How AI and Automation Are Driving Operational Gains in New Zealand Utilities

New Zealand utilities are no longer waiting on transformation. Increasingly, organisations are using AI and data-driven tools to improve field operations, strengthen resilience, and reduce operational bottlenecks.

This shift is practical, measurable, and grounded in real activity. The utilities industry operators implementing these capabilities are seeing immediate operational improvements: reduced rework, faster inspections, better asset visibility, and more efficient crew deployment.

Below is a snapshot of how utilities in Aotearoa are improving scheduling, maintenance, and decision-making through automation, and what this means for your organisation.

1. Automation in Field Scheduling and Crew Operations

Across the sector, utilities are beginning to adopt intelligent scheduling and workforce management tools to improve crew deployment and service delivery. The driver is clear: 30-50% of manually scheduled field jobs contain flaws that need fixing before work can begin, and manual schedulers spend 4-7 hours weekly building schedules that AI can generate in minutes.

Automated field scheduling platforms optimise:

• Crew assignments based on skills and certifications - ensuring the right technician with the right qualifications arrives at each job

• Job sequencing and routing to minimise travel time - reducing fuel costs and maximising productive field hours

• Real-time updates for dynamic conditions and emergencies - allowing rapid response to changing priorities without manual intervention

This reduces rework and wasted hours, the same operational gains highlighted in the previous automation snapshot, and supports more predictable field operations. Rather than relying on schedulers' institutional knowledge or manual spreadsheets, AI evaluates hundreds of variables simultaneously to match crews, equipment, and job requirements optimally.

These tools also provide operational visibility that manual processes lack, helping utilities identify patterns and bottlenecks before they become systemic issues. When scheduling data is aggregated and analysed, it reveals inefficiencies that were previously hidden: certain job types that consistently overrun estimates, geographic areas with disproportionate rework rates, or skill gaps that need addressing through training or hiring.

Early implementations are already showing results. Utilities using automated scheduling report crews spending 65% of their time on jobs, compared to just 44% with manual scheduling, a productivity increase that directly impacts service delivery and cost management.

2. AI-Enabled Asset Inspection and Maintenance

In one of New Zealand's most collaborative efforts, major electricity distributors including Northpower, Orion Group, Unison Networks and WEL Networks have partnered with an AI platform for grid asset inspection and maintenance.

This initiative uses drones and image-based machine learning to rapidly inspect assets such as poles and lines across large networks. In early results, utilities have dramatically shortened inspection times, from 30–45 minutes per inspection to as little as 5–7 minutes in some instances, enabling crews to focus on higher-value work.

This isn't just about speed. The AI analyses thousands of images to detect anomalies that human inspectors might miss or that would require dangerous manual pole climbing to identify. Thermal imaging identifies overheating components. Visual analysis flags corrosion, vegetation encroachment, or structural degradation at scale.

Early detection of potential issues can reduce unplanned outages, improve safety for field teams, and extend asset life, all critical in a landscape where demand and reliability pressures are rising. With NZ electricity demand projected to grow 35-82% by 2050 and much of the existing infrastructure already aging, proactive maintenance becomes essential rather than optional.

The collaborative approach taken by these four utilities also demonstrates an important principle: sharing learnings and platforms across the industry accelerates progress for everyone while reducing individual implementation risk.

3. Digitalisation Strategy at Industry Level

Beyond individual organisations, the Electricity Authority is actively engaging the sector on how data and technology could shape the future electricity system in New Zealand.

The Authority's work recognises that a more data-driven and technology-enabled electricity system underpins efficient, reliable service delivery and supports consumer participation in a smarter grid. This includes exploring how better data sharing between utilities, retailers, and consumers can enable demand response programs, distributed energy resource integration, and more dynamic pricing mechanisms.

That industry-wide focus is an indicator that utilities cannot treat digital transformation as a siloed program, it's integral to operational resilience and future planning. The regulatory environment is evolving to support, and in some cases require, greater digitalisation and transparency.

For individual utilities, this means investments in automation and AI are not just operational improvements, they're strategic positioning for a regulatory and market environment that will increasingly expect real-time data, transparent reporting, and sophisticated demand management capabilities.

