What does it take to guide AI ambitions in Australia?
By Don Schuerman (pictured), CTO at Pegasystems
It probably won’t shock you to hear that in recent times, Artificial Intelligence (AI) has become the centrepiece of many Australian business strategies. With the promise of delivering transformational value, it’s no wonder so many businesses are going all-in. In fact, a recent GenAI study from Pega shows that 80% of Australian organisations are pouring up to half of their annual IT budgets into AI solutions, with 82% expressing confidence that it will add transformational business value over the next five to 10 years.
Clearly, the hype continues to grow, but as more companies integrate AI, some are finding the implementation more challenging than expected. In the rush to adopt AI, are Australian businesses biting off more than they can chew?
According to the same study, a staggering 68% of Australian organisations have experienced a failed AI implementation. This statistic should serve as a wake-up call, especially when considering that 67% of these organisations would trust AI to completely run a department – many experts, myself included, would say that’s a risky move. AI is powerful, but it shouldn’t be left to run the show on its own.
So, what’s the way forward? Before we continue to dive headfirst into AI, we need to take a step back and think about our approach. Here’s what I believe businesses should consider:
Don’t dive in without understanding the risks
AI can do amazing things – summarising information, automating processes, predicting customer behaviours, even mapping out blueprints for business operations, but let’s not forget that it also comes with its fair share of risks. A failed AI project which struggles because of a lack of knowledge and planning doesn’t just fail to deliver on the promised – and much hyped – value, it can lead to much more damaging outcomes, such as data breaches, loss of customer trust, and operational disruptions.
For example, if an AI system designed to automate customer service inadvertently mishandles sensitive customer data, the result could be a significant breach of privacy. This not only damages the company’s reputation but can also lead to legal ramifications and a loss of customer loyalty.
Each AI project requires careful planning, a deep understanding of the underlying technology, and a realistic assessment of the potential outcomes. This means not only understanding the technical aspects of AI but also considering how it will integrate with existing processes, how it will impact employees and customers, and what safeguards need to be in place to mitigate risks.
AI Is fast, but it’s not wise
As AI continues to evolve and become more sophisticated, it’s tempting to think that we can hand over entire departments – or even entire businesses – to machines. The allure of AI lies in its ability to process vast amounts of data quickly, automate complex tasks, and make decisions with a level of efficiency that humans simply can’t match.
However, before we get ahead of ourselves, it’s essential to recognise that AI, for all its power, still lacks the nuanced judgment, ethical considerations, and emotional intelligence that human beings bring to the table. AI’s – and let us be clear that there are many different forms – is quite capable of making decisions, but those decisions are only as good as the data they’re trained on. They can easily inherit the biases, errors, or limitations present in that data. Some forms of AI can learn to optimise decisions they are making, but AI lacks the ability to understand the broader implications of its decisions – and actually understand what it should be optimising for.
That’s why it’s crucial to keep humans in the loop when implementing AI. Businesses should implement AI in a way that augments human decision-making rather than replaces it entirely. This approach ensures that AI supports rather than undermines business operations – when humans and AI work together, they can achieve outcomes that neither could accomplish alone.
Take a hard look at your AI strategy
Before embarking on an AI initiative, it’s time to ask some tough questions. Do we have the right data to train and support the AI system? Are our existing systems and infrastructure capable of handling the AI integration? What are the potential risks, and how can we mitigate them? And perhaps most importantly, is AI the right solution for the specific problem we’re trying to solve? By taking a step back to re-evaluate these aspects, businesses can ensure that their AI investments are aligned with long-term goals, not just short-term hype.
When done right, AI can deliver transformational benefits that drive innovation, efficiency, and growth. It can automate routine tasks, provide deep insights from data, and even predict future trends. But these benefits don’t come from simply adopting AI – they come from adopting AI with a clear, thoughtful strategy.
By thoroughly understanding these factors and taking a cautious, informed approach, businesses can avoid the pitfalls that have led many projects to fail. Success with AI doesn’t come from jumping on the bandwagon – it comes from thoughtful, strategic planning and a clear understanding of both the opportunities and risks involved. Because in the end, it’s not the smartest technology that wins, it’s the smartest use of that technology that makes all the difference.
