Getting started with AI – a guide for business owners
When businesses start exploring the potential of Artificial Intelligence (AI) it can be exciting, daunting, scary and invigorating at the same time. AI is revolutionising and transforming businesses, supporting growth, reducing costs, and generally hitting efficiency goals.
There is a dangerous side to AI that does not get heard amongst all the buzz and hype. While we believe AI truly can help businesses, there is fine line between personal and business use of AI when it comes to legislative, ethical, and security risks. These are well known amongst the AI community - less so with most end users.
Business owners, in particular, must understand AI risk. This will allow commercial benefits to be realised without threatening a business’s risk profile.
To simplify what AI can be used for and to guide business owners on the journey, think of the inputs and outputs:
Text
Images
Videos
Voice
Numbers
The most common is text, where you type a question into an AI tool and essentially have a conversation, you could generate a story, report, or funny email. Images and videos are another two types of content to INPUT into AI as well as get outputs. You can ask AI to enhance an old photo or to recognise who is walking into your office. AI could create a flyer or video ad showcasing your latest product or generate a message from the CEO. AI can answer your phone, analyse your finances and much more.
With the emergence of agentic AI, the opportunities explode exponentially again. While some businesses are still reviewing, adopting and exploring, others are automating tasks and removing the human in the loop where appropriate to do so.
Today, our client and Partner network see the challenge as 'how should I go about using AI' rather than 'should I use AI' for my business. If you think of AI as process automation, most businesses are already using it. Here is simple guide for business owners who are not sure where to start.
Explore
Do
Ask AI questions about various subjects and topics. Ask more, delve deeper, and see if it can help you do things quicker. Learn how to talk to an AI (it's not that different to talking to a human). Ask what AI can do to understand its capability. Explore various tools to see which suit you best.
Do not
Share personal information, names, addresses, habits, private data, or reports. Just last week millions of assumed 'private' AI conversations entered the public domain. Business plans, medical concerns, family details, and travel plans were briefly accessible.
It's easy to explore AI without risk. Just don't share anything you wouldn't in a room full of people. AI can make mistakes, so starting with familiar topics is best.
Testing capability
Do
Start with topics you know well. Ask AI for information, trends and insights about familiar subjects. You can check both speed and quality of output. Ask AI to argue against its last suggestion and judge the system's capability. Create your own daily newsletter written to your preferred length and tone.
Do not
Assume AI 'knows' you or has context about your questions. This is where risks form. For better responses, you must give more context. Do not share confidential information until you understand and accept the risks.
To understand capability you'll eventually need to share private information. However, you could use sample data to simulate real-life challenges for testing. Manually cross-checking AI's work gives deeper understanding of effective use.
Plan
Do
For businesses wanting to adopt AI, having a plan is vital. Understand the variety of tools available and related policies. Paid subscriptions don't guarantee 'privacy'. Most businesses can leverage AI for efficiency - speeding processes, reducing errors, and boosting ideation.
Do not
Assume AI can solve everything. If underlying processes are flawed or AI fixes non-issues, commercial benefits won't be realised. Risk assessment is crucial. Businesses must trust AI output to gain advantages. Double-checking every output adds inefficiencies.
Once you know where to deploy AI, start using it for commercial benefit within accepted risk categories. Some plans (Instagram posts) are quick and low-risk. Others (automatically ordering restaurant ingredients based on weather) need more consideration.
