July 27, 2026
For the past few years, artificial intelligence has been a key talking point within healthcare. We’ve seen greater focus on foundations, brilliant proofs-of-concept, enthusiastic clinical pilots, and promising trials of administrative automation.
But as we look to embed AI deeply across healthcare delivery, more organisations are struggling to transition beyond proof of concepts into AI value at scale. Moving from isolated AI pilot to widespread innovation requires more than just solid foundations and good technology. It demands the deliberate alignment of strategy, clinical engagement and robust governance.
To understand exactly where the friction lies, Equal Experts spent six months conducting a comprehensive research piece on the state of AI adoption in Australia. By gathering real-world insights, our research explored what makes AI in healthcare different from previous technology waves and where it is already delivering real value. We published these findings in our report, AI by design in healthcare, with the aim of supporting healthcare organisations with practical guidance, irrespective of their AI maturity.
With evidence from more than 100 digital leaders across Australia’s healthcare landscape, our research indicates that while enthusiasm for AI is high, strategy and governance remain significant challenges.
Healthcare organisations hold some of the most sensitive personal data in society, and so AI initiatives must navigate exceptionally high expectations around privacy, cybersecurity and responsible data use. While this drives a culture of caution around AI, it also sharpens the value case. If AI can demonstrably reduce wait times, improve early detection, streamline administration processes or ease clinician workload, the upside is significant.
However, too many organisations are still treating AI as a standalone IT project, an approach that simply won’t work at scale. Treating it as a traditional IT asset ignores its wide-ranging operational potential and its unique risk profile.
In our discussions with healthcare executives, two major hurdles came up time and again: funding uncertainty and regulatory anxiety.
Balancing AI investment with legacy system demands within tight healthcare budgets remains a key challenge for many organisations. Numerous leaders cited unclear return on investment and resource constraints as the primary blockers for AI at scale.
Compounding this is the frequently changing and high-impact regulatory landscape. Australian AI policy is evolving, requiring an early, proactive focus on safety, explainability, and accountability. The Safe and Responsible AI review from the Australian Government, the AI Clinical Use Guide from the Australian Commission on Safety and Quality in Healthcare, and clarifications to the Therapeutic Goods Administration (TGA) artificial intelligence and medical device software regulation have all impacted how healthcare organisations can use AI.
Further changes are also on the horizon. By December 2026, organisations will also have to explicitly disclose if AI is making decisions about patients and if data is being processed overseas under reforms to the Privacy Act. Violating these frameworks can carry severe penalties and impact ongoing trust.
To lift foundations and break through the pilot bottleneck as well as achieve true innovation at scale, Australian healthcare leaders must shift their thinking. To manage clinical risk and operational requirements effectively, organisations need to move away from traditional silos and treat AI as a whole-of-organisation shift.
Drawing on Equal Experts’ AI in healthcare research and our experience helping heavily regulated organisations navigate complex digital transformations, we have structured a four-part blueprint that integrates robust strategy with real-world execution.
Start by identifying a problem or opportunity where AI could genuinely improve patient care or operational efficiency in a managed way, not just where it’s interesting or where there is a new tool available.
Identifying the right problem to solve is one of the most critical aspects of any AI initiative and something we focus on in our AI Discovery workshops. The goal is to help identify high-impact AI use cases with clear outcomes, such as reducing clinical documentation burdens or improving patient communication and validate them quickly, turning potential into real action.
Clinical buy-in, information security, and operational ownership must be considered from the project’s outset. By establishing solid foundations for data management, AI guiding principles and domains of primary focus from day one, initiatives are collaborative and ready for scale beyond initial pilots.
We demonstrated the value of early organisational alignment when working with a global medical affairs company on their long-term technology transformation. While the organisation looked to modernise its technology for long-term benefits, broader issues around processes, culture and ways of working were hindering progress. By helping the company understand and address these organisational issues first, we ensured the business was better prepared to innovate and build faster in the future.
With access to some of the most sensitive personal data in society, AI initiatives must navigate exceptionally high expectations around privacy and responsible data use. Organisations need to be transparent about how AI models are utilised and clearly demonstrate the human oversight in place as their use of AI grows.
We took this approach in our data governance work with a leading Australian mental health organisation. Partnering with the not-for-profit organisation, we helped it to uncover existing risks, co-create a robust governance framework and plan a practical, realistic roadmap to strengthen governance capabilities over the next year. By putting rigorous standards across data quality, access and governance, we built a foundation of long-term trust with both users and regulators.
Equal Experts also developed a comprehensive AI Governance Framework designed to provide organisations in highly regulated industries with a robust structure for responsibly and securely navigating AI. It includes guidance on governance, risk management, high-level AI stage gates, AI portfolio management, AI Ops and technical architecture.
The biggest misconception in healthcare technology is that governance slows you down. In reality, leaving risk management to the end is what destroys project momentum. Building collaborative processes that put validation, safety parameters, and risk management in place early can accelerate delivery pilots and initial use cases.
We worked with a large Australian superannuation fund to dramatically accelerate its time to market by unblocking bottlenecks in its security architecture and governance processes. By streamlining requirements sharing, stimulating open discussion and introducing a fast-track process for smaller, low-risk projects, the project reduced the average time required for decisions from 12 weeks to just three weeks. This enhanced agility enables the superannuation fund provider to quickly respond to new regulations in the sector, maintain compliance and capitalise on new opportunities.
The era of treating AI as an experimental playground is at an end. As regulatory scrutiny tightens and the demand for operational efficiency grows, the organisations that succeed will be the ones with the strongest strategic and governance foundations.
Is your organisation building an AI strategy, navigating the complexities of governance or ready to move from pilot to scale? Download the full AI by design in healthcare research report to explore more insights or contact the Equal Experts Australia team today to discuss how we can support your organisation.
Ken Gallacher is a commercially savvy, delivery-focused digital executive with over 30 years’ experience leading high-impact transformations, both as a CIO and as a Partner at Big4 consulting firms. Ken brings a wide range of industry experience across healthcare as well as financial services, government, media, education, manufacturing and retail sectors. Connect with Ken on LinkedIn.
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