Embedding AI in Health: What Leaders Need to Know About AI Today
By Michael De Santis, and Dale Bracegirdle, Future Leadership
In five years, AI will be deeply woven into health systems. Leaders who have ignored this moment, or treated AI as superficial hype, will find themselves chasing reactive remediation. Yet proactive leaders, who have built foundations in governance, ethics, data, and culture, will be competitively positioned.
Artificial intelligence (AI) is no longer for the early adopters; it’s a disruptive force reshaping healthcare’s landscape and rendering laggards obsolete. For health leaders, the challenge is urgent: guide AI’s responsible integration while safeguarding patient welfare, clinician trust, and institutional integrity. The days of passive observation are over. Leaders must lead.
As a leadership consultant, drawing on recent Australian and NSW strategic reports, along with industry commentary, here’s how I’d advise health executives to approach AI with clarity and impact:
- Vision & Strategy
- Set a clear ambition: AI as a pillar of mission alignment by 2030.
- Prioritise high-impact use cases (e.g., triage, population health, chronic services).
- Governance & Oversight
- Establish an AI Ethics Committee.
- Implement regular audits, bias reviews, and safety assessments.
- Workforce & Capability
- Launch education programs at scale.
- Recognise clinician innovators through grants and time release.
- Infrastructure & Data
- Invest in secure data lakes and interoperability platforms.
- Engage IT, legal, and privacy teams early.
- Piloting & Scale
- Start small—with pilots co-led by clinical and digital teams.
- Define clear metrics (e.g. time saved, diagnostic accuracy, cost efficiency).
- Culture & Communication
- Celebrate successes and share failures to normalise learning.
- Engage patients on transparency and consent.
If that sounds like a fitting and proactive approach for you, let’s chat further.
For those interested in diving into the unique Health landscape, let’s break down the emerging environment and further explore the promises and perils.
Principled Ambition
A timely piece in Health Services Daily warns of a troubling paradox: the benefits of AI are vast, but so are the stakes for getting it wrong. Missteps, like flawed diagnostics, biased algorithms, or data misuse, risk irreversible harm. How do leaders navigate innovation as it outpaces safeguards?
Here I raise the importance of Principles. Every team should have them. Principles help us navigate the tension of “just because AI could do it, does that mean it should?”
Investments in innovation must go hand-in-hand with enterprise-grade governance: policies, oversight mechanisms, continuous auditing, and ethical review.
Regulatory Momentum: A Double-Edged Sword
Current Australian laws largely encompass AI, but require refinements for clarity and agility, particularly for high-risk healthcare applications. Last week, the Australian Department of Health published its final report, Safe and Responsible AI in Health Care Legislation and Regulation Review. This is a pivotal milestone. It outlines an integrated, multi-pillar strategy across five domains:
- Regulatory clarity – closing legislative gaps.
- Governance frameworks – embedding best practice.
- Capability uplift – training and skills.
- Government as exemplar – leading by example.
- International engagement – aligning with global norms.
The government is contemplating mandatory guardrails, notably for situations that include decision support or automation affecting patient care. Leaders must interpret this not as bureaucratic heavy-handedness, but as alignment, a necessary assurance that ambitious digital transformation is underpinned by legal and ethical legitimacy. It also flags areas requiring proactive attention: consent processes, professional accountability, data stewardship, and clinical responsibility.
Beyond Compliance
Whether in Australia, NSW or internationally, emerging guidance emphasises ethics, governance, and aligned incentives. In NSW, the AI Assessment Framework (AIAF) now underpins all AI deployments, with a dedicated Health AI Taskforce ensuring alignment on clinical governance, safety, legal and ethical standards.
Effective frameworks demand active leadership, not just for technology review, but for culture-shaping. Health services should embed:
- High-integrity data strategies ensuring accuracy and bias mitigation.
- Cross-functional committees blending clinical, legal, ethical, technical and patient perspectives.
- Continuous oversight, from model development to real-world performance monitoring.
- In essence, health leaders must not simply govern AI; they must steward its ethical infusion into care delivery.
