Australian firms shift focus to data quality over AI excitement

Australian technology organisations are expected to shift away from enthusiasm for artificial intelligence towards a focus on measurable outcomes by 2026, according to Alex Avery, Managing Director and Founder of Notitia.

While IT spending in Australia is forecast to reach AUD $172.3 billion by that year, industry leaders are now placing greater emphasis on the results technology can deliver, rather than pursuing AI for its own sake.

Value over hype

Australian businesses are becoming more discerning in their approach to technological adoption. Avery notes an increase in demand for solutions to clearly defined business problems rather than interest in adopting AI tools without a specific purpose.

"We're seeing the end of AI hype and the return of technology for purpose," said Avery, Managing Director and Founder, Notitia.

Organisations are now seeking to understand the underlying problem before investing in or building any technology solution. Many are starting to prioritise foundational work such as establishing data governance and data quality processes before introducing new digital tools.

"We are seeing more requests from Australian businesses who understand that it is critical to get their house in order first. This means putting in place data governance and quality processes to ensure the correct foundation is built to support the introduction of new technology," said Avery.

Data foundations

As businesses try to extract more value from AI, attention has turned to the quality of the underlying data. Avery points out that successful AI implementation relies on comprehensive, clean, and well-structured data, which forms the foundation for consistent and reliable outcomes. Without this, AI initiatives are likely to fail.

"You can't extract valuable insights or automated processes from chaos. Without clean, well-structured data, AI can't deliver consistent or reliable outcomes. Getting your data environment in order is the first and most important step," said Avery.

He asserts that poor quality data can result in AI compounding problems inefficiency, rather than providing value.

"AI doesn't fix bad data. In fact, it can make the consequences of bad data faster and bigger. 2026 will be about maturity, not momentum. The organisations that pause to strengthen their data foundations will outperform those that chase the next big tool," said Avery.

Governance priority

Pierre du Preez, Director at Notitia, sees data governance and data quality as a key differentiator for organisations aiming to scale AI effectively. He highlights the transition taking place between experimentation and reinforcing data infrastructure to enable responsible AI adoption.

"If 2025 was about experimenting with AI, 2026 is about reinforcing the data pipelines and governance frameworks behind it. The companies winning next year will be the ones who know exactly where their data lives, who owns it and how it's being used," said du Preez, Director, Notitia.

Du Preez explains that structured discovery is key, and that business challenges often span people, processes, and technology components. He notes that perceptions of governance as an administrative burden are changing.

"Data governance is the backbone of trust. It's what makes innovation repeatable and scalable. You can't move fast without control," said du Preez.

Avery adds that robust governance makes analytics and AI initiatives more reliable, changing the risk landscape for organisations.

Human-centred focus

Aside from technical readiness, Notitia anticipates a renewed focus on human-centred design (HCD) in 2026. Avery argues that technology succeeds only when it aligns with the way people work and make decisions. He describes HCD as critical in understanding user needs before any system or process is built.

"The lesson is simple: if people can't use it, it doesn't work. Human-centred design ensures that we understand the people and their needs, behind the process before we even consider the first wireframe. If we don't understand their goals, pain points and environment, that dashboard or web product won't land, no matter how powerful the tech is," said Avery.

Du Preez notes that combining HCD with data analytics ensures solutions are trusted and adopted by users. He emphasises that HCD is ingrained in Notitia's approach to solution delivery.

"Design bridges the gap between intent and impact. It ensures the solutions we build actually make sense to the people who rely on them," said Avery.

Strategic approach

Avery and du Preez caution against adopting AI for its own sake and suggest organisations will benefit from a more deliberate, strategy-led adoption model. Setting clear goals and preparing infrastructure, data, and teams ahead of technology deployment is recommended to avoid costly missteps.

"AI is not a silver bullet. It amplifies what's already there: if your systems and processes are weak, it amplifies the problems; If your foundation is strong, it amplifies the value," said Avery.

This approach marks a broader cultural shift in how Australian organisations evaluate and deploy technology, prioritising readiness and clarity over rapid adoption.

"The next 12 months will be less about 'what can AI do' and more about 'what are we ready for'," said Avery.