Agentic AI
In short – agentic AI – or AI agents, take action-based outputs. Rather than simply presenting information to the user, they have been set up to automatically initiate tasks. For many businesses this is not new at all – it just has a new name. Process automation has been around for decades, as has programmatic advertising. The main change now is the data processing speed. Information is analysed faster, insights generated almost instantly, and action taken in moments. Results are analysed and new actions are deployed round the clock. Some examples of using AI as an agent for tasks:
Business and Enterprise
Robotic Process Automation (RPA) - Software bots handling invoice processing, data entry, and compliance reporting autonomously
Customer service agents - AI systems resolving support tickets by accessing knowledge bases and updating customer records
Finance and Trading
Algorithmic trading bots - Systems executing millions of daily trades based on market analysis and risk assessment
Fraud detection agents - AI monitoring transactions real-time, flagging suspicious activity and blocking fraudulent payments
Healthcare
Drug discovery platforms - AI agents designing molecular compounds, predicting interactions, and optimising clinical trials
Radiology assistants - Systems analysing medical images, flagging abnormalities, and prioritising urgent cases
Technology and Software
Code generation assistants - Tools like GitHub Copilot writing code, debugging programs, and suggesting optimisations
Infrastructure management - Systems automatically scaling cloud resources, patching vulnerabilities, and optimising performance
Transportation and Logistics
Route optimisation systems - AI planning delivery routes, adjusting for traffic, and coordinating fleet movements
Warehouse robots - Autonomous systems in fulfillment centres picking, packing, and sorting packages
Marketing and Sales
Programmatic advertising - AI agents bidding on ad placements real-time, targeting audiences across websites
Dynamic pricing engines - Systems used by airlines and e-commerce adjusting prices based on demand and competition
Smart Home and IoT (Internet of Things)
Home automation systems - AI learning household patterns and automatically adjusting temperature, lighting, and security based on occupancy
When AI goes bad: A few notable examples of the challenges businesses have come across recently
Australian Retail Facial Recognition Privacy Breaches (2024) Facial recognition trials in Australian retail are raising privacy and bias concerns, particularly regarding inaccuracies in identifying people-of-colour and impacts on indigenous communities.
Medical AI System Failures in Australian Hospitals (2024) The Epic Sepsis Model missed 67% of septic patients and showed no improvement in outcomes across 15 hospitals. These international failures have made Australian healthcare providers cautious about AI adoption.
Australian Government Workplace AI Governance Failures (2024) Only 18% of AI-adopting organisations have policies within six months of implementation, while 38% have no policy plans. Australia's 35% AI usage ranks among the lowest in Asia-Pacific due to poor governance.
Air Canada Loses Legal Case Over Chatbot's False Information (2024) Air Canada was ordered to pay compensation after its chatbot provided incorrect bereavement fare information. This became the first known case of company liability for AI chatbot misinformation.
NYC AI Chatbot Tells Businesses to Break the Law (2024) New York City's business assistance chatbot repeatedly gave illegal advice, including telling businesses they could steal tips and discriminate against tenants. The chatbot remained online despite criticism.
Multiple Lawyers Sanctioned for ChatGPT's Fake Legal Citations (2023-2024) Several lawyers were sanctioned for submitting fake case citations generated by ChatGPT. Notable cases included New York lawyers fined $5,000 for six non-existent cases.
DPD Chatbot Goes Rogue, Swears and Writes Poems About Company (2024) DPD's chatbot began swearing at customers and writing poems calling the company "useless" after a system update. The feature was immediately disabled.
Conclusions
AI offers significant business potential but requires a strategic, risk-aware approach. Business owners should follow a three-phase journey: first explore AI capabilities using general topics without sharing sensitive data, then test the technology on familiar subjects to assess quality and reliability and finally plan targeted implementations within acceptable risk parameters.
While AI can enhance efficiency, reduce costs, and accelerate processes and data analysis, success depends on understanding both capabilities and limitations. The key is starting cautiously, avoid including confidential information initially. Gradually scale usage as competence and trust develops. Not every business process needs AI, focus on areas where automation genuinely adds value rather than trying to solve problems that don't exist. With proper planning and risk assessment, businesses can harness AI's commercial benefits while protecting their security and operational integrity.
Business owners need to take their business to the next level to succeed in a competitive market and like any new technology roll-out seek appropriate support to realise vision.
Author:
Mitesh Patel
Partner, nem Australasia
August 2025