Australia’s utility sector accounts for some 43.1% of the country’s carbon footprint, and some 37.2% of its direct emissions, new research from Edith Cowan University (ECU) has revealed.

Dr. Soheil Kazemian, from the ECU School of Business and Law, said the utilities sector included electricity generation, transmission and distribution, gas supply, water supply and waste collection and treatment.

Electricity generation and transmission were identified as the most significant contributors within the utilities sector, with commercial services and manufacturing emerging as substantial sources of embodied emissions within the sector.

The research, published in the Management of Environmental Quality: An International Journal, revealed that 71% of embodied emissions were attributed to electricity transmission, distribution, on-selling electricity, and electricity market operation. Electricity generation accounted for a further 15%, while gas supply accounted for 5%, water supply for 4%, and waste services and treatment for the remaining 5% of embodied emissions in the sector.

“The study highlights electricity transmission and generation as the subsectors with the highest potential for adopting low-carbon technologies. By pinpointing emission hotspots and offering detailed sectoral disaggregation, the results of the research provide actionable insights for prioritizing investment in emissions reduction strategies, advancing Australia’s sustainability goals and supporting global climate change mitigation,” Dr. Kazemian said.

He said that as with any other business, the pressure to reduce the carbon emissions footprint of the utility sector would need to originate from the consumer sector.

Unlike other sectors, however, increased investment into the utilities sector is likely to result in a smaller carbon footprint.

“This is a major difference between the different sectors in Australia. If you invest more in mining, that means the carbon footprint from that industry would increase, and the same can be said for manufacturing as the investment would result in expanded business.

“While new infrastructure development can generate temporary increases in emissions for the utility sector during construction, the long-term impact depends on where those dollars are spent. Investment in renewable energy systems or efficient delivery networks can significantly cut emissions, whereas continuing to fund carbon-intensive energy sources risks locking in higher emissions for decades to come.

“This complexity highlights a critical point that meaningful decarbonization will depend not only on policy or technology, but also on consumer choices. When households and businesses demand cleaner energy, utilities are more likely to channel investment into low-carbon solutions. By consciously choosing renewable energy options and supporting sustainable providers, consumers can send a powerful market signal that accelerates the transition to a cleaner grid,” Dr. Kazemian said.

While the AI genie is out of the bottle for organisations for all sizes, only 13% of businesses are fully prepared for it, with those ready as much as four times more likely to move pilots into production and 50% more likely to see measurable value, according to a study by Cisco.

The data comes from the Cisco AI readiness index 2025, a global study, now in its third year, based on a double-blind survey of 8,000 senior IT and business leaders responsible for AI strategy at organisations with more than 500 employees across 26 industries across 30 markets.

Cisco added that the combination of foresight and foundation is delivering real, tangible results at a time when two major forces are starting to reshape the landscape: AI agents, which raise the bar for scale, security and governance; and AI infrastructure debt, the early warning signs of hidden bottlenecks that threaten to erode long-term value.

Regarding AI agents, the survey found ambition was outpacing readiness. Overall, 83% of organisations planned to deploy AI agents, and nearly 40% expected them to work alongside employees within a year. But the study discovered that, for majority of these companies, AI agents were exposing weak foundations – that is, systems that can barely handle reactive, task-based AI, let alone AI systems that act autonomously and learn continuously. More than half (54%) of respondents said their networks can’t scale for complexity or data volume and just 15% describe their networks as flexible or adaptable.

AI infrastructure debt was called the modern evolution of technical and digital debt that once held back digital transformation. Moreover, the survey regarded it as “the silent accumulation of compromises, deferred upgrades, and underfunded architecture that erodes the value of AI over time”. Some 62% of firms expect workloads to rise by over 30% within three years, 64% struggle to centralise data, only 26% said that they have robust GPU capacity and fewer than one in three could detect or prevent AI-specific threats.

Among the topline results from the report were that “small but consistent” group of companies surveyed – falling into the category of pacesetters, and making up about 13% of organisations for the past three years – were outperforming their peers across every measure of AI value.

Cisco noted that the pacesetters’ sustained advantage indicated a new form of resilience: a disciplined, system-level approach that balances strategic drivers with the data and network infrastructure needed to keep pace with AI’s accelerating evolution. It added that such firms were already architecting for the future, with 98% designing their networks for the growth, scale and complexity of AI, compared with 46% overall.

The research outlined a pattern among companies delivering real returns: they make AI part of the business, not a side project; they build infrastructure that’s ready to grow; they move pilots into production; they measure what matters; and they turn security into strength.

Virtually all pacesetters (99%) were found to have a defined AI roadmap (vs 58% overall), and 91% (vs 35%) had a change-management plan. Budgets match intent, with 79% making AI the top investment priority (vs 24%), and 96% with short- and long-term funding strategies (vs 43%). The study noted that such firms architect for the always-on AI era. Some 71% of pacesetters said that their networks were fully flexible and can scale instantly for any AI project (vs 15% overall), and 77% are investing in new datacentre capacity within the next 12 months (vs 43%).

Just over three-fifths had what was defined as a “mature, repeatable” innovation process for generating and scaling AI use cases (versus 13% overall), and three-quarters (77%) had already finalised those use cases (versus 18%). Some 95% track the impact of their AI investments – three times higher than others – and 71% were confident their use cases will generate new revenue streams, more than double the overall average. Meanwhile, 87% were highly aware of AI-specific threats (versus 42% overall), 62% integrated AI into their security and identity systems (versus 29%), and 75% were fully equipped to control and secure AI agents (versus 31%).

The result of this approach, said Cisco, was that pacesetters achieve more widespread results than their peers because of this approach, with 90% reporting gains in profitability, productivity and innovation, compared with around 60% overall.

Commenting on the results from the survey, Cisco president and chief product officer Jeetu Patel stated that the AI readiness index makes one thing clear: AI doesn’t fail – readiness fails, adding: “The most AI-ready organisations – the pacesetters from our research – prove it. They’re four times more likely to move pilots into production and 50% more likely to realise measurable value. So, with more than 80% of organisations we surveyed about to deploy AI agents, these new findings confirm readiness, discipline and action are key to unlocking value.”