The energy sector is navigating a once-in-a-century transformation. A value chain originally designed for the simple, unidirectional flow of electricity is rapidly shifting to a highly complex, multidirectional, and dynamic environment.
Right now, Australia and New Zealand are on the frontline of this disruption, with Australia, in particular, facing the challenges of scale and decentralisation earlier and more acutely than most other markets.
In Australia, data centre consumption is forecast to increase 25.1% every year. To keep up with this demand and meet aggressive renewable energy targets, the industry must build out capacity at speed and scale.
Simultaneously, Australia must find a way to efficiently manage what is already the world’s most decentralised grid. With 40% of Australian homes generating their own power from rooftop solar panels, the focus is shifting to storage. Following the launch of a federal subsidy scheme in 2025, households, small businesses, and community organisations installed 300,000 batteries in nine months—a figure anticipated to reach 2 million by 2030. Orchestrating this massive network of connected devices is key to unlocking flexibility in the new energy system.
Managing all this growth and complexity through traditional hiring is impossible. The transition to renewable energy alone is forecast to require an additional 59,300 workers by 2030, in a market already facing a shortage of skilled resources.
To survive and thrive, energy and utilities companies must fundamentally change how they operate by embracing the Agentic Enterprise and adopting a hybrid workforce. By pairing human expertise with autonomous AI agents capable of reasoning, adapting, and executing complex workflows, the industry can finally decouple massive operational growth from headcount.
Let’s dive further into the three imperatives driving the need for transformation, including unprecedented speed and scale, customer flexibility, and increasing operational resilience. We’ll also explore what the hybrid workforce looks like in action across the value chain.
Imperative 1: Unprecedented speed and scale
The energy industry is facing a massive infrastructure bottleneck. To hit the Australian Government’s target of an 82% renewable grid by 2030, an unprecedented build-out of new infrastructure is required.
When you compound this with the surging power demand from data centres and the complexities of managing electrification, the mandate is clear: energy and utility companies must plan, build, and connect at a velocity that manual processes simply cannot sustain.
This is where a hybrid workforce becomes essential. For example, AI agents can help to identify and eliminate manual bottlenecks. They can autonomously process grid connection applications and perform complex capacity analyses. They can also manage supply chain requests for quotes (RFQs) and supplier qualifications, reducing procurement cycle times and deployment delays.
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Imperative 2: Customer flexibility and simplification
The adoption of new energy technologies is completely reshaping the grid and the relationship customers have with their energy provider. Households and businesses are adopting rooftop solar and batteries at record speeds. Over 40% of Australian households already generate their own solar power. With electric vehicles (EVs) forecast to add another 6.5 TWh of annual consumption to the grid by 2030, everyday ratepayers are transforming into prosumers.
Navigating this new reality is complex. Customers are struggling with affordability and are being asked to shift from a simple, low-engagement experience to the electrification journey, with active participation in a dynamic energy system. Even for energy experts, managing these moving parts creates a massive cognitive load.
In a hybrid workforce, AI agents can act as an ‘Energy Concierge’ and simplify the prosumer experience. Imagine an AI agent that manages the customer’s enrollment and participation in a Virtual Power Plant (VPP). The agent can identify events such as a midday solar spike and seamlessly negotiate with a customer’s smart battery agent to store excess energy and sell it back to the grid.
Ultimately, the agent creates the simple, automated, and trusted experience customers actually want while unlocking demand flexibility.
Imperative 3: Increasing operational resilience
The legacy grid is becoming increasingly fragile, threatened not only by aging assets but also by extreme weather events. We are seeing examples of this vulnerability play out in real time. Aging infrastructure is failing; Australia’s coal-fired power plants suffered 119 combined breakdowns over just six months in 2025. At the same time, extreme weather is causing widespread disruption, as when Cyclone Gabrielle in New Zealand left nearly 240,000 customers without power.
To maintain system resilience, energy and utilities companies must move away from reactive maintenance and transform field operations. AI agents can help by providing human experts wiith insights to predict and prevent failure.
For example, by unifying real-time operational signals with inputs such as weather forecasts, agents can monitor asset health to identify and resolve issues before they escalate into major problems.
When unavoidable emergencies do occur, agents can autonomously correlate SCADA alarms, smart meter data, and customer calls to get to the root cause faster. Agents can also as an expert partner to field teams, autonomously coordinating emergency mutual aid, deploying crews, and optimising restoration sequencing to reduce Mean Time to Repair (MTTR).
