This analyst insight provides an overview of how smart grid deployments lead to a sustainable future and which challenges need to be addressed.

Omdia view


Lockdown measures and travel restrictions during the COVID-19 pandemic led to a significant drop in energy consumption and emissions. According to a BP report, energy demand dropped by 4.5% and carbon emissions from energy use fell by 6.3%, the lowest rates since World War II. However, as most economies return to normal, demand for energy gradually rises, resulting in higher prices and increased energy emissions. At the same time, climate change and rising temperatures are among the most critical issues globally. To prevent the effects of climate change, the International Energy Agency requires major economies to transform their energy policies to lower carbon dioxide emissions to near zero by 2050. Omdia believes that, among other solutions and strategies, the adoption of IoT and AI unlocks tremendous opportunities for utility vendors and other businesses to optimize energy consumption, meet their sustainability goals, and maintain costs at relatively low levels.

Legislation as a key driver for achieving energy efficiency

Over the last years, the deployment of renewable energy sources and investments in advanced technologies has been among key strategic priorities for the majority of businesses as a way to achieve sustainable energy transitions and minimize costs. It should be noted that most of these efforts are driven by governments and regulatory bodies that are essentially forcing businesses to meet their social and environmental goals. In many countries, governments and policymakers provide financial incentives to business/energy vendors that embrace novel tools suitable for energy control and implement penalties for those exceeding energy emission levels. These legislations and funding opportunities typically target the electricity and gas sectors. For example, as part of the 20/20/20 initiative, EU member states committed to deploying almost 200 million smart meters for electricity and 45 million smart gas meters by 2020. According to available data from the Department for Business, Energy & Industrial Strategy in Great Britain, published at the end of 2Q21, 25.2 million smart meters were installed in homes and small businesses, increasing 4% over 1Q21. Another report from E-Control, the regulatory body that monitors smart meter rollouts in Austria, reports that 1.8 million smart meters were installed by 2020 and 1.2 million were ordered. It should be noted that not all governments have imposed mandatory deployments and strict deadlines (these countries include Germany and Netherlands). For instance, a press release from EON Germany, an energy supplier, mentions that Germany lags behind other EU countries like Sweden, and only 20,000 smart meters were installed by the provider across the country in 2020. Countries in the eastern EU are slower in smart meter deployments owing to budget constraints, theft concerns, and lack of specific law frameworks.

Electricity smart meter deployments across different countries are particularly important because they lay the groundwork for broader energy grid digitization. This evolution of the energy grid allows utilities and governments to address some of the energy sector’s current challenges and promote green and clean energy solutions. At the same time, smart grids unlock opportunities for customers to have better control over their energy consumption and costs.

IoT and AI are fundamental technologies for upgrading grid infrastructure

The shift from traditional grids into intelligent grids requires a series of cutting-edge technologies, including IoT (and more specifically smart meters) combined with AI and predictive analytics. This confluence of technologies is essential for two-way communication between all system parts and enabling automatic energy distribution while maintaining a balance in supply and demand.

A high-level way to envision this is IoT systems employing a range of connected sensors can gather data about real-time environmental conditions and the energy performance at any point of the energy distribution chain. After data collection, AI algorithms analyze the collected data to quickly predict demand and determine optimal distribution levels to prevent grid congestion and minimize transmission costs. Also, by introducing intelligence into the grid, utilities not only have enhanced visibility and control but are also able to properly determine energy availability from alternative power resources, including sustainable, renewable technologies. For instance, IoT sensors that report real-time weather information can work with AI to predict energy availability in the near future. As an example, data analytics solutions that examine wind speeds analysis can predict the kilowatts that can be produced.

Barriers to overcome

To achieve the full potential of IoT and AI solutions within the energy sector, some key barriers need to be addressed in terms of deployment cost, connectivity, interoperability, and security.

In terms of deployment costs, it is important to note that large-scale smart meter deployments are a costly process with a long-term ROI, making utility vendors hesitant to replace old equipment unless they are incentivized or required by regulation. In both situations, governments can play a major role. For example, government initiatives that provide either funding or tax relief to utilities, allowing them to essentially offset the cost of their smart grid deployments, have helped spur widescale smart meter deployments in many countries, including the US.  In some other countries, utility suppliers are state-owned, so they can absorb the deployment cost.

Another important issue that needs to be solved for scaled smart grid deployments is the interoperability of different types of connected devices and communication networks. The ultimate efficiency of the smart grid depends on the capability of connected devices and systems to communicate and exchange information securely. Therefore, the development of standards and frameworks is essential.

Besides network infrastructure, cost barriers, and interoperability, security is another major concern. Intelligent grid and smart meters can capture data that give rise to privacy concerns and discourage customers from consenting to have smart meters installed or sharing their data. Also, like any other network-connected system, cybersecurity IoT attacks are a challenge for many utility vendors, which are usually not experienced in IT cybersecurity solutions. According to the World Economic Forum, large-scale cyber-attacks focused on utilities are fifth on the list among the risks most likely to occur in the next 10 years. A potential cybersecurity attack could jeopardize an entire grid’s functionality, and in turn, pose local and national security risks. Therefore, end-to-end security solutions and practices (like antivirus, network security, and firewalls) and regulations like the GDPR are essential to protecting customers and ensuring the reliability of the digital grid.

Future outlook

Smart grid deployments, enabled by technological advancements in IoT and AI, are essential to overcoming the challenges of today’s landscape with rising energy prices and reduced energy emission goals. According to a survey conducted by Omdia in January 2021, the global COVID-19 pandemic did pause smart meter installations in countries like the UK and Italy, which planned scaled rollouts. However, this impact is expected to be short term, and as economies return to normal, smart meter deployments will continue growing worldwide, reaching 79 million units by 2024.


Further reading

Utility Meter Market Survey – January 2021 (January 2021)

IoT Application Analysis, Utility Meters – 2021 (March 2021)

“Energy efficiency in industry: Different approaches for the same goals” (March 2019)


Eleftheria Kouri, Senior Analyst, IoT