4. Broader Digital Transformation Examples in NZ Utilities

Some organisations are applying modern cloud and analytics platforms to improve operational reporting, asset lifecycle management, and decision support:

Meridian Energy has modernised core systems with unified cloud platforms, enabling faster, more accurate reporting and streamlined procurement and planning processes. This kind of foundational infrastructure upgrade creates the data environment that AI and automation require to function effectively.

When asset data, work orders, inventory systems, and financial platforms are integrated on modern cloud infrastructure, utilities gain:

• Single source of truth for operational data, eliminating conflicting information across systems

• Real-time analytics that surface issues before they become crises

• Scalable infrastructure that can accommodate growing data volumes as IoT sensors and monitoring systems expand

• Secure, auditable data flows that meet regulatory and compliance requirements

These aren't fringe experiments, they're foundational upgrades that improve visibility, operational control, and long-term planning capability. They also create the technical foundation that makes advanced automation possible.

5. What NZ Utilities Are Learning from Early Implementations

From these early real-world efforts, a few operational lessons are emerging that can guide other utilities considering similar investments:

Practical Takeaways

Focus on specific operational pain points first

Scheduling, inspections, and maintenance workflows are excellent starting points for automation because they deliver measurable gains with limited risk. Rather than attempting enterprise-wide transformation, successful utilities identify the single biggest source of operational inefficiency and address it systematically.

Data quality and integration are essential

Reliable crew, asset and operational data is a prerequisite for meaningful automation outcomes. If your asset register is outdated, crew certifications aren't current, or job history data is fragmented across disconnected systems, AI will amplify these problems rather than solve them. Data readiness assessments, conducted before automation projects begin, prevent costly false starts.

Governance and human oversight must be built in

AI and automation in critical infrastructure require transparent decision logic, clear accountability, and secure integration, not just faster outcomes. Operators must be able to override AI recommendations when context demands it. Decision-making processes must be auditable for regulatory compliance. These governance structures should be designed at the same time as the technical implementation, not added later.

Security can't be an afterthought

Systems that touch scheduling, asset data, and network planning expand integration points. Cyberattacks on electrical substations jumped 70% in one year - a reminder that every new system connection is a potential vulnerability. A security-first architecture ensures automation strengthens operations rather than exposing risk.

This means conducting security assessments during vendor selection, implementing role-based access controls, encrypting data in transit and at rest, and establishing monitoring for anomalous system behaviour.

6. What This Means for Your Utility

AI and automation in New Zealand utilities are being used now to:

• Reduce manual rework in field operations - recovering hundreds of hours monthly

• Improve inspection outcomes and risk visibility - identifying issues before they cause outages

• Support smarter planning and regulatory reporting - meeting compliance requirements efficiently

• Enable digitalisation across operations - creating foundations for future capabilities

More importantly, the early adopters demonstrate that automation can deliver operational gains without compromising governance or security, when implemented with structure and oversight.

The competitive gap is widening. Utilities that systematically adopt automation are building advantages in efficiency, reliability, and workforce productivity that compound over time. Those still relying entirely on manual processes face mounting pressure from aging infrastructure, workforce constraints, and rising customer expectations.

Start With a Clear Operational Focus

Not every utility needs to transform every process at once. The most successful approaches begin with high-impact areas like scheduling and inspections, invest in data readiness, and embed governance and security controls from the outset.

The New Zealand examples highlighted here share a common thread: they started with clear operational objectives, measured outcomes rigorously, and scaled based on proven results.

If you're exploring how AI and automation can deliver measurable results in your operations - safely and strategically - start with an AI readiness and governance discussion tailored to utilities.

Book a Free AI Readiness Consultation →

Key Takeaways

• Major NZ utilities (Northpower, Orion, Unison, WEL) using AI for asset inspections -cutting times from 30-45 min to 5-7 min

• 65% crew utilisation with AI scheduling vs 44% with manual processes

• Electricity Authority driving industry-wide digitalisation - transformation is strategic, not optional

• Meridian Energy modernised core systems with cloud platforms for operational control

• Data quality, governance, and security must be built in from day one

• Start with high-impact pain points like scheduling and inspections