AI can write an email in seconds, summarise a 20-page report, analyse complex information and even create a presentation before your coffee has had time to cool.
Just because AI can do something doesn’t mean it should – or that the result will be good, accurate, or even necessary in the first place.
As AI becomes an increasingly familiar part of our working lives, much of the conversation focuses on how we use it, what it can do, and where its limitations lie. What can we automate? How can we work more efficiently? And, perhaps most importantly, how do we use it responsibly?
Imagine you have a report to prepare. You could ask an AI tool to summarise the source material, generate some key points and turn them into a first draft. It might take seconds.
But then you start checking the details. One point is missing, another has been taken out of context, and something else is inaccurate. You’re left wondering where a particular statement came from. Before long, you’re rewriting sections, correcting errors, and adding information AI didn’t include.
Suddenly, the time you thought you were saving is being spent checking and correcting the AI-generated content.
The problem isn’t necessarily the technology. It’s how we approached the task. Using AI effectively requires more than knowing how to open a tool and write a prompt. It requires judgement, knowledge, and skills.
Is AI the right tool for this task? What context does it need to produce a useful result? What information should I avoid sharing? How do I verify the accuracy of its output? And, perhaps most importantly, who is responsible for the final result?
This last question is easy to overlook.
AI can generate an answer, but it doesn’t take responsibility for what happens next. The person using it still needs to check the information, consider the context and decide whether the output is appropriate. If the information is inaccurate, sensitive or misleading, using AI doesn’t remove our responsibility for the consequences.
This becomes particularly important when AI is used to handle confidential information, personal data, or information that could influence decisions. Knowing what not to share can be just as important as knowing what to ask. Understanding the limitations of a tool can be just as valuable as knowing its capabilities.
This is why becoming AI-capable is about more than adopting the latest tool or learning new features. It’s about developing the knowledge and skills to recognise where AI can add value, where human oversight is necessary, and where using AI may create more problems than it solves.
As AI continues to evolve, the ability to assess, question and make decisions around its use is likely to become increasingly valuable across industries and roles.
The future of work won’t necessarily belong to people who know the most AI tools, but to those who know how to use them effectively, when to rely on them, and when human judgement needs to take the lead. AI capability is about more than using technology – it’s about applying AI effectively, making informed decisions, and taking responsibility for outcomes.
La Trobe University and the Australian Centre for AI in Medical Innovation (ACAMI’s) new AI Essentials Lunch and Learn Series is designed to help professionals build this broader understanding – combining practical AI skills with insights into strategy, ethics, security and governance.
The four module, short self-paced suite,provides essential AI skills for professionals including:
By the end of this short course, you will be equipped to move beyond AI experimentation towards purposeful implementation and effectively integrate AI tools into your professional workflows. You will also develop the skills to critically evaluate the benefits, risks and trade-offs of AI in the workplace, navigate ethical challenges, and manage data securely.
Learn more about the AI Essentials Lunch and Learn Series.
