Navigating AI spectrum in Digital Transformation in ANZ - AI in action

Artificial Intelligence (AI) is transforming how organisations across Australia and New Zealand (ANZ) deliver services, automate operations, and achieve efficiency. But not all AI is the same. Understanding the AI spectrum in digital transformation—from non-agentic AI to agentic workflows and autonomous systems—is critical for public and private sector leaders looking to apply the right solution to the right problem.

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This article explores the AI spectrum in detail, its relevance to digital transformation in ANZ, and how ServiceNow Responsible AI plays a pivotal role in shaping future-ready organisations.

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What is the AI Spectrum?

To fully leverage AI, one must first understand the landscape it occupies. The "AI spectrum" refers to the range of AI capabilities based on their level of autonomy and decision-making. It typically includes three major classifications:

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Non-agentic AI: Fully Human-Directed Intelligence

Non-agentic AI performs narrow tasks based on predefined rules, lacking contextual awareness or goal-setting abilities. These systems are entirely dependent on human prompts to function and are best suited for repetitive, high-volume operations.

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Key Characteristics:

• Executes pre-set instructions
• No understanding of intent or adaptation
• Outputs require human interpretation and action

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Examples: Spam filters, basic chatbots, predictive analytics, image classifiers

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ServiceNow Examples:

• Predictive Intelligence: Uses machine learning to classify incidents or recommend solutions based on past data
• Virtual Agent (Pre-GenAI): Rule-based chatbots navigate FAQ or structured queries
• Document Intelligence: Extracts key fields from forms, but requires manual routing for decisions

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These tools significantly reduce manual work but do not take initiative or adapt without reprogramming.

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Agentic AI: Context-Aware Digital Assistants

Agentic AI systems can pursue predefined goals, delegate subtasks, and make limited decisions. While humans remain in control of critical oversight, these systems proactively act on context and trigger actions within bounded workflows.

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Key Characteristics:

• Operates with a goal-driven logic
• Learns from patterns to improve decisions
• Supports partial automation with human validation

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Examples: Intelligent routing, AI workflow triggers, co-pilot assistants

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ServiceNow Examples:

• Now Assist (GenAI): Conversational assistant that can initiate workflows (e.g., “Create a change request”)
• Flow Designer with AI triggers: Observes system events and initiates actions
• AIOps: Correlates and resolves incidents using system health insights

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This category is the most impactful for mid-stage digital transformations, offering intelligent action with traceable governance.

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Autonomous AI: Adaptive and Self-Directed Systems

Autonomous AI operates independently, able to make decisions, adapt to novel situations, and optimise for objectives without requiring continuous human input.

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Key Characteristics:

• Understands abstract goals
• Uses advanced planning or reinforcement learning
• Responds to open-ended environments in real time

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Examples: Self-driving vehicles, autonomous drones, autonomous service orchestration

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ServiceNow Examples:

• Future AI agents: Capable of cross-platform orchestration (e.g., ITSM + HR + SecOps)
• Reinforcement-learning-based optimisers: Self-tune workflows across complex systems
• Exploratory vision: Moveworks-style agents resolving without escalation

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Though still emerging, this AI class will underpin the next wave of scalable, adaptive digital operations.

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The key distinction lies in the AI's ability to interpret goals, act upon them, and adapt in dynamic environments. The further along the spectrum, the more powerful—and potentially risky—the AI system becomes.

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Why Understanding the AI Spectrum Matters

Many organisations rush to "adopt AI" without understanding the kind they actually need. This often leads to overengineering or, worse, unintended risks such as biased outcomes or unchecked automation. By understanding where each tool falls on the AI spectrum, leaders can:

• Align the right AI type with their operational needs
• Manage risks through human-in-the-loop controls
• Maximise ROI by focusing AI resources where they create true value

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In short, it's not about using the most advanced AI, but using the right AI.

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Benefits of applying AI spectrum in digital transformation

Leveraging the AI spectrum strategically allows organisations to modernise in a phased and responsible manner. Benefits include:

• Targeted automation: Deploy non-agentic AI for repetitive, rules-based tasks without overcomplication.
• Goal-driven augmentation: Use agentic AI to streamline complex workflows such as service management or incident response.
• Future-ready scalability: Explore autonomous AI for scalable solutions like intelligent monitoring or predictive maintenance.
• Risk governance: Apply tiered oversight aligned with the AI's autonomy level, ensuring ethical and human-centred deployment.

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ServiceNow Responsible AI embraces these principles, supporting government and enterprise teams as they walk the tightrope between innovation and integrity.

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AI Applications in digital transformation in ANZ

AI adoption across Australia and New Zealand is accelerating, driven by urgency, innovation, and government mandates to modernise. From non-agentic tools to fully autonomous systems, agencies and enterprises are applying AI thoughtfully across defence, healthcare, and mining.

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Non-Agentic AI in ANZ: Enhancing Human Decision-Making

Non-agentic AI operates as an assistant or tool, relying on human input to act on its outputs. While it lacks autonomy, it plays a foundational role in delivering reliable, explainable results in mission-critical sectors.

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Public Sector – Defence

• The Royal Australian Navy employs machine learning to process sonar data from buoys, accelerating threat detection.
• Defence forces use AI to analyse surveillance and reconnaissance imagery, surfacing objects of interest for human review.
• Predictive maintenance models optimise aircraft engine servicing across air force fleets.

