Powering the future: Why AI-ready systems are now a utility imperative
Australia’s energy and utilities sector is at a defining moment. The shift to renewable energy and growing demand for digital services are speeding up the need for smarter, more flexible technology.
Yet many systems underpinning critical infrastructure—from grid control to billing and customer engagement—are still outdated. In a sector where responsiveness, transparency and integration are nonnegotiable, technical debt has gone from an IT issue to a business risk.
As three forces converge—regulatory urgency, growing investor scrutiny of digital readiness and the rapid adoption of generative AI—2025 is shaping up to be a breaking point. One in which large-scale application modernization is both urgent and achievable.
Infrastructure is at the center of our quality of life. From how we work to how we connect with others. Furthermore, a mix of global and local trends shape the daily lives of Australians.
One of the most urgent challenges is the need to modernize critical energy systems. This issue isn’t new, nor unique to Australia. Around the world, aging infrastructure is becoming too expensive, too inflexible and too risky to maintain in a rapidly evolving environment.
Legacy platforms in Australia—from outage response tools to emissions reporting and asset management systems—are expensive to run and raise incompatibilities. The issues include automation, data sharing and AI integration needed to respond to climate events, policy shifts and rising customer expectations.
The barriers to modernization—cost, complexity and perceived risk—kept many programs stuck in pilot mode. But systems once seen as too sensitive to upgrade can no longer be left behind.
This isn’t just about keeping pace. It’s about securing the future of Australia’s energy infrastructure, ensuring it remains reliable, compliant and capable of supporting the clean energy transition. Transgrid’s recent USD 179 million proposal to overhaul its control room systems is a clear example. The company warned that legacy tools are now “overburdened” and unable to manage the demands of a renewable-heavy grid.
Without urgent upgrades, real-time response to grid events—and overall system resilience—is at risk. Modernizing them isn’t just about “keeping up”—it’s about making sure Australia’s critical energy infrastructure is secure, compliant and future-ready.
One often-overlooked aspect is the mainframe. Despite assumptions that mainframes are fading out, their relevance is growing. Much of the industry’s mission-critical data still resides on them. Modernizing these applications and integrating them with cloud and other systems—is becoming central to energy providers’ digital transformation. At IBM, we’ve seen the value of mainframes firsthand. When modernized and paired with AI, they extend the value of an organization’s data.
Even more telling, according to research from the IBM Institute for Business Value, 79% of IT executives agree that mainframes are equally essential for enabling AI-driven innovation. For the energy sector—where uptime, resilience and security are paramount—modernized mainframe environments offer a trusted, high-performance foundation.
When integrated with cloud platforms and modern development toolchains, they unlock powerful capabilities in automation, analytics and real-time decision-making.
Previously, updating legacy systems required manual reverse-engineering, code rewrites and complex testing. Generative AI is now transforming this equation. AI-powered tools can read legacy code and suggest modern equivalents, generate documentation for previously undocumented systems, map dependencies and automate testing to ensure functional equivalence—all significantly cutting time, cost and risk. They can even assist with migration planning and compliance support, enabling modernization rather than risky rip-and-replace efforts.
In Australia, legacy platforms are actively slowing down key sectors. For instance, the outdated metering systems, still in use across parts of the electricity network, forced utilities such as SA Power Networks to delay the rollout of smart meters well into the 2030s. These delays limit system optimization, real‑time pricing and automated demand response capabilities.
Government agencies echo the same problem: an OpenText study found that 80% of their budget is spent on running systems, including legacy applications and databases—more than in sectors like banking and finance.
What’s critical to understand is that AI and modern platforms now share a symbiotic relationship. Generative AI accelerates modernization by handling labor-intensive and repetitive tasks swiftly and accurately. Meanwhile, only modern, API-first platforms can support advanced capabilities such as predictive maintenance, real-time optimization, customer analytics and emissions forecasting.
You can’t effectively scale one without the other. Organizations that recognize and act are better positioned to drive innovation, increase resilience, and meet the demands of both regulators and customers.
For energy and utility leaders, the question is no longer whether to modernize, but when. With tightening emissions regulations, climate-related disruptions and capital flowing toward digital-first infrastructure, modernization has become a board-level priority.
Legacy systems depend on a shrinking pool of specialists, are hard to integrate and often need expensive workarounds to stay functional. Most importantly, they hold back the full benefits of AI and automation. As use cases such as autonomous dispatch and real-time market optimization grow, organizations still relying on fragmented, on-prem systems risk being left behind.
Legacy infrastructure no longer just burdens IT—it defines the limits of what energy and utility providers can achieve. The breaking point is here. The ones who act now are not going to just keep up. They are going to lead.