, not tool-level.
- 02
Hours-per-task is the new productivity metric.
It's measurable, defensible, and exactly what AI moves. Vague 'productivity' lifts have become unconvincing; specific hours-back numbers haven't.
- 03
The function that productises first wins onboarding.
A rebuilt workflow becomes a training asset for every new hire after. Three months in, your fastest-onboarding function will be the one you trained first.
What you get.
- 01
45-minute function diagnostic with the function lead
- 02
Custom 3–4 hour workshop on the team's real work
- 03
15–25 production prompts tailored to the function's stack
- 04
One-page workflow standard the function lead owns
- 05
Manager review protocol (30-minute separate session)
- 06
60-day adoption check-in with written recommendation
Where this shows up.
Sales
Pain
CRM admin, follow-up writing, proposal drafting eat selling hours.
Future
AI drafts CRM notes from call transcripts, follow-ups in the rep's voice and proposal v0 from a structured brief.
Outcome
40% time off admin, faster pipeline movement, more consistent house tone.
Operations
Pain
Status reporting, supplier emails and internal handoffs leak hours every week.
Future
AI summarises weekly status from records, drafts supplier comms and populates handoff templates.
Outcome
Less Monday-morning scramble and a more even operating rhythm.
Marketing
Pain
Blank-page tax, channel-specific rewriting, brief-to-asset cycle.
Future
AI produces first drafts against a written house style, reformats one asset across channels and turns a brief into copy + headline options.
Outcome
More output without more headcount.
Customer support
Pain
Ticket triage, reply drafting and tone consistency.
Future
AI suggests replies in your tone, classifies and routes tickets, and flags risk language.
Outcome
Shorter response times, fewer escalations, steadier brand voice.
Finance
Pain
Month-end commentary, AP/AR queries and variance explanations.
Future
AI drafts commentary from report data, answers common AP queries and explains variances against budget in plain language.
Outcome
Faster close, fewer 'we'll send the commentary tomorrow' emails.
Admin / EA
Pain
Meeting notes, inbox triage, scheduling-related comms.
Future
AI captures notes and action items, drafts replies and surfaces priorities and conflicts.
Outcome
Senior PA leverage on junior PA hours.
The engagement.
- Step 01
Diagnose
45-minute working session with the function lead to pick the one workflow worth rebuilding. Measured on time, error or revenue impact.
- Step 02
Design
Workshop built around that workflow. Prompts, templates and review protocol drafted before the team arrives.
- Step 03
Deploy
A live 3–4 hour workshop where the workflow gets rebuilt with AI, end-to-end, on the function's real work.
- Step 04
Embed
Written workflow standard for the function lead. Manager review protocol. 60-day adoption check measuring time-on-workflow before and after.
What changes.
40–60%
Time reduction on the targeted workflow.
Measured on the first 10 runs post-training. The diagnostic defines the baseline so the lift is honest, not theatrical.
15–25
Production prompts the function owns.
Built around the function's actual stack. HubSpot, Xero, Office 365, Notion, whatever sits at the centre of how they work today.
One written workflow standard per function.
Survives a staff change. The function lead inherits the standard; new hires inherit the workflow.
Who this works for.
This is for you if…
- You can name the function that's the bottleneck without thinking
- Your team has done a foundations workshop or is already AI-fluent
- You want function-level adoption you can measure
- The function lead is willing to commit half a day plus a Monday review
- You'd rather rebuild one workflow properly than skim ten
- You're preparing for AI implementation and want capability before tools land
Not the right fit yet if…
- Your team hasn't done any AI training and tool access is uneven
- You're not sure which workflow to target (start with an AI Readiness Audit)
- You want generic capability rather than function-specific output
How this compares.
Five common ways teams try to lift function-specific AI capability. One of them ships the outcome.
Internal champion runs informal sessions
- Gives
- Cheap, organic, low overhead
- Falls short
- Inconsistent, capability walks if the champion leaves
- Edison difference
- Written workflow standard the business owns
Generic LinkedIn Learning module
- Gives
- Affordable, on-demand
- Falls short
- No real workflow rebuilt; theoretical
- Edison difference
- Workshop rebuilds the function's real workflow live
Vendor-led training (HubSpot, Salesforce)
- Gives
- Tool-specific depth
- Falls short
- Skewed to the vendor's tool, not your operating reality
- Edison difference
- Tool-agnostic. Fits your stack as it is
Big consultancy 'AI for sales' programme
- Gives
- Polished, brand-credible
- Falls short
- Six figures, off-the-shelf, junior handover
- Edison difference
- Boutique, fixed-quote, function-specific
Wait until everyone's done foundations
- Gives
- Logical sequencing
- Falls short
- Foundations alone rarely shifts function metrics
- Edison difference
- We sequence both. Foundations then role-based
Edison AI
Operator-grade, founder-led, fixed quote. Built around your real stack and workflows , not a binder, a brochure, or a six-figure off-the-shelf programme.
What buyers ask first.
“My function lead is too busy for a workshop.”
That's why we run the workshop on their team. The function lead commits to a 45-minute diagnostic and a 30-minute review session, not the full half-day.
“Our processes aren't documented.”
Most aren't. We document the workflow in the room as we rebuild it. You get the SOP as a by-product, not as a precondition.
“What if AI gets the work wrong?”
Every workflow includes a human review step. The point isn't to remove judgement. It's to remove the first 60% of typing.
Common questions.
Which functions do you train?
Sales, marketing, operations, customer support, finance, executive admin and HR most commonly. Also legal, procurement and L&D on request.
How long is each role workshop?
3–4 hours of live work, plus a 45-minute diagnostic in advance and a 30-minute manager session after.
How much does function-specific AI training cost in Australia?
$6,500–$15,000 plus GST per function depending on team size and workflow complexity. Multi-function packages drop the per-function rate.
Do we need to have done foundations first?
Strongly preferred for teams under 50% AI adoption. Skippable if the function is already AI-fluent on the basics.
Can you train two functions in parallel?
Yes, with two facilitators. Common inside an AI Adoption Programme.
How is success measured?
Time-on-workflow before vs after, function lead satisfaction, and adoption rate at the 60-day check-in, all defined in the diagnostic.
What if the workflow we choose turns out to be wrong?
The diagnostic exists to prevent that. If the workshop reveals a deeper issue, we name it and recommend the right next move rather than ploughing on.
What tools work with this training?
Tool-agnostic. We've trained on HubSpot, Salesforce, Pipedrive, Xero, MYOB, NetSuite, Zendesk, Intercom, ClickUp, Notion, Office 365 and Google Workspace.
The same service creates different leverage depending on your industry.
- Real Estate & PropertyMaintenance, owner comms, inspections, portfolio reporting. Without the admin tax.
- Education & TrainingEnrolment, curriculum, AI policy, staff capability. Done responsibly.
- Trades & Field ServicesThe field-to-office gap, finally closed. Quotes, schedules, jobs, customers, in sync.
- Professional ServicesProposals, knowledge, client comms. AI that respects expert judgement.
- Retail & EcommerceSupport, content, inventory, performance. The operating side of D2C.
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