AI is rapidly reshaping Australia’s software development landscape, a trend supported by recent research showing widespread adoption.

While CSIRO predicts AI could contribute up to AU$315 billion to the Australian economy by 2028, GitLab research indicates a significant portion of developers are already integrating AI into their workflows.

As local organisations adopt AI in software development, we’ll see a transformation in developer workflows and the broader technology ecosystem.

This shift will manifest in significant ways, including AI’s integration as a team member within software development teams and the open source community’s role in democratising AI.

Here are four AI trends that will shape software development this year.

1. AI is becoming a proactive development partner

Recent GitLab research found that 62% of Australian software developers already use AI in their development processes, signaling a clear trend: AI is shifting from a reactive tool to a proactive partner, transforming how developers work.

This will enable developers to spend more time on complex, strategic tasks than daily, monotonous ones that can often consume their day.

For example, automated testing will move beyond AI-written tests to AI-managed test suites, including traditional application security testing.

By treating AI as a partner, developers can prioritise creative problem-solving, accelerate innovation, and deliver impactful business outcomes.

2. Tech giants dominate the infrastructure market, but change is underway

While the number of AI startups is rising, AI infrastructure is still largely shaped by major tech players and cloud hyperscalers.

With their immense resources and expertise, these industry leaders have invested substantially in cutting-edge hardware, such as graphics processing units (GPUs) and tensor processing units (TPUs), essential for training and deploying advanced AI models. This has historically created high barriers to entry for smaller players to compete.

However, the landscape is evolving with more than 650 AI companies headquartered in Australia and $7 billion in foreign investment flowing into the sector over the past five years.

As investment grows and infrastructure becomes more accessible, the potential for a more diverse AI ecosystem in Australia continues to expand.

3. The quality of open-source AI models will improve

The democratisation of AI will accelerate in 2025 as more organisations release high-quality large language models. While tech giants will continue championing their proprietary models, the increasing availability of open source alternatives will lower the barrier to adopting AI and make it more accessible to people and organisations alike.

Like the enduring coexistence of open source and commercial software, both AI approaches will thrive, offering diverse functionalities and strengthening the industry.

4. ModelOps is becoming a critical component of the software development lifecycle

While many data scientists and engineers operate outside the traditional DevSecOps workflow, this disconnect will increasingly hinder their effectiveness.

As AI becomes more deeply integrated into software development, ModelOps has become a critical component of the software development lifecycle.

By combining DataOps, which focuses on preparing and managing data, with MLOps, which handles the development, training, deployment, and versioning of AI models, ModelOps provides a comprehensive framework for ensuring the successful integration of AI into software development workflows.

This year will be a turning point as Australian organisations capitalise on their AI investments and foundations. As AI matures, we expect more sophisticated applications and groundbreaking innovations, such as updates similar to the introduction of “reasoning” models.

From personalised user experiences to autonomous systems, AI is reshaping industries and redefining business models. Integrating AI into core business processes will become increasingly seamless, driving efficiency, productivity, and competitive advantage.

Although there will be some friction as open-source communities work to democratise AI and distribute models beyond tech giants and hyperscalers, this work will ultimately contribute to a thriving and diverse tech ecosystem.