Harnessing AI and Automation for Smarter Healthcare Data Storage

Healthcare organisations are generating unprecedented data volumes while simultaneously gaining new tools to manage them. As organisations worldwide embrace AI technologies, the volume of data they generate and manage has grown exponentially. Gartner forecasts that global generative AI (GenAI) spending will reach $644 billion in 2025 – a staggering 76.4% increase year-over-year – with more than 80% of enterprises predicted to have deployed GenAI-enabled applications by 2026. This surge in AI adoption simultaneously creates unprecedented data volumes while offering powerful solutions for managing them more efficiently.

For Australian healthcare organisations, this dual reality presents both challenge and opportunity. Electronic health records, medical imaging, genomic data, and Internet of Medical Things (IoMT) devices collectively generate terabytes of information daily. Yet the same AI technologies driving this data explosion can fundamentally transform how organisations store, govern, and extract value from their information assets. As more and more organisations globally integrate AI into their daily operations and create their own AI agents, the question is no longer whether to automate data management. Rather, it’s how to strategically implement these capabilities to optimise storage, automate enforcement of retention policies, and build scalable systems for the decade ahead. 

Strategic Approaches to Smarter Healthcare Data Storage

Here are three strategic ways healthcare organisations can harness AI and automation to transform data storage, making it smarter, leaner, and future-ready:

1. Automate Information Lifecycle Management to Reduce Redundant Storage and Enforce Retention Policies

Australian healthcare providers face mounting data volumes from sources like electronic medical records(EMRs), high-resolution imaging, and genomic sequencing. This growth not only strains infrastructure but also inflates operational costs. According to PwC, medical costs are projected to rise by 8.5% in 2025 – the steepest increase in over a decade – with data infrastructure contributing significantly to this surge. 

While the Australian Privacy Act requires personal information, including health records, to be retained only as long as necessary and securely destroyed thereafter, jurisdictions such as New South Wales, Victoria, and the Australian Capital Territory (ACT) impose stricter rules. These regions mandate that healthcare records be kept for at least seven years for adults, and until age 25 for minors — overriding the Privacy Act’s general provisions.

AI and automation can help healthcare organisations meet these retention obligations efficiently. Intelligent lifecycle management platforms like that of AvePoint can automatically classify data based on their type and sensitivity, apply jurisdiction-specific retention rules, and securely dispose of these records once their retention period ends. For instance, diagnostic images can be tagged separately from administrative files, ensuring each follows its appropriate schedule.

Automated workflows also reduce the risk of human error, such as missing retention deadlines or deleting records under legal hold, which enables consistent governance across cloud and on-premises environments. By embedding intelligence into backup systems, healthcare IT teams can streamline compliance, minimise redundant storage, and control rising infrastructure costs.

2. Prepare for Scalability Through Smart Data Minimisation

Data minimisation is emerging as a strategic lever in healthcare data management. Under the Privacy Act, healthcare organisations must retain personal information only as long as necessary for legitimate business or legal purposes. Yet many storage systems default to indefinite retention, creating sprawling data estates that are costly and difficult to manage.

AI-powered data management tools like AvePoint Confidence Platform’s Opus can identify and flag redundant, obsolete, or trivial (ROT) data. This unified, purpose-built platform analyses content and usage patterns to detect duplicate records, outdated versions, and files that no longer serve clinical or administrative functions. This goes beyond age-based rules, incorporating context such as access frequency, relevance to ongoing care, and legal obligations, enabling healthcare organisations to sustainably achieve intelligent storage optimisation.

By implementing a smart system that allows them to keep only business-critical data, healthcare organisations can prepare for future growth without proportionally increasing storage infrastructure or compliance overhead. As digital health initiatives expand and patient expectations evolve, scalable data practices will be essential to maintaining operational efficiency.

3. Apply AI for Predictive Storage Planning and Dynamic Capacity Management

Static storage provisioning leaves healthcare IT teams caught between over-investing in unused capacity and scrambling to address unexpected bottlenecks. These conventional strategies can lead to over-provisioning, wasted resources, or sudden capacity shortfalls that disrupt clinical workflows. To stay ahead, organisations need a smarter, adaptive approach that anticipates demand and optimises infrastructure in real time.

AI-powered predictive analytics, available through solutions like the AvePoint Confidence Platform’s tyGraph feature enable healthcare providers to forecast storage needs based on historical trends, usage patterns, and emerging data sources. These insights allow IT teams to plan capacity proactively, allocate resources efficiently, and prevent bottlenecks before they occur. For example, if imaging data spikes during seasonal health campaigns, AI can help organisations adjust storage allocations and prioritise critical workloads without manual intervention.

By integrating predictive planning with automated governance, healthcare organisations can maintain optimal performance without overspending on unused capacity. This approach not only reduces operational costs but also ensures that critical patient data remains accessible when needed, supporting continuity of care and compliance across hybrid environments.

Building Smarter, More Resilient Healthcare Systems

The convergence of data growth and AI innovation is reshaping healthcare technology. Australian organisations that embrace AI and automation for data management can reduce costs, ensure compliance, and lay the groundwork for scalability and future advancements.

The journey begins with assessing current practices, identifying gaps, and deploying intelligent lifecycle management solutions. Those who act now will not only solve today’s storage and governance challenges but also unlock strategic advantages — from faster analytics to improved security and greater agility in adopting emerging technologies.