Unlocking trapped value of data to power AI agents
These three imperatives demand an architecture that legacy, siloed systems were never designed to deliver. A hybrid workforce needs what any high-performing workforce needs — trusted data, proven processes, clear guardrails, and the right tools at hand. The shift is in how that capability is consumed. Humans work through interfaces; agents work through APIs. Any system that cannot expose its capability as a tool is invisible to the agent workforce. Headless-first is no longer an architectural preference; it’s the precondition for participating in the agentic enterprise.
For most energy retailers and network businesses, the existing stack falls short of this test. The CRM holds the customer, EAM holds the asset, ERP holds the market data, ADMS holds the network and billing sits apart from all of it. Each integration between these systems was built to solve a specific problem at a specific point in time — none of them were built for an agent that needs to reason across the full picture in real time.
The path forward is not a wholesale rebuild. It is a unified agentic layer that activates the data and systems already in place. The Salesforce platform delivers this through four tightly integrated systems, each addressing a distinct part of what a hybrid workforce needs to operate at scale.
Key components of an agentic architecture:
- A system of context (Data): The trusted data layer that delivers the right data, at the right moment, for every agent action. It must federate the existing data estate — meter data, data warehouses, finance systems and OT historians — without forcing migration; resolve identity across NMIs, ABNs and site hierarchies; manage data quality, master data and lineage to a regulator-grade standard; and provide the real-time connectivity and API governance that keeps data moving across customer, stakeholder, field, asset, and market-facing systems.
- A system of work (Processes): The encoded business logic and workflows agents must inherit — bill cycles, grid connections, market reconciliations, field dispatch — across sales, service, revenue, marketing and industry-specific processes. Built on shared metadata and a shared automation engine, with industry accelerators for electricity and gas market scenarios, so agents operate within the same approval chains, pricing engines, and tariff logic that humans already use, rather than rediscovering or approximating them.
- A system of agency (Agentic Orchestration): Where agents are designed, governed and run. The full spectrum of agent types — conversational, proactive, ambient, autonomous and collaborative — covers the surface area of energy and utilities operations. Every interaction passes through a trust layer for PII masking, behavioural guardrails and full audit, with deterministic controls on regulated processes. A control plane brings agents from any vendor under one identity chain, one policy model and one observability plane, using open standards (MCP and A2A) to coordinate them — ensuring every agent only executes the actions for which it is authorised.
- A system of engagement (Channels): Where humans and agents converge — unified customer channels, and a collaboration surface where teams swarm complex issues alongside agents. Crucially, every platform capability must be exposed as an API, MCP tool or CLI command, so agents can act inside the field service app, the network operator console, voice IVR, WhatsApp, or any MCP-compatible client, including ChatGPT, Claude and Gemini. The conversation becomes the interface. The platform doesn’t change — only the surface does.
Most vendors can give you one of these capabilities. Some can give you two. Pre-integrated platforms such as Salesforce deliver all four, already wired together, so energy and utilities companies can deploy a hybrid workforce in months, not years, without an all-encompassing system overhaul.
Stop piloting AI. Start elevating your workforce with agents.
Agentforce can help you build your hybrid workforce, unlocking limitless digital labour and freeing your team to focus on what matters: pioneering new energy services, building community trust, and accelerating the path to net zero.
A complete, extensible and open platform, Agentforce lets you build and deploy agents that work 24/7 to help you handle high-volume, repetitive, and data-heavy tasks, such as managing grid connection requests, and VPP enrollments.
Powered by Data 360, Agentforce connects to real-time data across your entire enterprise—from legacy billing systems to grid-edge operational signals—without creating new silos. This unified foundation empowers agents to act as trusted energy advisors for your customers and expert assistants for your field teams, delivering measurable efficiency and safety outcomes across the value chain.
Getting started: Your Guide to the Agentic Enterprise for Energy & Utilities
Download our industry white paper to explore:
- The AI Maturity Model: Evaluate your progress along the AI maturity curve, from basic automation to multi-agent orchestration.
- The Agentic Architecture Blueprint: Learn how to construct a trusted and effective agentic architecture.
- The Four R’s of Workforce Transformation: Gain practical tips for integrating agents into your team structure and building a hybrid workforce.
