Transform – Tomorrow’s thinking, today: Data foundations for AI - Episodes 15, 16 and 17
At a glance
Transform is a podcast where we explore the ideas and developments shaping how communities grow. This three-part conversation explores how data insights shape the decisions organisations make every day, common challenges across regions, the mindset shifts driven by emerging technologies and how organisations approach AI adoption.
Part one: What breaks trust in infrastructure?
In part one, GHD’s Tom Bedeman (Data Insights Business Group Leader) and Jon Jarritt (Data & Insights Market Leader) explore common challenges in data infrastructure, drawing on their work across the UK and a trip around Australia, where they spoke with 27 clients across multiple asset sectors.
This episode tackles a fundamental question: when everyone is investing in similar technology, why do results still vary so widely?
Some of these gaps are foundational. When systems use different or unclear definitions for the same data, results become harder to trust. Another gap is treating data investment as a one-off capital expense rather than the ongoing operational capability it needs to be.
Part two: What's the difference between data, applications and platforms?
We rely on applications to turn data into insight. Over time, organisations have invested in new platforms to modernise these applications. While this approach has delivered benefits, especially when it comes to legacy applications, it’s also introduced new challenges.
In part two, Tom and Jon explain how thinking around data is evolving and why technology alone rarely fixes data challenges. With AI rapidly reducing the cost and time to build systems, they pose the question: are we moving too quickly without fixing the foundational issues?
Part three: What should infrastructure leaders do next with AI?
In part three, Tom and Jon explore the risk and reward in investing in AI. While interest in this new technology continues to grow, managing expectations, preparing machine-readable workflows and having data quality as a foundation can support AI adoption safely.
There is a clear momentum for organisations to join this AI journey and progress does not need to come at the expense of safety.
By putting data first — clarifying meaning and strengthening data — organisations can position themselves to adopt AI in a way that suits their operations and risk profile.