Reframing AI Execution: The Frameworks CIOs Need Beyond the Pilot Phase
In this Community Intelligence Report, ADAPT reveals why AI success depends less on new tools and more on fixing the foundations required to scale them.
Published Jun 23, 2026 in
Articles
Data & AI Strategy
Contributors
Pooja Singh
AI experimentation is giving way to execution.
Across Australia, technology leaders are discovering that scaling AI requires more than deploying new tools.
It demands stronger data foundations, clearer governance, and operating models designed for AI at enterprise scale.
This report reveals why many organisations remain trapped between successful pilots and meaningful business outcomes, and what leading CIOs are doing differently to bridge that gap.
The execution challenge
While AI capabilities continue to advance rapidly, many organisations are still constrained by fragmented data, process debt, and siloed ways of working.
Boards are demanding faster returns, yet the foundations required to support industrial scale AI remain unfinished.
Drawing on insights from Peter Smith, CEO of Mission Australia, Sheridan Ware, CIO, advisor and Non Executive Director of the Sustainable Digitalisation Project, and Arul Arogyanathan, Group CIO at Village Roadshow Group, this report explores the frameworks, governance models, and leadership disciplines required to move beyond experimentation and create measurable enterprise value.
What you’ll learn in this report
- Why process debt and weak data foundations continue to stall AI execution.
- How leading CIOs are assessing AI investments through practical business value frameworks.
- What role governance, co design, and workforce readiness play in successful adoption.
- How to decide when to buy, extend, customise, or build AI capabilities.
AI experimentation is giving way to execution.
Across Australia, technology leaders are discovering that scaling AI requires more than deploying new tools.
It demands stronger data foundations, clearer governance, and operating models designed for AI at enterprise scale.
This report reveals why many organisations remain trapped between successful pilots and meaningful business outcomes, and what leading CIOs are doing differently to bridge that gap.
The execution challenge
While AI capabilities continue to advance rapidly, many organisations are still constrained by fragmented data, process debt, and siloed ways of working.
Boards are demanding faster returns, yet the foundations required to support industrial scale AI remain unfinished.
Drawing on insights from Peter Smith, CEO of Mission Australia, Sheridan Ware, CIO, advisor and Non Executive Director of the Sustainable Digitalisation Project, and Arul Arogyanathan, Group CIO at Village Roadshow Group, this report explores the frameworks, governance models, and leadership disciplines required to move beyond experimentation and create measurable enterprise value.
What you’ll learn in this report
- Why process debt and weak data foundations continue to stall AI execution.
- How leading CIOs are assessing AI investments through practical business value frameworks.
- What role governance, co design, and workforce readiness play in successful adoption.
- How to decide when to buy, extend, customise, or build AI capabilities.
