Everyone is investing in AI but very few organisations are scaling it, and even fewer are seeing real value.

At ADAPT’s 5th Data & AI Edge, Gabby Fredkin shared the latest insights into how senior technology, data, and business leaders are navigating AI transformation, drawing on more than 5,000 executive interactions and 1,000 in depth surveys across A/NZ.

 

Key takeaways:

  • Scaling AI requires operating model change, not a growing stack of disconnected tools and experiments.
  • Clear ROI definitions unlock scale. When success is measured through business outcomes, value becomes visible and repeatable.
  • AI at speed requires human safety. Trust, shared ownership, and employee confidence are critical as deployment accelerates.

 

Understanding your quadrant

Gabby introduces a practical way to assess AI readiness through four archetypes: koalas, greyhounds, turtles, and tigers, based on data architecture maturity and governance maturity.

This isn’t a maturity model or a race to the top right, but a diagnostic lens to understand where organisations actually operate today.

Most organisations sit in “AI adjacent” territory: experimenting with tools like copilots, but without integrating AI into operating models, decision making, or enterprise scale.

 

Why AI stalls for koalas and greyhounds

Koalas struggle because their data isn’t AI ready: architecture, governance, and capability don’t work together, creating friction rather than scale.

Greyhounds, by contrast, move fast on modern platforms and deployments, but governance and business ownership lag behind.

The result is agent sprawl, unmanaged risk, and technology-led AI that doesn’t always translate into business value.

In both cases, the barrier isn’t lack of effort; it’s misaligned metrics, legacy processes, and unclear ROI articulation.

 

Governance without value vs value without control

Turtles demonstrate strong governance, policy, and training, but without modern architecture, control increases while value plateaus.

Governance becomes a bolt on rather than an enabler of scale.

Gabby highlights a critical tension: organisations don’t need more compliance; they need better compliance that makes it easier to move AI from experimentation into production.

The organisations that break through focus on evolving operating models alongside platforms and governance, not treating them as separate transformation tracks.

Tigers represent what AI at scale truly looks like: organisations that redesign their operating models around AI rather than treating it as a series of experiments.

Using Lendi as an example, Gabby shows how even large, highly regulated organisations with legacy systems can move fast by setting clear guardrails, embedding agents into core workflows, and starting adoption with senior leadership to build shared context and momentum.

The impact is measured not through activity, but through business outcomes (time saved, customer experience, and clearly defined ROI), using metrics the organisation already trusts.

Tigers differ because they orchestrate AI across teams and workflows, track outcomes rigorously, and address the human challenge alongside speed, ensuring employees feel safe as deployment accelerates.

AI success at scale comes from coordinating the hard things together, operating model change, governance, speed, measurement, and human adoption.

With a passion for creating stories with data, Gabby is consistently rated as one of the top speakers at ADAPT’s events.

In roundtable discussions, he specialises in using statistics to initiate thought-provoking discussions. ​

Gabby is effective in translating information into insights, enabling ADAPT’s customers to become more data-driven.​

Contributors
Gabby Fredkin Head of Analytics & Insights at ADAPT
As the Head of Analytics and Insights at ADAPT, Gabby Fredkin’s primary role is managing analysis to produce ADAPT’s actionable insights to... More

As the Head of Analytics and Insights at ADAPT, Gabby Fredkin’s primary role is managing analysis to produce ADAPT’s actionable insights to identify trends supporting organisations in Australia.

With a passion for creating stories with data, Gabby is consistently rated as one of the top speakers at ADAPT’s events. In roundtable discussions, he specialises in using statistics to initiate thought-provoking discussions, enabling ADAPT’s customers to become more data-driven.​

Using modern data science techniques, he provides ADAPT and its customers with confidence in the accuracy and validity of the information used for ADAPT’s research, advisory and events.

Working across artificial intelligence, machine learning, AI ethics, DevSecOps, end-user behaviour, and human-centred design, Gabby’s vast experience continues to grow, supported in part by a Master of Business Analytics from Deakin University.

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transformation data leadership