AI In Australian Recruitment: What's Actually Working Right Now

AI is quickly becoming part of the recruitment operating model, but the agencies seeing the greatest value are not simply adding more technology. They are changing how work gets done.

In this TRN World session, James Osborne, Founder of The Recruitment Network, and Josh O'Loughlin of Tech2Rec explored how recruitment businesses are using AI in practice, from automating administration and improving CRM data to identifying new business opportunities and building additional revenue streams. Their message was consistent: AI works best when it is introduced in the right order and used to strengthen, rather than replace, the human side of recruitment.

The opportunity is bigger than automation

Recruitment businesses are facing pressure from multiple directions. Economic conditions, changing workforce behaviour, greater competition, regulation and technology are all reshaping the market.

That does not simply create risk. It also creates an opportunity to rethink the agency operating model.

Some recruitment businesses are already doing this successfully. They are running leaner teams, generating higher output per recruiter, using offshore support more effectively and introducing AI agents to handle clearly defined tasks.

The important point is that these businesses are not succeeding because they have adopted one particular AI tool. They have redesigned the way their businesses operate.

People remain central, but technology is being used to remove the work that does not require human judgement.

Use AI to give recruiters more time with people

One of the strongest opportunities for AI is also one of the simplest.

Recruiters still spend a significant amount of time on administrative work. Notes, CRM updates, searching for information, formatting CVs, sourcing data and organising follow-ups all consume time that could otherwise be spent speaking with clients and candidates.

The goal should be to change that balance.

When AI and automation take responsibility for more repetitive work, recruiters can spend more of their day in meetings, on calls, networking, advising clients and building relationships.

In that sense, good AI adoption should make recruitment more human, not less.

Start with your CRM, not another new tool

Before adding new technology, recruitment leaders should examine what they already have.

CRM data is the foundation for almost every useful AI application in recruitment. If that data is poor, AI simply allows the business to act on poor information more quickly.

One agency reviewed during the session had made 421 placements over an 18-month period. Most appeared to have come from LinkedIn or job boards. However, further analysis showed that 285 of those candidates were already sitting in the CRM.

The agency was therefore spending time and money searching externally for talent it already had.

This is why CRM optimisation needs to come before more ambitious AI projects.

Recruitment businesses should understand whether their records are complete, whether contact information remains accurate, whether conversations are being captured consistently and whether consultants genuinely trust the database.

AI cannot compensate for foundations that are not working.

Automate administration before chasing advanced AI

A practical implementation roadmap starts with repetitive administrative work.

Call and meeting notes are an obvious example. Recording, transcribing and summarising conversations automatically can improve CRM data while removing manual work from consultants.

The value is not simply the time saved. Automated capture can preserve information that might otherwise disappear because a recruiter did not consider it important enough to include in their notes at the time.

The same principle applies to CV formatting. AI can convert incoming CVs into a standard agency template without consultants repeatedly editing documents by hand.

CRM maintenance is another priority. Agencies can conduct an initial data clean to deal with historical problems, then introduce ongoing processes that identify duplicates, update contact records and enrich data as circumstances change.

The important word is consistency. Automation only creates a strong foundation when it becomes the default way the business operates.

Better data makes AI-assisted business development possible

Once the underlying data is reliable, agencies can move into more commercially valuable applications.

AI can monitor the market for job opportunities, identify relevant hiring managers and surface information into the CRM for consultants to act on.

It can also help agencies move earlier in the sales cycle.

Traditional recruitment business development often begins when a vacancy has already been advertised. By that point, multiple recruiters may already be approaching the same organisation.

A stronger approach is to monitor the events that tend to happen before recruitment begins.

An organisation receiving investment, opening an office or expanding into a new location may indicate future hiring demand.

AI agents can monitor those signals continuously.

For example, an agent could identify a company that has signed a lease for significantly more office space than its current employee numbers appear to require. That difference may indicate likely headcount growth.

Instead of waiting for a vacancy to become public, the recruiter has an opportunity to begin a relevant conversation earlier.

Keep people in control of outreach

AI can also support personalised business development, but this is an area where human oversight matters.

