Higher education · course advice & customisation

A leading Australian provider of online higher education.

Clearer course explanations and study options tailored to prospective students.

Advisers who used to repeat the same unit explanations now spend more time on conversations that need their judgement.

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At a glance

What improved

Satisfaction & enquiry experience

The quality of first replies

Response time

24+ hrs → under 1 min

On routine course questions

After-hours coverage

70–80%

Of off-hours enquiries handled by next morning

Adviser time

25–40% freed

For the cases that need real judgement

The task that needed help

Prospective students asked the questions that actually decide enrolments. “What does this unit actually teach me?” “How does it set me up for the one after?” “Which of these three units gives me the strongest base in data analytics, and what are the trade-offs?” “I’ve got a diploma from ten years ago and a full-time job. Can I make this work?”

The questions deserved depth. The adviser team was answering hundreds of these questions a week, often under time pressure and after hours. The replies that went out were honest but uneven. Some prospective students got a paragraph explaining how the unit fitted their study plan; others got a sentence and a catalogue link. The detail in the first reply depended on how busy the adviser was that morning.

The AI employee’s role

A course advice assistant.

Prepares initial course explanations and tailored study options. No formal credit assessment, no admission decisions, no current-student support.

Tools and information

Full course catalogue, including unit syllabi and learning outcomes
Prerequisite and pathway maps across partner universities
Career-pathway documents
Previous enquiries and customer relationship management (CRM) records
Examples of good adviser replies, to guide tone and wording

What it prepares

Read the prospective student’s goal, previous study, and limits on time, study mode, and budget
Explain each relevant unit: what it teaches, which skills it builds, and how it connects to the next unit
Suggest one to three study options and explain the trade-offs: fastest completion, strongest qualifications, or easiest to fit around work
Flag questions about eligibility, study credit, or recognition of prior learning (RPL) for a named adviser
Give the adviser the details and a draft reply to review

Improvements after the first week

The first replies were too long: six paragraphs on every unit when the prospective student needed two on the right ones. Detailed answers were useful, but only when they answered the actual question.

The rule changed. Start with a short summary of each unit and explain why it fits the student’s goal. Then offer a “want more on this one?” link for extra detail. Reply quality scores improved the same week.

What people decide

Formal assessment of recognition of prior learning (RPL) and study credit
Admission and scholarship conversations
Career-change consultations where a prospective student needs personal advice
Hardship, fee assistance, and special access cases
The judgement call on whether a degree is the right answer at all

What the AI employee prepares

Understanding the prospective student’s question and circumstances
Explaining units and pathways at the right level, not too shallow, not too long
Proposing tailored study options with the trade-offs explained
Passing eligibility and study-credit questions to the right adviser
Recording the enquiry, suggested study options, and the student’s limits on time, study mode, and budget

For context, published reports of similar AI systems in higher education describe these ranges: response times measured in seconds for routine enquiries, 70–80% of after-hours questions cleared before the next morning, and 25–40% of adviser time freed for career changes, recognition of prior learning, and hardship enquiries.

What the AI employee does not do

Confirm study credit or recognition of prior learning. That formal assessment comes from a human.
Promise an admission outcome. The employee can describe pathways; admission belongs to the institution.
Quote fee assistance, scholarship, or special-access eligibility.
Touch current-student support. Different queue, different rules.
Send anything without review. Every draft pauses for an adviser.

What the team does now

Advisers now spend more time on conversations that need them: career changers deciding whether a degree is the right answer, prospective students with complex previous study, and people who need guidance on recognition of prior learning. Routine course explanations arrive sorted and drafted at the right level of detail. Advisers can focus on the decisions behind the enquiry.

An example from the work

Enquiry #6022, career-change to data analytics, prior diploma 2014, working full-time. Drafted three pathways (fastest / most credentialled / working-friendly). Each unit explained at summary depth with expand-on-request. RPL signal on the diploma, flagged to Daniel, holding off send.

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