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Public Sector – Healthcare

• Canterbury DHB in New Zealand applies AI to triage radiology images, flagging critical cases for prioritisation.
• AI systems support pathology by identifying cancer cells in microscope slides.
• Hospitals leverage AI to assess patient risk using electronic medical records, supporting clinical decision-making.

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Private Sector – Mining & Resources

• BHP uses AI to analyse telemetry data from trucks and drills, preventing equipment failure through predictive insights.
• Geological modelling powered by AI accelerates exploration and resource identification.
• BHP’s work with Microsoft at the Escondida mine uses AI to optimise ore processing in real-time.

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Agentic AI in ANZ: Automating Workflows with Limited Autonomy

Agentic AI agents act within boundaries, pursuing a defined goal and making decisions within set parameters. These systems collaborate with humans to execute tasks efficiently while adhering to governance protocols.

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Public Sector – Defence

• AI decision-support systems in battlefield environments recommend actions based on tactical data.
• Cybersecurity agents autonomously isolate intrusions or initiate responses to attacks.
• The Defence Digital Group (Australia) uses ServiceNow and intelligent automation (including RPA bots with OCR) for IT and administrative processes.

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Public Sector – Healthcare

• Waitematā DHB's Virtual Health Command Centre monitors patient vitals 24/7 and sends automated alerts.
• Southern Cross Health (NZ) automates insurance claims using AI for straightforward scenarios.
• Hospitals deploy RPA bots for appointment scheduling, billing, and transcription tasks.
• AI-assisted robotic surgery supports surgeons by stabilising instruments and suggesting optimal incisions.

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Private Sector – Mining & Resources

• Autonomous drills align with pre-programmed blasting plans and self-adjust based on surface conditions.
• AI process control at Escondida (Chile) enables dynamic, real-time optimisation.
• AI agents schedule maintenance or order parts based on predictive indicators.
• Computer vision monitors video feeds to detect hazards and trigger emergency protocols—Rio Tinto leads in this space with intelligent mine systems.

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Fully Autonomous AI in ANZ: Pushing the Boundaries

At the far end of the spectrum, fully autonomous AI agents operate independently with minimal intervention. These systems can set sub-goals, adapt to real-time changes, and act on their own in complex environments.

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Public Sector – Defence

• The RAAF’s Loyal Wingman drone operates semi-independently alongside piloted aircraft.
• Autonomous vessels and drone swarms are in experimental phases for surveillance and logistics.
• Military supply chains explore the use of autonomous trucks in high-risk zones.

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Public Sector – Healthcare

• Autonomous delivery robots transport medications and supplies inside hospitals.
• Robotic exoskeletons help rehabilitate patients by dynamically adjusting to user feedback.
• Implanted AI-enabled devices detect cardiac irregularities and deliver real-time interventions.

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Private Sector – Mining & Resources

• BHP and Rio Tinto operate autonomous truck fleets that navigate terrain using GPS, LIDAR, and onboard AI.
• Rio Tinto's AutoHaul system runs fully autonomous iron ore trains across Western Australia.
• In underground mining, autonomous drones and loaders map post-blast environments without exposing humans to risk. These agents operate with minimal human intervention, capable of setting sub-goals and adjusting to complex, dynamic environments.

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Government (Defence)

• The RAAF’s Loyal Wingman drone flies semi-autonomously alongside piloted jets.
• Defence is testing drone swarms, autonomous patrol vessels, and convoy trucks.

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Government (Healthcare)

• Medical robots dispense medication and navigate hospital corridors.
• Exoskeletons aid rehabilitation, adjusting movements in real-time.
• Implanted devices detect and treat conditions like arrhythmias automatically.

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Mining & Resources

• Western Australia’s mining sector leads globally in autonomous truck fleets, including BHP’s Spence mine.
• Rio Tinto operates long-distance autonomous ore trains in Pilbara.
• Underground loaders and drones map conditions post-blast without human entry.

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A roadmap to adopt AI intelligently across the AI spectrum

To ensure that AI adoption is both effective and ethical, organisations in ANZ should follow a progressive model:

1. Assess: Determine your organisation’s readiness, data maturity, and governance frameworks.
2. Apply: Start with low-risk non-agentic AI to drive early wins.
3. Advance: Gradually integrate agentic workflows where human-AI collaboration can thrive.
4. Adapt: Explore autonomous systems where high scalability and low risk intersect—always with governance in mind.

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Remember, Rome wasn’t built in a day. The key is to adopt AI with both ambition and caution.

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Novabridge - a trusted ServiceNow responsible AI partner

At Novabridge, we don't just deploy ServiceNow solutions—we embed ethical, human-centric AI into the heart of your digital transformation. Whether you’re in mining, health, education or government, our team brings:

• Deep technical expertise in ServiceNow Responsible AI modules
• Strategic understanding of ANZ governance and sector-specific challenges
• Empathy-led delivery that puts people first

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With a wide presence in 6 cities of Australia (Sydney, Canberra, Melbourne, Brisbane, Perth) and 2 cities in New Zealand (Wellington and Auckland), we can support ANZ organisations’ AI applications in digital transformation, adapting both New Zealand’s Digital Industry Transformation plan and the Australian Federal Government's framework.

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Conclusion

In the rapidly evolving AI landscape, knowing where your tools sit on the AI spectrum can make all the difference between chaos and clarity. By adopting a principled, spectrum-aware approach, organisations across ANZ can innovate boldly without losing their ethical compass.

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Let Novabridge be your guide in navigating the AI spectrum in digital transformation. The future is closer than you think—and with the right partner, it's within reach.