If the CRM contains useful conversation history and accurate information, AI can draft outreach based on genuine context.

The safer model is straightforward: AI drafts, the recruiter reviews and the recruiter decides whether to send.

Fully automated outreach creates unnecessary risk. Incorrect information, invented details or language that does not sound natural can reach a client before anyone in the agency has seen it.

The review may only take seconds, but it protects the quality of the client experience.

Agencies can also improve outreach without asking AI to write anything. A well designed process that automatically creates follow-up tasks, triggers reminders and keeps consultants working to a defined cadence can solve many of the same consistency problems.

AI and automation are related, but they are not the same thing.

Build AI assistants only after the foundations are secure

The next stage is to connect an AI assistant across the systems recruiters already use.

An assistant connected to email, CRM, calendar and other business applications can help employees retrieve information without manually searching through multiple systems.

Instead of spending 10 minutes looking through notes and messages, a consultant can ask a question and receive the relevant information immediately.

This becomes particularly powerful when the assistant can also take controlled actions, such as preparing follow-up emails or generating daily briefings.

However, integrations also create risk.

Connecting an AI assistant to business systems without carefully reviewing permissions can unintentionally expose sensitive information.

Before doing this, agencies need clear controls around what AI can see, what it can change and what actions it is permitted to take.

Employees should also be using managed business accounts rather than individually created personal AI accounts that the company cannot properly monitor or control.

AI readiness includes security.

Move towards workflows that run in the background

The more advanced stage is where AI begins responding automatically to business events.

Imagine a consultant completing a candidate interview.

The conversation is transcribed and added to the CRM. The candidate is matched against relevant vacancies based on what was actually discussed. Previous clients with similar hiring requirements are identified. Suitable outreach is prepared for the recruiter to review.

The consultant does not need to trigger each individual task.

This is where recruitment can begin to operate very differently. Consultants spend more time making judgements, building trust, negotiating and speaking with people while systems handle the activity that follows those conversations.

For many agencies, this should not be the starting point. It is what becomes possible when the earlier stages are already working.

AI can support new products as well as productivity

The commercial opportunity goes beyond improving recruiter efficiency.

Clients increasingly expect agencies to provide more than access to candidates. They are looking for market intelligence, workforce insight, salary information, specialist advice and a stronger understanding of talent availability.

That creates an opportunity for agencies to occupy the space between traditional recruitment supply and talent consultancy.

Services might include market mapping, benchmarking, workforce planning, hiring strategy, embedded solutions or other advisory projects.

AI can help agencies gather and process the information needed to deliver these services efficiently.

Some recruitment businesses are taking this further by turning advisory services into subscription-based platforms, creating recurring revenue alongside traditional placement income.

Others are finding ways to generate value from existing candidate assets. A shortlisted candidate who does not secure one role does not have to disappear back into the CRM. An anonymised, curated talent platform can create another way for clients to access pre-qualified candidates and another potential revenue stream for the agency.

Choose a platform and build capability around it

There is understandable debate about whether recruitment businesses should use ChatGPT, Claude, Microsoft 365 Copilot or another platform.

The more important decision is how the technology is being used.

Different platforms will continue to introduce new features and move ahead of one another. Constantly changing tools can become a distraction.

Recruitment leaders need a suitable platform that works with their systems and requirements, followed by the discipline to build processes, knowledge and internal capability around it.

The technology will continue evolving. The operating principles are more durable.

The right sequence matters

The strongest AI strategies in recruitment do not begin with ambitious autonomous agents.

They begin with the basics.

Clean the data. Use the CRM properly. Automate repetitive administration. Capture conversations consistently. Introduce AI assistants with sensible controls. Then begin building workflows that operate more independently.

From there, AI can support a broader change in the recruitment business itself, helping agencies identify opportunities earlier, deliver more value to clients and develop new sources of revenue.

The objective is not to replace recruiters.

It is to build a business in which recruiters spend far more of their time doing the work that clients and candidates actually value.

Host: James Osborne - Founder, The Recruitment Network

businessSpeaker: Josh O'Loughlin - Managing Director, Tech2Rec