Why the intelligent smart grid is no longer a future vision, but a present-day necessity

Demanding users, regulators, and energy supply are putting pressure on today’s utilities to rethink how they operate. The traditional one-way power grid is rapidly becoming obsolete. Utilities now have to deal with increasingly complex, decentralised power networks. Intelligent smart grids, powered by Industrial AI, predictive analytics, and IoT, provide utilities with the real-time data, intelligent automation, and workforce augmentation needed to manage them. Global pressures on energy supply and usage are not set to go away anywhere soon. In fact, AI data centre demand, ageing workforces, and the rise of distributed energy resources will just keep mounting. Carol Johnston reports

The centralised one-way generate and deliver power model is fast fading into history, as every day it is challenged by demanding customers and new and even more demanding AI data centres. While the days of a fully autonomous grid are still a way in the future, the intelligent smart grid powered by Industrial AI, predictive analytics and an empowered workforce is very much here today.

It is taking energy and utilities far beyond simple decarbonisation goals – it is improving reliability, affordability, and safety.

Historically, electricity grids were relatively predictable systems. Power flowed in one direction, from centralised generation facilities through transmission and distribution networks to homes and businesses. Utilities owned the assets, controlled the flow, and could largely manage the system through centralised planning and human oversight.

That model no longer exists, and utilities face a whole new set of emerging and worsening threats—rising electricity demand from power-hungry data centres, infrastructure that continues to surpass intended lifecycles, and retiring workforces taking years of tacit knowledge with them.

Welcome to the intelligent smart grids. Defined by the International Energy Agency:“Smart grids are an electricity network that uses digital and other advanced technologies to monitor and manage the transport of electricity from all generation sources to meet the varying electricity demands of end users. It uses all parts of the system as efficiently as possible, minimising costs and environmental impacts while maximising system reliability, resilience, flexibility and stability.”

More goal posts have levelled the energy playing field

Previously, energy pressures have often skewed towards a specific goal. In recent years, sustainability has dominated company agendas as governments and regulators pushed utilities to reduce emissions and accelerate decarbonisation efforts.

Today, there’s a rebalance of priorities stemming from rising energy costs, growing electricity demand from AI-driven data centers, and increasing concerns around grid resilience in light of recent extreme weather events. With growing demand for energy independence, and security in the wake of global geopolitical shifts, the focus is now on reliability, affordability, safety, and sustainability, because globally, unreliable, unstable power isn’t an option.

New DERs mean new complexities, and more to fix in real-time

The rapid rise of Distributed Energy Resources – rooftop solar, battery storage, EV charging, microgrids and decentralised generation – has transformed the grid into a far more dynamic and complex environment. While the utility still owns 80-90% of grid assets, some utilities may now be managing two-way energy flows across assets they do not fully own or control.

The amount of flowing data is too much for humans to consume and take action on alone. An issue out in the field may require a technician to interact with third parties to coordinate access and safety while working on the lines where two-way energy flow exists.

Smart grids can not only make split-second decisions, far quicker than humans could make at such a scale, smart grids can also detect infrequent issues, analyse large amounts of data and make recommendations on corrective actions, even execute actions if authorised to do so without a human in the loop. Automated intelligence capable of processing vast streams of operational data in real time – such as smart devices out in the field – allow utilities to send commands and real-time adjustments to keep the grid running, stable, and harmonised.

There are hurdles along the way – four in particular – that will need to be dealt with, and here is how.

1. Data, data, data… and more big data! But what should utilities do with it?

The utilities sector has never had a lack of data. For decades, the sector has been collecting an overwhelming amount of information from substations, field assets, meters and control systems. The problem has been turning this siloed big data into timely, actionable decisions.

Let IoT do the grunt work – keep human expertise where it matters most!

With IoT and automated smart-grid technology, sifting through this mass of data becomes so much easier. With IoT and automation doing the grunt work, utilities can begin identifying meaningful operational signals hidden within enormous datasets. AI and predictive analytics can sift through huge volumes of operational data, identify patterns, and predict where failures are likely to occur next.

