Research reveals majority (81%) of Australian organisations struggle to demonstrate ROI of AI investments: Snowflake

As Artificial Intelligence (AI) projects move beyond experimentation, the imperative has now shifted towards integrated AI adoption that delivers real business value. While AI enthusiasm is high across APJ, a new research report from analyst firm Ecosystm, “Making AI Work: Strategy, Data, and the Power of Ecosystems”, has revealed how A/NZ organisations are applying Agentic and generative AI, the benefits of AI adoption and that crucial roadblocks are halting organisations from harnessing the benefits of AI.

Commissioned by Snowflake, this Ecosystm research draws on insights from over 700 business and IT leaders across the APJ region. The research revealed that, across A/NZ, businesses are actively piloting and deploying Agentic and Generative AI for customer experience, marketing & communications, operations, and IT.

With customers as the primary focus, the most evaluated use cases are interacting with customers across channels, reported by 67 per cent of Australian organisations, improving chatbot responses (53 per cent), and generating marketing content (65 per cent). Meanwhile, New Zealand’s most evaluated use cases are interacting with customers across channels (68 per cent), generating marketing content (60 per cent), and improving search & summarisation of data and reports (56 per cent).

However, the research revealed that translating isolated pilot successes into consistent, scalable business value has proven more complicated than many organisations anticipated. In Australia, the challenge of demonstrating the business value or ROI of AI investments is especially acute, with 81 per cent of organisations reporting difficulties, second only to Korea (83 per cent) among surveyed nations. In contrast, 70 per cent of New Zealand organisations indicated challenges in proving AI value, the lowest among the surveyed countries.

“While there is widespread AI enthusiasm across the region – particularly in Australia and New Zealand – business leaders are now expecting to see the technology deliver real business value,” said Theo Hourmouzis, Senior Vice President, Australia, New Zealand and ASEAN, Snowflake. “To unlock this value, organisations must deeply integrate AI into their business strategy, rather than pursuing it as merely an experiment. This requires starting with clear, measurable use cases tied to real business needs rather than deploying AI for AI’s sake.”

Data Challenges prominent across A/NZ

According to the report, AI adoption often faltered due to fragmented data and underprepared technology foundations, rather than from issues with models themselves. It found that the top data challenges for Australian and New Zealand organisations were data accessibility (56 per cent of respondents), data quality (52 per cent), data security and data observability (49 per cent each).

These challenges highlight the on-the-ground reality, with the report finding that just 19 per cent of Australian companies and 24 per cent of those in New Zealand have fully integrated AI into their business strategy.

Investments in technology required to address unstructured data challenge

The report emphasises that fragmented and underprepared data and technology foundations lead to failed AI adoption. For AI adoption to succeed, it requires a flexible, high-performance data backbone; seamless access to data through centralised metadata catalogues and lineage tracking; and continuous, real-time monitoring of model performance, data drift, bias, and output quality.

According to the report, only 38 per cent of organisations among all nations surveyed have invested in technologies that enable them to analyse unstructured data.

However, this is evolving as organisations across Australia and New Zealand are shifting towards a more strategic approach to AI. The report found 85 per cent of Australian organisations and 76 per cent of those in New Zealand are engaging, or plan to engage, tech partners to support their strategic, technological, and data needs for AI projects.

“AI isn’t just plug and play; partners will be vital to helping bridge capability gaps, accelerate deployments, establish governance frameworks, enabling organisations to stay ahead of the next wave of disruption,” said Hourmouzis. “Whether it’s cloud providers supporting infrastructure modernisation, systems integrators enhancing data governance and compliance controls, or MSPs helping to scale AI, local organisations don’t need to forge their AI journey alone.”

Best Practices: Solving for the ROI Challenge

To better demonstrate the ROI of AI projects – and overcome challenges like data accessibility – the research provides five best practices organisations should adopt:

• Immediate Impact, Lasting Value: AI success hinges on delivering quick wins like faster lead times or better customer satisfaction, while building long-term value through smarter decisions and greater agility. Leading organisations measure short-term KPIs alongside strategic enablers such as data quality, explainability, and workforce adoption to drive impact now and resilience for the future.

• Measuring ROI Across the AI Lifecycle: Pilots prove feasibility but don’t capture full value. True ROI emerges as AI scales and integrates into operations. Organisations must measure across the entire AI lifecycle, from infrastructure upgrades and model maintenance to governance, compliance, and ongoing optimisation, to reveal hidden costs and sustained benefits, understanding a full picture of AI’s return.

• Integrating Disparate Tools for Clearer Insights: Fragmented tools across data preparation, model development, deployment, monitoring, and impact tracking create silos and blind spots. Organisations must adopt integrated AI lifecycle platforms that unify technical and business metrics, streamline workflows, and enhance governance controls, delivering faster iteration and sharper visibility into AI’s business value.

• Building Strong Foundations: AI initiatives falter without robust skills, reliable data, and strategic focus. High-performing organisations invest in scalable data infrastructure, build cross-functional teams with technical and domain expertise, and tightly align projects to business goals and KPIs; turning experiments into engines of growth and competitive edge.

• Recognising the Cost of Inaction: ROI isn’t just about cutting costs; it’s about making smarter decisions, strengthening compliance, empowering teams, and driving continuous innovation. The real risk lies in inaction. Forward-looking organisations are investing The AI News Blog, backed by scalable governance capabilities, agile talent, and future-ready models to stay competitive.

The report can be found here.