NSW Health Strategy: A Model for Innovation-Infused Leadership
In May this year, NSW released its Health Research and Innovation Strategy 2025–2030. For the first time, AI is centrally recognised as a catalyst for system-wide innovation. The strategy sets a collaborative roadmap: bridging government, academia, and industry in a coordinated innovation ecosystem.
Leaders should note several enablers:
- Shared R&D infrastructure, including data linkage and AI testbeds.
- Flexible funding models that reward translational and operational impact.
- Capacity building, not just in data science, but in frontline clinician engagement.
The strategy heralds a shift from siloed pilots to scalable, mission-aligned innovation. Leadership’s role is to steward this shift: empower multidisciplinary collaboration; signal clear priorities; sustain investment; and share early wins to build momentum.
Risks and Realities
Research shows underuse of AI costs both efficiency and clinical opportunity. Yet AI failures like biased output, weak data governance, or poor performance can undermine trust, harm patients, and destabilise adoption. A recent BCG analysis concludes the same: AI isn’t a panacea. Its most powerful effects come from disciplined digital transformation, including clear outcomes, measurable KPIs, and readiness to recalibrate when pilot performance falls short.
Leaders must keep three guardrails in sight:
- Safety-first mindset: every deployment must be risk-assessed and clinically validated.
- Operational discipline: embed AI into workflows with clear ownership, training, and monitoring.
- Adaptive culture: expect failure; learn fast and integrate lessons.
Data as the New Frontier
AI depends on quality data and quality data governance. The Australian review highlights gaps: privacy law, consent mechanisms, My Health Record, and identifiers, all may require amendment. NSW and national strategies echo the need for stewardship.
Future-fit health organisations must invest in:
- Robust privacy and consent models, with clarity on data use, anonymisation, and retention.
- Infrastructure for secure, interoperable data platforms.
- Governance governance – not a double up! A double down, including committees, technical advisors, data stewards, and breach protocols.
Without these, even the most sophisticated AI remains a liability.
Beyond Algorithms
AI isn’t just a clinical tool, it’s a strategic capability reshaping health systems. NSW Strategy places AI at the centre of 10‑year research and investment planning. AI’s inflection extends to operations, population health, chronic disease management, genomics, and social care systems.
Health leaders must resist the narrow view of AI as a hospital-level innovation. Instead, position it for system-level transformation:
- Chronic disease: predictive analytics to guide prevention stratification.
- Workload: automating documentation and triage to free up clinician time.
- Service planning: demand forecasting for equity-focused resource allocation.
- Telehealth: intelligent decision support to boost reach and quality.
The goal is a suite of connected, scalable applications delivering measurable benefits.
Looking Ahead
AI in healthcare isn’t coming, it’s here. As the recent Australian regulatory roadmap puts it, the balancing act between innovation and safety must be proactive and integrated
For health leaders, the time to act is now: lead with clear vision, match it with rigorous governance, empower clinicians, and build the data infrastructure that makes intelligent care possible. Celebrate milestones, but commit to the long game. Leaders who seize this moment won’t just avoid harm; they’ll shape better, smarter, and more inclusive healthcare for the future.
Does your workplace need to embed AI leadership across the organisation? I’d love to have a chat about the challenges and opportunities for capability building.
Michael De Santis is a Partner at Future Leadership and a recognised expert in health system leadership and workforce transformation. This article draws on current trends, national inquiry findings, and Future Leadership’s on-the-ground experience to support health sector leaders in shaping sustainable, future-ready organisations.
Dale heads up the Future Leadership L&D practice. He has extensive leadership development experience in taking executive teams to new levels of performance. Dale is known for his practical and engaging approach to AI-augmented leadership and team effectiveness facilitation, staying ahead of current thinking and critical perspectives with a driven passion for leadership development and wellbeing.
References:
https://www.health.nsw.gov.au/research/Pages/research-and-innovation-strategy.aspx
https://www.health.nsw.gov.au/research/Publications/research-and-innovation-strategy.pdf
