Machine Learning in Australia

National Pulse Report 2021

How are organisations in Australia using Machine Learning?

Here at DiUS, we know that Machine Learning will define the future of technology in many ways. And yet this transformative technology is not yet being adopted at the rate it should be. Indeed, our experience has been that a great proportion of organisations struggle to move beyond proof-of-concept or pilot stage.

So we asked organisations across Australia to complete our survey about how they’re adopting Machine Learning (ML). Over 200 organisations responded and we’ve now developed a comprehensive report outlining how organisations are using ML.

In this report, we dig into what’s behind this gap; what’s preventing more organisations converting an interest in ML into success? We also offer insights and tips that may help organisations wanting to progress their ML Journey.

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Key findings

8 in 10 have started their ML journey

There’s a strong appetite for ML in the Australian market with 82% of organisations interested in ML, but only 21% have an ML project in production.

ML adoption is going to accelerate

86% of respondents see ML as critical or one of several important technologies going forward, and 49% of those who have not yet started plan to do so in the next 12-24 months.

Invest in data

Data-related challenges are either the top or second most commonly reported challenges once the ML journey is started. The importance of data quality, data engineering and building appropriate data infrastructure and pipelines to enable ML initiatives cannot be overstated.

Australia could be facing a ML skills gap

Only 69% of organisations with models in production report sufficient ML capability.

Top ML use cases are internally focused… for now

The top two business areas are operational efficiency (48%) and business decision making (46%). Going forward, respondents plan a shift to both an internal and external focus: operational efficiency (57%) and customer experience (51%).