Ways using AI tools can benefit your business
Automating operational tasks, such as admin work, invoicing, booking jobs and following up customers, using AI tools can help your business grow – because it frees up your time to focus on getting that next quote done or time to think about opportunities for growth.
AI Is super useful for admin tasks, marketing, creating quotes, and handling customer enquiries. AI can help you respond faster, reduce having to do things over, and create more consistent results.
We asked 500 Kiwi business owners how AI has helped them, and this is what we found out:
- 42% said AI gave them more time for important tasks
- 38% said it improved their work‑life balance
The AI Forum New Zealand found that:
- 91% reported improved efficiency
- 77% saw cost savings
- 55% saw new career opportunities
With a bit of learning up front, AI can help streamline your day‑to‑day work and improve the quality of your work.
How AI can help
Every business is different, so have a think about what areas in your business AI tools can add the most value.
AI tools can often help you to:
- write and edit faster – emails, social media posts, job adverts, proposals
- summarise and re‑format – meeting notes, documents, checklists
- spot patterns – find themes in sales figures or customer feedback
- create consistent first drafts – content you can quickly review
- create simple automations – move information between systems to reduce manual work.
Pick one area, try a small task, review the result, then scale what works.
Where to trial AI in your business
If you’re thinking of trialing AI in your business, it's important to consider where it could have the most impact.
Start by identifying areas of your business that are less complex, where you can test AI tools at no or low cost. Focus on tasks where results can be checked by a person. This is called ‘Human in The Loop’ (HITL).
This method helps you start small to gain confidence and momentum, giving you a solid foundation to build on. Once you’ve successfully trialled AI on a smaller scale, you can look for larger, strategic opportunities across your business.
You could use AI to:
- summarise invoices or receipts
- explore trends in a spreadsheet
- segment customers
- segment content for different customer types.
Start where risks are low and reviewing results is easy:
- good first tasks (low risk) - rewrite an email, polish a job advert, turn notes into a checklist
- next steps (medium risk) - draft newsletter content, summarise long documents, theme customer feedback
- advanced (higher risk) - publishing website copy, sending customer emails or messages automatically, changing prices or updating customer records.
For higher risk tasks, always check that the AI tool offers strong security and data-protection controls, and set them up properly. Make sure a person checks the output before you send or publish.
Preform a quick Return on Investment (ROI) check
Before you commit time or budget, ask yourself about:
- Time saved – will this task save 30+ minutes a week?
- Ease of review – can a person check the result fast?
- Risk level – is the impact of a mistake low?
- Frequency – is this task frequent enough to matter?
- Value add – does the draft output move you closer to a final product?
If most of your answers to these questions are 'yes', then the task is a good one to test.
Be careful with personal or sensitive information
There are some basic finance, data and customer segmentation tasks that can be good use cases for trialling AI.
Whether you’re using a free AI tool or paying for one, always check:
- how your inputs are used, where they’re stored, and if they’re used to train the model
- what data controls are available and if you can turn off data retention or delete your history
- if the provider offers enterprise-grade privacy settings
- if the tool meets your organisation’s security and compliance requirements.
If you need to use personal customer details or other sensitive data, choose a secure AI tool that provides strong privacy protections and robust data-management controls.
AI assistants vs agents
Assistants draft or summarise information. They’re ideal for quick wins like writing, re‑formatting, and research support.
However, agents can also take actions across systems on your behalf - for example, sending emails, changing records, or moving files. These features are becoming more common in everyday business tools, which means automation that once required specialised software is now much more accessible to small businesses.
This can save time, but it also raises the level of risk – when a tool can act within your systems you’ll need clear limits, low system permissions, and human oversight.
Consider which approach is right for your business and begin with assistant‑style tasks. If you trial an agent start with a small pilot, keep cross-system permissions low, and always require a person to confirm important actions.
Understand the risks involved
Like any new tool, technology or business venture, there are challenges you’ll need to navigate when using AI. Think about what these may be for your business and how you’ll deal with them up front, so they don’t become barriers to your progress.
AI is powerful, but there are risks to manage.
Focus on:
- accuracy: AI can be wrong or over‑confident - check facts, numbers, and names.
- privacy and data sharing: keep sensitive data out of consumer tools, and opt for business plans and settings.
- tone and brand: adjust prompts and review drafts before anything is shared publicly.
- shadow AI: avoid unapproved tools – set clear rules and provide safe tool options.
Find out how to mitigate risks through simple and effective processes, by visiting our web page.
Before you start
If you’re ready to test AI in your business, tick these off before you test:
- One small test case with clear success criteria.
- Non‑sensitive sample data for testing.
- A general‑purpose tool you already have access to.
- A person responsible for reviewing and approving the results.
- A simple way to save results and note lessons learned.
Once you’ve done the test, and you’re happy with the result, you’ll be ready to implement on a bigger scale.
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