Why getting AI adoption right the first time is crucial for success

Australian organisations are navigating a transformative period as artificial intelligence (AI) adoption accelerates across industries. The potential of AI is vast, offering opportunities to enhance efficiency, drive innovation, and reshape entire sectors. However, with this potential comes significant responsibility. The process of implementing AI is complex, and the challenges associated with getting it right the first time should not be underestimated.  

Data from the Logicalis Global CIO Report 2024 shows that 89 per cent of Australian CIOs are actively seeking opportunities to integrate AI into their businesses, with 85 per cent earmarking specific budgets for AI development.¹ This level of commitment highlights the critical role that AI is playing in the strategic planning of Australian businesses. Despite this enthusiasm, Australian CIOs are approaching AI adoption with a healthy dose of caution.  

The reality is that unlearning an AI model is far more difficult than deploying one. Once an AI model is trained, its learned behaviours become deeply embedded and reversing these behaviours can be both time consuming and resource intensive. This makes it crucial for organisations to lay a solid foundation before embarking on their AI journey.  

AI can drive incredible efficiencies and innovation; however, it requires clean, well-structured data and a clear understanding of its intended use. Without this predesigned structure, organisations risk embedding incorrect or biased behaviours into their AI models.

It's important to have a solid business use case to promote AI implementation within a business. A strong use case aligns AI initiatives with the company's strategic goals, maximising the potential for positive impact and return on investment (ROI). It lets organisations identify specific problems that AI can solve, avoiding the risk of implementing AI for the sake of it. Clarity in a well-defined use case also aids in securing stakeholder buy-in and resource allocation by providing a clear roadmap of expected benefits and outcomes.

A well-defined business use case also plays a pivotal role in project management and risk mitigation. It outlines the scope, requirements, and potential challenges of AI implementation, facilitating better oversight throughout the project lifecycle. This promotes AI deployments that are purposeful, efficient, and scalable, driving meaningful business transformation and providing a competitive advantage.

The CIO Report reveals that 72 per cent of technology leaders expressed concerns about the challenges of regulating AI use within their organisations, and these concerns are well-founded.² The state of data is one of the key challenges facing Australian organisations. Data that is siloed, unstructured, or poorly governed reduces its value and complicates its efficacy when it's fed into or used to train AI models. The risk of AI models producing incorrect or biased outcomes increases without proper data governance, leading to potentially significant operational and reputational risks.

Additionally, because AI is not a static technology, and it evolves and learns over time, its outputs can change as new data is introduced. This dynamic nature requires constant oversight and management to ensure that the models continue to operate as intended. CIOs must establish robust governance frameworks that include ongoing monitoring, evaluation, and adjustment of AI models to address these concerns. This is particularly important given the ethical considerations associated with AI, as AI models can inadvertently learn and propagate biases, which can have serious implications for businesses, particularly in sectors where fairness and equity are paramount, such as finance, healthcare, and law. Both well-structured data and a clear use case are essential foundations that organisations must establish from the outset to ensure long-term AI success.

The rush to adopt AI without proper governance and oversight can lead to significant failures within a business or department, so it's crucial that organisations address these challenges early in the AI implementation process. Without clearly defined measures, outcomes, user enablement, and purpose, AI is just another tool that businesses may invest valuable time and money into, only for it to sit on the shelf. Understanding where, why, and how AI can improve a business is the most important first step.

Organisational leaders must take the time to understand what AI can and cannot do, ensure their data is in order, and establish the necessary governance frameworks before they begin their AI journey. Doing it right the first time will save time and resources, and it will save an organisation from potential reputational and financial damages in the future from using ungoverned data.

The pace of technological change is relentless, and AI is just one of many emerging technologies that require management. CIOs are being pulled in multiple directions as they seek to balance the demands of AI implementation with other priorities such as cybersecurity, digital transformation, and sustainability. This requires a strategic approach to resource allocation and a clear understanding of where AI fits within the broader technology landscape. AI must be carefully integrated with other technological initiatives to ensure organisations are prepared for the wider impact of digital transformation.

Australian CIOs demonstrate a strong commitment to AI adoption, recognising its transformative potential and taking proactive steps to ensure that their organisations are well-positioned to capitalise on it. However, they are also aware that the stakes are high, the decisions they make today will have long-lasting implications for their organisations and, as such, there is little room for error.

The global AI race is on, though it is not a race that can be won by rushing to the finish line. It's about taking the time to do things right from the start. The organisations that succeed will be those that approach AI with caution, care, and a commitment to excellence.  

CIOs must take the time to understand the technology, as doing so will empower organisations to harness the power of AI to drive innovation and growth while minimising the risks associated with this rapidly evolving technology.