Commercial uses of AI have expanded steadily in recent years across finance, healthcare, education and other sectors. Energy systems need AI, too.

Today, almost 60% of people worldwide have access to the internet via an ever-increasing number of electronic devices. And as internet usage grows, so does data generation, writes Daria Bierla Gazzola, digital communications officer at IRENA.

Data keeps growing at unprecedented rates, increasingly exceeding the abilities of any human being to analyse it and discover its underlying structures.

Yet data is knowledge. This is where artificial intelligence (AI) comes in. Today’s high-speed computing systems can “learn” from experience and, thus, effectively replicate human decision-making.

Besides holding its own among global chess champions, AI aids in converting unstructured data into actionable knowledge. At the same time, it enables the creation of even more insightful AI – a win-win for all. However, this doesn’t happen without challenges along the way.

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Commercial uses of AI have expanded steadily in recent years across finance, healthcare, education and other sectors. Now, with COVID-19 lockdowns and travel restrictions, many countries have turned to innovative technologies to halt the spread of the virus.

The pandemic, therefore, has further accelerated the global AI expansion trend.

Energy systems need AI, too.

Rapidly evolving smart technology is helping to make power generation and distribution more efficient and sustainable. AI and the Big Data that drives it have become an absolute necessity.  Beyond just facilitating and optimising, these are now the basic tools for fast, smart decision making.

With the accelerating shift to renewable power sources, AI can help to reduce operating costs and boost efficiency. Crucially, AI-driven “smart grids” can manage variable supply, helping to maximise the use of solar and wind power.

Read more in IRENA’s Innovation Toolbox.

Risks must be managed to maximise the benefits.

AI usage in the energy sector faces expertise-related and financial constraints.

Decision makers, lacking specialised knowledge, struggle to appreciate the wide-ranging benefits of smart system management. In this respect, energy leaders have proven more conservative than those in other sectors, such as healthcare.

Meanwhile, installing powerful AI tools without prior experience brings considerable risks. Data loss, poor customisation, system failures, unauthorised access – all these errors can bring enormous costs.

Yet like it or not, interconnected devices are on the rise.

What does this all mean for the average consumer?

Smart phones, smart meters and smart plugs, connected thermostats, boilers and smart charging stations have become familiar, everyday items. Together, such devices can form the modern “smart home”, ideally powered by rooftop solar panels.

AI can help all of us, the world’s energy consumers, become prosumers, producing and storing our own energy and interacting actively with the wider market. Our data-driven devices, in turn, will spawn more data, which helps to scale up renewables and maximise system efficiency.

But home data collection raises privacy concerns. Consumers must be clearly informed about how their data is used, and by whom. Data security must be guaranteed. Consumer privacy regulations must be defined and followed, with cybersecurity protocols in place to prevent data theft.

Is the future of AI applications in energy bright?

Indeed, the outlook is glowing, but only if policy makers and societies strike the right balance between innovation and risk to ensure a healthy, smart and sustainable future.

Much about AI remains to be learned. As its use inevitably expands in the energy sector, it cannot be allowed to work for the benefit of only a few. Clear strategies need to be put in place to manage the AI use for the good of all.