From a workforce perspective, utilities can prioritise work that requires immediate attention while safely deferring others.

2. Locating a starting point – easier said than done

Utilities need to make sure this analysed data is accurate and reliable, but alone this is not enough. Companies must ensure that the data is from the correct sources of data in order to be able to make an informed decision. It’s about identifying the right starting point of data, while ensuring consistent data that is cleaned through good data hygiene.

But the operational benefits are worth it!

It is where technology such as edge devices, smart sensors, an Industrial AI care in the right place and in real time to help with smarter asset management, predictive maintenance, and real-time monitoring. Instead of relying on manual inspections every few years, utilities can use intelligent, connected assets that continuously self-monitor and report issues as they happen. The benefits are two-fold: for reliability, and for safety.

24/7 monitoring and IoT-enabled assets, enables utilities to detect anomalies that humans might miss, especially intermittent faults that only occur under certain conditions.

From a planning perspective, early warning signs for one asset can be extrapolated to raise issues on similar assets for replacement or maintenance, way before issues or downtime occurs. Industrial AI and predictive analytics, then ensure maintenance schedules are continually optimised and assets are repaired or replaced at the right time.

3. Dealing with the  technology brain drain: time to empower the workforce

Utilities are also battling a less visible but equally serious challenge – the loss of institutional knowledge.

Large portions of the experienced workforce are approaching retirement, and utilities are struggling to compete with major technology firms for data scientists, AI specialists, and digital engineers. Unlike hyperscalers and technology giants such as AWS and Google, utilities operate within heavily regulated environments with limited flexibility, which makes recruitment and retention of workers with IT skills increasingly difficult. Moreover, they are also struggling to retain the knowledge of operational staff in the field. Current projections show more than 106,000 professionals are expected to retire in the next five years, the equivalent of a loss of 17% of the UK utilities workforce at large.

It’s not about replacing – it is about augmenting workforce experience!

Utilities are now beginning to explore how AI systems can capture decades of tribal knowledge and make it accessible to newer employees in real-time. Out on the field, it could give less experienced field technicians real-time guidance and step-by-step instructions during complex maintenance procedures. These ready-made tools reduce the need for technical expertise too, with the ability to automatically analyse sounds, images, and observations, compare them against historical data and manuals, and recommend likely fixes.

For example, IFS Resolve calls in digital workers to sift through huge data volumes analyse and flag issues, aid troubleshooting and identify resolutions based on previous repairs. From a wider recruitment perspective, employees become more productive, empowered, and efficient, enabling utilities to do more with fewer people while improving operational decision-making.

4. A distributed IoT-led grid is a vulnerable one: Time to get smart(er) on cybersecurity

With staff shortages, and an increasing amount of workers leaving the industry, reliance on digitally-driven operations has only increased – which only opens the floodgates for cybersecurity attacks.

The more technology introduced, the smarter these assets become – but way more vulnerable. Connected devices, from smart meters to automated substations, introduce additional cybersecurity exposure. As utilities deploy more IoT-enabled infrastructure, cybersecurity is no longer confined to the IT department of a utility – which could compromise entire organisations.

In this day and age, everything is smarter – IT protection needs to be too!

Investing in a solution with embedded advanced security controls is a non-negotiable for navigating today’s smart grid. Utilities must seek an IT solution that can manage user access, enforce segregation of duties (SoD), and maintain compliance across the entire organisation.

From role-based permissions to detailed audit logs, advanced solutions will help utilities reduce cyber risk, prevent fraud, and support regulatory requirements all within a centralised platform.

But none of it will be possible without pairing humans with technology

Utilities will need to be less reactive, and more proactive operationally and from a planning perspective. And remember that energy infrastructure is too critical, too regulated, and too complex to remove humans from decision-making processes.

The technology is there to enable utilities to modernise without compromising reliability, to scale innovation without increasing operational fragility, and to deploy Industrial AI in ways that enhance, rather than replace, human expertise.

The autonomous grid may still be years away, but the smart grid is already here!

Carol Johnston is VP Industries, Energy, Utilities, and Resources, at industrial AI and software IFS.