Over the past two years, I have spearheaded multiple Generative AI (GenAI) initiatives to enhance customer service, streamline internal processes, and gain a competitive edge. These projects have spanned various applications, from deploying customer service chatbots to automating internal workflows. Originally published at LinkedIn Pulse on 24 March 2024. Photo by Tara Winstead @ Pexels.com This journey has provided us with critical insights, revealing both the immense poten

In many organisations, Chief Data and Analytics Officers (CDAOs) find their roles confined to traditional data management tasks, mirroring the responsibilities typically associated with Chief Data Officers (CDOs). Their focus often centres on governance, compliance, and platform investments — essential areas, but ones that risk overshadowing their ability to deliver strategic business value through analytics. Originally published at LinkedIn Pulse on 13 April 2025. Photo by

Vibe coding is an emerging paradigm in software development where developers express high-level intent in natural language, and AI assistants generate the underlying code. It flips the developer’s role from coder to orchestrator, with a focus on reviewing, testing, and tightening what the machine produces. In the right context, this is a game-changer. It slashes time spent on boilerplate, accelerates prototyping, and lets non-specialists turn ideas into working models faster

In 2023, the field of generative artificial intelligence (AI) experienced remarkable progress, with significant advancements in natural language processing, computer vision, and audio synthesis. These developments have unlocked a plethora of new opportunities and applications, shaping the future trajectory of technology across a wide range of sectors. This article provides an overview of the ethical considerations and responsible strategies for the development, deployment, an

Generative AI (GenAI), especially LLMs, has transitioned from a buzzword to an essential business asset. Leading organisations have moved beyond the proof-of-concept (POC) phase and are now actively deploying GenAI solutions. Many non-technology companies have realised that developing proprietary LLMs is unnecessary for solving internal challenges . Instead, they acquire LLMs from vendors or the open-source marketplace. Originally published at LinkedIn Pulse on 23 March 2025

The buzz around AI often overshadows a critical reality: over 85% of employees anticipate that AI will impact their jobs within the next 2-3 years, leading to a mix of excitement and apprehension. There’s a notable disconnect between leadership’s perception of readiness and the reality on the ground, with C-suite leaders more likely to cite a lack of employee readiness as a barrier, even as employees are already adopting generative AI tools at a higher rate than expected. Thi

The transformative power of Artificial Intelligence (AI) is evident, but its full potential is often left untapped. This isn’t due to technical challenges, but rather a sizable communication gap between technical teams and senior leaders. For mid-to-senior-level leaders, knowing how to communicate effectively about AI isn’t optional; it’s crucial for driving business growth and successfully implementing AI. Originally published at LinkedIn Pulse on 30 November 2025. Effectiv

In today’s data-driven landscape, CDO, CAO, and CDAO are critical in steering organisations towards success. The journey began with the CDO, who introduced a data-centric culture by developing robust data strategies, ensuring data governance, and effectively managing data assets. As the volume and complexity of data grew, the need for specialised analytics expertise became apparent, leading to the creation of the CAO role. The CAO focused on transforming raw data into actiona

In today’s highly competitive environment, the rush to harness the transformative power of Artificial Intelligence (AI) is apparent. However, beneath the surface of many organisations, there is a subtle, often hidden, threat: Shadow AI. This isn’t the stuff of sci-fi thrillers; it involves the widespread use of AI tools and initiatives by individual teams or departments, such as marketing, HR, or customer service, without central oversight, approval, or understanding from IT

The honeymoon phase is over. What comes next will reshape every company on earth. There is a quiet revolution underway inside enterprise technology—and it bears no resemblance to the breathless headlines about artificial general intelligence or trillion-parameter models. It looks like budget reviews. It looks like an infrastructure audit. It looks like boards are demanding to know why AI investments are producing inconsistent returns at unsustainable cost. The era of deployin

The Governance Gap Behind Woolworths, Commonwealth Bank, and the Next Headline You Haven’t Read Yet For boards and executive teams navigating AI adoption in 2026. Imagine calling Australia’s largest supermarket chain for help with your grocery order. The company has invested heavily in artificial intelligence. They’ve partnered with Google. They’ve announced their new AI assistant to the market with genuine fanfare. You type your question, and the chatbot tells you about its

In the modern business landscape, the utilisation of data and analytics has transcended its conventional role of providing retrospective insights and has emerged as a catalytic force for driving meaningful impact across organisations. This article explores the concept of transformative analytics, delving into its significance, challenges, and strategies while shedding light on real-world instances of organisations that have successfully harnessed analytics to bring about prof

Multiple recent recruitment surveys revealed that the demand for data engineers has recently exceeded the previous demand for data scientists. The Dice 2020 Tech Job Report said data engineer was the fastest growing job in technology with a 50% year-over-year growth in the number of open positions. Many mentees asked me how do I perceive this shifts in demand, and what area should they pursue. Actually, I see a course correction happening in the industry. Most organisations t

As 2025 draws to a close, I find myself at the epicentre of a profound strategic misalignment in the technology world. On one hand, Artificial Intelligence (AI) has delivered at a scale few could have predicted even three years ago; it is now the undisputed operational core of global commerce, driving spectacular technological breakthroughs in fields from personalised medicine to autonomous manufacturing. Yet a persistent, unsettling anxiety grips the financial markets, the c

The introduction of modern Artificial Intelligence (AI), especially large language models (LLMs) and predictive models, is undeniably a defining technological moment for enterprises. These technologies offer exponential capabilities that feel like organisational superpowers , exponentially enhancing human productivity. Yet, this extraordinary potential is inextricably linked to an exponential amplification of systemic risk , creating a profound operational dilemma for

Artificial Intelligence (AI) is no longer a future consideration. It is a present imperative reshaping how businesses operate. AI enhances decision-making by delivering speed, precision, and insight at a scale that human intuition cannot match. By analysing vast datasets and identifying patterns, AI generates actionable intelligence that drives real-time value. The economic potential is massive, with trillions in possible value creation and significant productivity gains. Com

Australian businesses are trapped in a self-perpetuating cycle of mediocrity. While we claim to be innovative and proactive, many of our largest and most influential organisations are led by executives fundamentally ill-equipped to steer a modern technology and data-driven enterprise. The culprit is the pervasive reliance on the general manager archetype, a leader whose broad, non-technical background, while perfect for traditional business operations, becomes a liability in

The global executive suite has invested an estimated $30 billion to $40 billion in Generative AI (GenAI) initiatives. Yet, a staggering majority of these investments are failing to yield a measurable financial impact. The widespread failure to convert this capital expenditure into shareholder value signals a profound strategic misstep. The core issue? Treating AI as a standalone technological novelty, a shiny new chatbot , rather than a fundamental amplifier of exis

The pervasive notion that sophisticated Artificial Intelligence (AI) systems, particularly predictive models and large language models (LLMs), operate under a regime of continuous, autonomous self-improvement is one of the most persistent and potentially damaging misconceptions in contemporary technology discourse. This belief, often propagated through media narratives and science fiction precedents like Recursive Self-Improvement (RSI), a concept involving a system autonomou

The recent reversal of the Commonwealth Bank of Australia's (CBA) AI-driven job cuts serves as a powerful cautionary tale for every business leader navigating the era of artificial intelligence (AI). CBA's initial decision to slash 45 customer service jobs and replace them with an AI-powered voice bot was a move rooted in outdated, Industrial-era management philosophies. This approach, focused on headcount reduction and operational cost-cutting, proved to be a strategic fai