AI has quickly gone from nascent to necessary for CIOs across the region . Many CIOs are now grappling with how to quickly , efficiently and securely take advantage of the power of generative AI and ML applications , while simultaneously evaluating the new use cases that emerge every day from improving customer service and developer productivity , to increasing operational efficiency and more .

In my conversations with CIOs , the vast majority of them see the opportunities AI presents but they are struggling with growing concerns regarding intellectual property leakage , compliance and privacy .

Despite the near universal agreement that AI is a business priority , a significant amount of work still needs to be done . The technology ’ s emerging nature means there is a lack of strategic best practices ,

established guardrails or even reference architectures . As such , many organisations are still determining which IT environments are best to run different parts of their AI processes and workloads . While some might default to the public cloud , this may not be the best fit for applications which require access to sensitive and business critical data .

A related point for any CIO to consider is the emerging nature of the regulations governing the use of AI and the legislative differences in each jurisdiction the organisation operates . One of the biggest pitfalls enterprises must avoid when implementing AI models – or any emerging technology for that matter – is running afoul of data security and sovereignty regulations . We ’ re only just starting to figure out what questions to ask in the regulatory space so it will be some time until we have the answers . Until then , enterprises need to maintain control of their data and applications .

When it comes to the skills required to implement , maintain , train and manage an advanced AI model , CIOs need to be clear-eyed about the capabilities their organisations have . If the necessary skills don ’ t currently exist within the organisation , what training will be required ? Alternatively , if new talent will need to be hired , where will that talent come from ? This is particularly challenging in nations with pronounced technical skills gaps , such as Australia .

Ultimately , AI will be a core driver of innovation and business differentiation in the years to come . It has the ability to completely reimagine how businesses , governments and society as a whole operates , but its implementation must be approached with a careful consideration of the infrastructure , governance and skills required to truly reap its rewards .

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