AI in MedTech: EBOS MedTech responds to industry shifts highlighted at MTAA Symposium

Artificial intelligence was front and centre at the AI Revolutionising MedTech Symposium on 19 November in Sydney, hosted by MTAA and APACMed. The event highlighted critical questions about how AI will influence clinical care, data governance and patient outcomes across the region.

Representing EBOS MedTech, Rachel Crimmins, Brett Isaac, Kush Gupta, Zainub Mardawala and Terry Cool contributed insights that cut through the hype and focused on system readiness and ethical adoption.

What Is the Impact of AI on MedTech today?

AI is reshaping clinical workflows, diagnosis and predictive modelling. But as Rachel noted:

“Is the healthcare system prepared for an increase in patient counts due to quicker diagnosis? Are regulatory bodies ready for this acceleration? And are we skipping proper digitisation of records for a catch-all called AI?”

Her comments highlight a key theme: AI succeeds only when systems are prepared for it.

Key Insights from the MTAA symposium

1. Industry collaboration must strengthen

The sector must work together, regulators, industry, clinicians and technology partners, to ensure AI is safe, ethical and sustainable.

2. Legal and regulatory partners are critical enablers

A leading insight came from Brett Isaac, who reframed the conversation:

“The strongest insight today wasn’t about the tech at all. It was the reminder that our legal and regulatory partners are key enablers in unlocking AI value. In a world of personalisation, consent and privacy aren’t hurdles; they’re the foundations that let us safely use data in ways that truly move the dial for our business.”

This reinforced the idea that AI maturity depends as much on governance as on innovation.

3. MTAA’s self-regulation work raises major ecosystem questions

Kush Gupta highlighted that MTAA is developing a self-policing guideline for MedTech, but the industry must address deeper questions:

·       Is the framework being developed only by MedTech, or the full ecosystem?

·       What is the data value chain, and where does AI sit within it?

·       Who benefits from AI-enabled data use—and who decides?

·       How is data security governed across multiple layers and partners?

·        How and by whom is consent collected and managed? Is patient data exposed at every stage—and should it be?

·       How do we ensure AI inputs are accurate, complete and contextualised?

4. Consent frameworks must evolve for AI

As Terry Cool noted:

“What you had consent for five years ago doesn’t mean you have consent to use in this AI world.”

Consent must reflect new forms of data use and risk, especially in patient-facing digital and diagnostic tools.

5. Trust remains a barrier despite the availability of clinical data

Zainub Mardawala highlighted a core tension facing the sector: while clinical data is abundant, trust in AI-generated outputs remains low.

“Although extensive clinical data is accessible for AI development, the healthcare sector continues to struggle with a lack of trust in AI-generated results. Concerns over informed consent, data privacy and security breaches create significant barriers to the responsible and widespread use of AI in clinical settings. These obstacles contribute to a lack of scalability and prevent the development of future-proof solutions. Harmonisation with regulators around the world – and leveraging the foundational work already underway – is a critical starting point.”

Her insights reinforce that AI readiness is not just a technical challenge but a cultural and regulatory one, requiring confidence, transparency and alignment across the entire ecosystem.

6. Strong data foundations remain essential

AI cannot function reliably without:

• Digitised clinical records
• High-quality, interoperable data
• Accurate and context-rich patient information

Many healthcare systems do not yet meet this standard.

7. Human connection still leads to better outcomes

Despite rapid advancement, clinicians remain central to care. As one speaker summarised:

“Technology can enhance systems, but it’s people who create positive outcomes.” - Brett Isaac, EBOS MedTech

A perspective on AI in Healthcare

Aligned to our purpose, we believe AI should:

1. Serve the system, not outpace it
2. Be governed by updated consent, privacy and data-security frameworks
3. Advance through collaboration, not siloed development
4. Prioritise quality, safety and equity over technological speed

AI’s value will be realised only when healthcare systems, regulations and data foundations evolve together.

What Comes Next for MedTech and AI?

The symposium made clear that the future of MedTech will be shaped by:

• Trust
• Transparency
• Strong governance
• Collaboration across sectors

EBOS MedTech will continue to engage with industry bodies, regulators, and partners to advocate for technologies that enhance patient care and support clinicians.

We remain committed to exploring innovations that create positive outcomes and strengthen healthcare systems across our regions, and with Paul Petherbridge now on the MTAA Board, EBOS MedTech is ready to help shape the industry’s next chapter in AI, governance and responsible innovation.