And How the Kodora AI Mastery Model Helps Organisations Become AI Masters
Artificial intelligence is no longer an experimental technology reserved for the world’s most innovative companies. It has become a competitive necessity. Across Australia, businesses are under pressure to extract measurable value from AI—not simply by running isolated pilots, but by embedding AI into the core of how they operate. This shift demands more than just technical capability; it requires a clear, coherent AI strategy.
An AI strategy is a deliberate, organisation-wide plan for integrating artificial intelligence into business operations, customer experiences, and decision-making processes in a way that drives measurable value. It’s the difference between scattering resources across disjointed experiments and building a structured roadmap to sustained competitive advantage.
At Kodora, we see AI strategy as both a business discipline and a capability-building journey.
It’s about ensuring AI investments are not only technically sound but aligned with vision, governance, and operating models. To help leaders navigate this journey, we’ve developed the Kodora AI Mastery Model—a framework for understanding where you are on the AI adoption curve and how to progress to the highest level of maturity: becoming an AI Master.
Why AI Strategy Matters Now
The stakes for AI adoption are rising. Globally, PwC estimates AI could add up to US$15.7 trillion to the world economy by 2030, with as much as A$315 billion potentially accruing to Australia if adoption accelerates. But Australian organisations remain uneven in maturity. Some, like Commonwealth Bank and Canva, have deeply embedded AI into their products and operations. Others are still experimenting in pockets without a clear path to scale.
Without a coherent strategy, organisations risk falling into the “POC Factory”—running multiple AI projects without integrating them into a broader vision or realising a significant return on investment. This leads to wasted resources, fragmented capabilities, and missed opportunities for market leadership.
An effective AI strategy addresses three critical questions:
- What are we trying to achieve with AI? (Strategic outcomes)
- Where should we focus our resources? (Priority use cases and investment areas)
- How will we execute responsibly and at scale? (Governance, operating models, and talent)
Introducing the Kodora AI Mastery Model
The Kodora AI Mastery Model, adapted from the MIT Digital Mastery framework, is our way of mapping an organisation’s AI maturity across two dimensions: adoption intensity (the scale and breadth of AI investments and assets) and benefits intensity (how effectively those investments translate into competitive advantage and measurable returns).
The model identifies four broad categories:
- Beginners – Early in their AI journey, with minimal investment and few tangible business outcomes.
- Fashionistas – Running multiple AI initiatives but without a unifying strategy or clear ROI. Innovation is present, but benefits remain inconsistent.
- Conservatives – Selective with AI adoption, ensuring governance and oversight but often too cautious, missing opportunities to scale impact.
- AI Masters – Have built a strong AI foundation, integrating technology with vision, governance, and an operating model that consistently delivers profitability, customer experience gains, and market value growth.
The goal for any ambitious organisation is to progress to AI Master status—where AI is not just a tool but a strategic asset embedded across the business.
What It Takes to Become an AI Master
Our work with Australian enterprises shows that becoming an AI Master requires a balance of strategic ambition and operational discipline.
First, leaders need a clearly articulated AI vision that aligns with corporate strategy. This vision acts as a north star for investment decisions and helps avoid scattergun adoption. Without it, organisations risk falling into the Fashionista quadrant—innovating in silos without lasting impact.
Second, AI Masters invest in capability building. This means not only having access to data scientists and engineers but also developing cross-functional teams that include product managers, risk specialists, and change leaders. Upskilling at scale ensures AI adoption is sustainable and widely understood.
Third, they embed governance and risk management into the operating model from day one. This includes setting ethical boundaries, ensuring transparency in model decisions, and aligning with regulatory requirements such as the Australian Privacy Act and industry-specific standards.
Lessons from Australian AI Masters
Two local examples illustrate what AI mastery looks like in practice.
Commonwealth Bank has integrated AI deeply into its customer operations. Using H2O.ai, it links its customer database to ATMs and internet processing platforms, enabling a seamless flow of information across all customer channels, including branches. This integration provides rich insights into transaction data, member habits, and operational efficiency, allowing for tailored product delivery and improved service.
Canva, meanwhile, strategically acquired AI capability by integrating Leonardo.ai to link image and content databases, enhancing design workflows for its users. The move not only improved product experience but also positioned Canva as a serious contender against global giants like Adobe. Within weeks, the company reported a significant jump in its subscription base.
Both examples highlight a common theme: AI is embedded within the organisation’s core value proposition, supported by clear governance, and continually refined for impact.
Best Practices for Building Your AI Strategy
If your organisation is at the Beginner, Fashionista, or Conservative stage, moving toward AI Mastery requires a deliberate plan. We recommend:
- Start with a high-value use case portfolio: Identify 2–3 projects where AI can deliver quick wins while laying a foundation for scaling.
- Align data strategy with AI objectives: Ensure the right data is available, clean, and governed to support target use cases.
- Build governance from day one: Define ethical principles, set risk thresholds, and create approval workflows for AI deployments.
- Integrate change management: Equip employees with the skills and confidence to work effectively alongside AI tools.
- Measure, refine, scale: Use metrics that tie directly to business outcomes—such as cost reduction, revenue growth, or customer satisfaction—and continuously improve.
The Australian Context
Australian organisations face unique conditions that make AI strategy design particularly important. Data residency requirements, a strong regulatory environment, and sector-specific compliance obligations (especially in finance, health, and public services) require AI solutions to be not only effective but also trustworthy.
At the same time, Australia’s relative geographic isolation makes technology adoption speed critical for maintaining competitiveness. Organisations that move decisively to master AI will be better positioned to expand globally, attract top talent, and drive innovation domestically.
How Kodora Helps
At Kodora, we work with leaders to assess their current AI maturity using the Kodora AI Mastery Model, identify the gaps holding them back, and design a roadmap for becoming an AI Master. Our approach blends strategy, governance, and execution, ensuring AI programs deliver measurable returns while staying compliant with Australian laws and ethical standards.
We provide end-to-end support—from identifying priority use cases and building AI capability, to implementing governance frameworks and embedding AI into daily operations. Our experience spans industries including banking, mining, healthcare, and government, giving us insight into the specific challenges and opportunities in the Australian market.
By combining a clear AI strategy with the discipline of the Kodora AI Mastery Model, your organisation can move beyond experimentation and achieve true competitive advantage.
