Half of Australian organisations trail on tech upgrades as AI adds pressure

Almost half of Australian organisations are falling behind on their technology modernisation targets as the push to adopt artificial intelligence adds pressure to older IT setups.

IT services firm Kyndryl released the findings on Tuesday in its first State of Modernisation Report, which surveyed 2,000 business and technology leaders globally. In Australia, 49 per cent of respondents acknowledged they are trailing on modernisation.

Ageing systems face AI pressure

Rather than simplifying operations, artificial intelligence tools are exposing weaknesses in existing digital foundations. The study found that instead of migrating everything to a single cloud setup, Australian companies are managing increasingly fragmented environments, split between older on-premises hardware, multiple clouds and newer software.

Around a quarter of mission-critical business applications in Australia still run on mainframes, and 55 per cent of those estates are more than a decade old. Connecting fast-moving automation tools to these older databases has created technical friction and security headaches. Recent breaches linked to AI integrations prompted the Department of Home Affairs to urge reviews of legacy platforms across both public and private sectors.

The report also found that adoption of automated agentic workflows remains in its early stages locally. Only 6 per cent of Australian organisations currently run agentic AI in daily production, while 25 per cent are running trials and 43 per cent are assessing options. Globally, businesses that successfully integrated these systems into IT modernisation reported faster progress, with 67 per cent staying on track.

Priorities for upgrading software have also shifted. Where businesses previously updated older tools mainly to trim expenses, leaders now cite operational speed, system integration and stronger governance as their primary motivations.

What this means for Australian businesses

For smaller and mid-sized businesses, the findings provide a clear lesson: adopting front-end AI tools without cleaning up underlying systems creates long-term trouble.

• Fix core data and software first. AI assistants cannot deliver good answers if they connect to outdated, messy spreadsheets or disconnected accounting platforms.
• Avoid shadow IT sprawl. Sticking AI apps on top of existing processes without a plan creates security loopholes and data leaks.
• Focus on integration over novelty. Look for automation tools that connect directly to your core customer database or accounting software using secure application interfaces.
• Start small with repeatable tasks. Rather than attempting complete operational overhauls, test automated workflows on simple administrative tasks before expanding into critical business functions.