It's hard to believe nine months have passed since my last day at Iress. Time has flown, and we're already in the final quarter of 2024. Stepping away from the "daily grind" has allowed me to observe, read, and learn with a fresh perspective. While everything seems to be moving quickly, there's an odd sense that some things remain unchanged—a strange dichotomy.

Generative AI, as expected, follows the trajectory of the Gartner Hype Cycle. The level of investment and valuations among 'creators' and 'operators' is staggering. However, outside of Big Tech, tangible ROI and evidence of material, strategic use cases remain elusive. Risk can't be dismissed as quickly as some would like. Chatbots, despite their prevalence, don’t count as significant advancements.

The growing realisation that organisations must move beyond merely acknowledging the importance of data to leveraging it—beyond just having a data governance policy—is increasingly driven by AI. Technology leaders are taking divergent paths: the leaders are designing decentralised solutions like data meshes, while others cling to more traditional enterprise data warehouse strategies and single-tech solutions. Architecturally, this feels like the monolith/microservice debate, round two (or perhaps more).

There’s rapid iteration in tooling, languages, frameworks, and approaches to organisational design, all aimed at accelerating development. These iterations make it easier for developers to write more code faster (with GenAI speeding things up even more) and to identify and fix issues through advanced observability platforms. Yet, the ROI remains unclear for many, especially over the long term, as the impact and costs of having "more tech" begin to surface.

The fundamentals of building, designing, and operating 'good technology' seem increasingly overlooked. However, these fundamentals matter—big time. As Big Tech races ahead, those with poor foundational capabilities will lag and ultimately lose. Big Tech, inherently product- and tech-led, operates from a cultural core and capability base that supports sustained innovation and delivery. Traditional companies, by contrast, often lack this core and culture.

One critical perspective on this challenge is through the lens of cyber risks and the burden of legacy technology, which continue to pose significant threats globally, with costs running into billions of dollars annually. Despite the severity of these risks, many organisations struggle to address them effectively. The complexity and cost of modernising legacy systems often lead to a 'patch-and-pray' approach rather than a comprehensive overhaul. Additionally, the understanding and awareness of cyber threats at the board level provide a strategic challenge for directors. Where should investment be directed? Should they chase growth, cut costs, or protect the organisation? Achieving all three goals is difficult, as significant conflicts exist between them, especially over different time horizons.

It sounds harsh, and it's generalised, but talk, hype, and hope don’t produce outcomes—they incur costs and waste our most precious resource: time. Vision, commitment, culture, experience, data-driven innovation and experimentation, and execution capability drive success. It's easy to lose perspective in the endless chase.