Yesterday we ran a session for Golf Management Australia’s BMI leadership program on a topic many clubs are curious about but unsure how to approach: AI in club operations.
The conversation in the room was familiar.
Most managers had experimented with AI tools. Some had staff already trying them in day-to-day work. Very few had a shared structure for how the club should use them safely and consistently.
That pattern mirrors what we see across many industries.
Most organisations experimenting with AI don’t see measurable productivity improvements at first. Not because the technology doesn’t work but because the organisation never changes how work is actually done.
Golf clubs are no different.
Clubs run lean.
A typical GM or operations manager handles member communications, event enquiries, board reporting, staff issues, marketing updates, and policies and procedures often in the same morning.
Meanwhile, member expectations for fast responses are rising, inbox volume keeps increasing, and administrative work keeps expanding.
AI can’t solve all of that. But it can remove a meaningful amount of repetitive drafting, summarising and formatting work that absorbs time across a lean team.
The most effective use cases are rarely complex. They’re usually tasks your team already does every day.
In practice, the pressure usually shows up in a few familiar areas: repetitive member and guest enquiries, event and function coordination, board and management reporting, policy and SOP documentation, and the constant communication load that comes with small teams and rising expectations.
Many clubs receive dozens of similar enquiries each week membership questions, visitor bookings, corporate day enquiries. Each response often starts from a blank page. AI can draft responses quickly while maintaining tone and structure. One well-built prompt, used consistently, can remove hours of repetitive writing from your membership team’s week.
Event coordination produces constant communication: supplier emails, confirmations, run sheets, follow-ups. AI tools can generate structured drafts that staff refine rather than writing from scratch.
Preparing board updates can take hours. AI tools can help summarise notes, structure reports, and draft commentary for review. Human judgement still sits at the centre — but the drafting workload becomes much lighter.
Clubs constantly update governance documents. AI can draft, reformat, and summarise policy documents, reducing the time your GM or operations manager spends on documents that are functional rather than strategic.
When used this way, AI becomes a practical desk tool embedded in daily work, rather than another vague initiative that depends on one enthusiastic person.
The clubs seeing results are not replacing people with AI. They are using what we call Human at the Helm.
Humans remain responsible for judgement, relationships, decisions, and exceptions. AI handles the repetitive tasks: drafting, summarising, structuring text, identifying patterns.
Even small time savings compound quickly across a team.
If five staff save just fifteen minutes a day on writing or formatting tasks, that can add up to hundreds of hours per year across the organisation.
That question deserves a practical answer. Not hype. A clear plan: where AI helps, what guardrails exist, and what success looks like. The goal is not technology adoption. The goal is operational capability.
Small, visible wins build confidence quickly and create momentum for broader adoption.
The best starting point is usually not a big AI project. It is a clear plan.
For some clubs, that means identifying one or two high-friction workflows and putting a simple, structured starting point around them. For others, it means stepping back to assess current maturity, priorities, risks and where AI fits across the club more broadly.
Dovetail helps service-based businesses move from ad hoc AI use to structured operational capability through Strategic Implementation Plans, Activation Plans, right-sized governance, workflow-led adoption support, and practical training that builds shared AI fluency.
It is highly relevant for clubs because many club workflows are repetitive, communication-heavy and time-sensitive. Small teams and rising expectations make these environments well suited to practical AI support, especially in admin, reporting, communications and documentation.
Usually a repetitive writing or summarising task that already happens frequently. Member enquiries, board reporting support, budgeting and financial reporting, event communications and SOP drafting are often strong starting points.
Not always. Many do not need a heavy strategy process first. They do need clarity on where AI fits, what the first priority workflows are, and what simple guardrails should apply. For lower-maturity teams, a lighter activation-style plan is often the best starting point.
No. The practical starting point is often workflow-based rather than system-based. Many useful first wins can be achieved with existing tools and a better operating approach.
The main risk is inconsistency. Outputs vary, boundaries are unclear, and leaders lose confidence because results are hard to trust or scale. Informal use without shared rules or review creates rework and weakens momentum.
Most clubs do not need heavy AI compliance from day one. They do need simple, practical guardrails matched to current maturity. That usually includes clear usage boundaries, review expectations, approved workflow types, and shared understanding of what should not be uploaded or relied on without checking.
By choosing the right workflows, defining what good looks like, setting limits, and making sure review is proportionate. If AI drafts still require full rewrites every time, the club has not yet designed the workflow properly. The aim is to reduce friction, not shift it upward.
It means the team develops a common baseline for how AI is used in the club. Not everyone needs the same depth, but there is enough shared understanding that wins can be repeated, improved and used safely across roles. That is what turns isolated experimentation into operational capability.
A good start usually includes identifying the highest-friction workflows, agreeing simple guardrails, training the relevant people on those workflows, piloting one or two quick wins, and making the early results visible to leadership.
No. Clubs make the pattern easy to see because the workflows are so visible, but the same issue appears across service businesses: lots of experimentation, uneven usage, no shared operating model, and too little attention to the workflows where AI should first prove itself
