What the Deloitte Tech Trends 2026 mean for the future of New Zealand healthcare

This article was first published in the May 2026, by Tech New Zealand - written by Emily Speight, Associate Director, Deloitte New Zealand.

New Zealand’s healthcare system is operating under increasing structural strain. Workforce shortages persist, while demand for services continues to grow in both volume and complexity. Clinicians describe a system where more time is spent navigating processes rather than actually caring for people. At the same time, public expectations for access, quality, equity, and transparency continue to rise.

Technology has long been positioned as part of the solution to current healthcare challenges. Yet despite decades of digital investment, its impact has largely been slow. Electronic records, portals, and virtual care have improved access and information flow, but they have not fundamentally altered how the system operates or how clinical time is valued.

Tech Trends is Deloitte Global’s annual report exploring emerging technologies that are set to reshape organisations over the next 18–24 months. The 2026 report marks a shift away from technology as an add‑on and toward technology as a structural force. Rather than focusing on individual tools, it describes how leading organisations are rebuilding themselves around artificial intelligence - operationally, architecturally, and culturally. 

This year’s five trends provide a practical framework for thinking about how technology can support a more sustainable, equitable, and human‑centred health system, rather than simply a more digitised one.

1. AI goes physical: Navigating the convergence of AI and robotics

Tech Trends 2026 highlights how AI is moving beyond screens and software into the physical world. AI is increasingly embodied in robots, sensors, computer vision, and ambient technologies that can perceive, reason, and act in real‑world environments. As these technologies mature, their use is expanding into mainstream healthcare contexts.

Globally, healthcare systems and pharmaceutical organisations are combining generative AI with robotics to extend clinical and discovery capabilities far beyond traditional limits. Physical AI is enabling continuous monitoring and subtle intervention at a scale that human workforces cannot sustain alone. This is particularly relevant in aged care, rehabilitation, and rural or remote settings, where workforce shortages and geography add to existing pressures.

Example: Pharmaceutical industry

Some pharmaceutical companies are using generative AI to accelerate drug discovery by scanning existing research, connecting insights across vast knowledge bases, and identifying promising drug candidates - condensing months of analysis into days. These AI insights are then used in highly automated, robotic laboratories, where robots can independently mix compounds, run experiments, analyse results, and adapt the next round of testing in real time. 

2. The agentic reality check: Preparing for a silicon-based workforce

One of the major themes in Tech Trends 2026 is the rise of agentic AI - systems capable of planning, executing, and adapting across multi‑step workflows. The report is clear that organisations will struggle to realise the value of this technology if they simply automate existing processes. True impact comes when work is redesigned and AI agents are treated as a silicon‑based workforce, with appropriate governance, onboarding, and performance management.

Example: Digital teammates

Internationally, healthcare systems are beginning to deploy AI agents as ‘digital teammates’ rather than using isolated tools and chatbots. At the Ottawa Hospital in Canada, an AI‑powered avatar guides patients through pre‑admission preparation, appointment readiness, post‑visit education and assists campus navigation. Operating 24/7 in both French and English, it manages high‑volume coordination and information flows integrating with Electronic Medical Records (EMRs) and other data sources where necessary to improve patient preparedness and reduce administrative burden.

Agentic AI is highly relevant to New Zealand healthcare, where the system’s biggest constraint is human capacity. Agentic AI offers a way to rebalance this equation. Rather than supporting individual tasks, AI agents can manage referrals, scheduling, follow‑ups, documentation, and coordination across primary, secondary, and community care. Clinical accountability remains with humans; the agent manages routine and high‑volume execution, not care decisions.

3. The AI infrastructure reckoning: Optimising compute strategy in the age of inference economics

As AI adoption moves from experimentation to scaled deployment, Tech Trends 2026 points to a shift in cost dynamics. The largest expense is no longer AI model training, but ongoing inference - the day‑to‑day operation of AI systems at scale. This need challenges cloud‑only approaches and forces organisations to reconsider long‑term cost, resilience, and governance. Healthcare must also balance FinOps maturity with heightened requirements for data sovereignty, security, and reliability. 

Example: ‘SuperCloud’ approaches

While hybrid cloud is becoming the norm, many organisations are going a step further by adopting ‘SuperCloud’ approaches. These add a layer over different cloud and on‑premise systems, making it easier to manage costs, governance and operations in one place, even when the underlying technology is spread across multiple environments.

For healthcare, this means placing different types of work where they make the most sense. High-volume, predictable processes can run on more controlled, cost-effective systems, while the cloud can be used when flexibility is needed, such as for innovation or handling spikes in demand.

In New Zealand, infrastructure decisions must also consider the risks associated with ageing on‑premise environments that were not designed for continuous, compute‑intensive workloads. In a small health system with constrained budgets and spread-out services, early and deliberate architecture choices are critical not just for AI performance, but for long‑term resilience and sustainability.

4. The great rebuild: Architecting an AI‑native tech organisation

Rather than layering AI onto legacy systems, Tech Trends 2026 paints a picture of organisations undergoing a fundamental rebuild to become AI‑native. This year marks the point where AI shifts from experimentation to essential infrastructure. In AI‑native organisations, intelligence is designed in, not bolted on.

In healthcare, this shift to being AI-first extends beyond technology teams. Many core workflows remain fragmented, manual, and clinician‑unfriendly. Becoming AI‑native requires rethinking how care is designed, coordinated, measured, and governed. The concept of Zero Operations (Zero Ops) captures this shift. The goal is to reduce non-essential manual processes and operational friction as close to zero as practical, with intelligent systems managing routine work and escalating only when human judgement is required.

Example: Emergency triage

AI‑enabled emergency care models are a great way to picture this approach. Virtual EDs use AI to predict demand, update resource availability in real time, and recommend patient arrival windows based on urgency and capacity. AI agents can also triage patients by analysing symptoms and health information via text or phone to determine urgency and use specific platforms to direct patients to the appropriate clinician. For New Zealand, this represents a credible pathway to improving workforce sustainability by returning time and decision‑making space to clinicians.

5. The AI dilemma: Securing and leveraging AI for cyber defence

This year’s Tech Trends frames security as both a risk and an enabler of AI adoption. AI increases the number of ways cyber threats can get into digital systems, but it also gives organisations better tools to detect and respond to them quickly. This is especially important in healthcare, where patient data is highly sensitive. As AI becomes part of everyday clinical and operational decisions, strong security needs to be built in from the start, not added later.

AI‑enabled cyber defence offers continuous monitoring, anomaly detection, and rapid response capabilities. In healthcare, organisations need to secure AI within operating models that place trustworthy AI at the core to ensure overall security.

Example: GenAI cybersecurity in action

Generative AI is shifting cybersecurity from manual, alert‑driven processes to continuous, context‑aware oversight. Rather than overwhelming teams with disconnected alerts, AI connects signals across systems, explains what is happening and why it matters, and recommends policy‑aligned actions.

In healthcare settings, this enables early detection of suspicious access to patient data and more consistent, auditable responses. 

The future of technology use in healthcare

Taken together, these trends show that technology is becoming part of the fabric of healthcare, not just an added layer. The examples outlined all point to the same goal: reducing friction in the system so the healthcare workforce can focus on care.

For New Zealand, the opportunity lies in using these approaches to address workforce pressure and rising demand in a deliberate way. This is not about automating current processes to allow the system to run faster, but about redesigning how work is done and embracing a hybrid AI-human workforce by design. If applied thoughtfully, AI can help create a system that is more sustainable for clinicians and more responsive to the people it serves.