In the first half of the 2024–25 financial year, electricity consumption in Kenya increased by 278.75 GWh, reaching a total of 5,484.54 GWh. During the same period the previous year, national demand stood at 5,205.79 GWh.
This continued rise in power use reflects growing economic activity, expanding infrastructure, and increased demand across homes, industries, and businesses.
To meet this demand more efficiently, Artificial Intelligence (AI) is becoming an important part of modern electrical engineering.
AI technologies help improve how energy is produced, delivered, and used. They support efforts to cut energy waste, reduce emissions, and improve the reliability of power systems. Here, we discuss how AI in electrical engineering drives energy efficiency in electrical engineering.
Smarter grids with AI
AI powers smart grid technologies that balances electricity supply and demand in real-time. In Kenya, where renewable sources such as solar and wind witness constant expansion, AI algorithms help manage their variable outputs. This smoothens the supply fluctuations and enhances grid stability.
These intelligent grids reduce losses and increase operational efficiency with the analysis of vast amounts of data on consumption patterns, generation rates, and network conditions. These help utilities optimise energy flows and prevent outages.
Predictive maintenance to reduce downtime
One of the most transformative applications of AI in the energy sector is predictive maintenance. Traditional maintenance models rely on fixed schedules or respond only after equipment fails.
In contrast, AI enables a shift toward condition-based maintenance. Using sensors and machine learning algorithms, systems can monitor vibration, temperature, voltage, and other performance indicators to detect anomalies early.
In Kenya, where grid reliability is critical for economic development, this technology holds particular value. Utilities can anticipate failures in transformers, switchgear, or turbines before they escalate. This reduces unplanned outages, avoids high emergency repair costs, and extends the lifespan of infrastructure. According to the International Energy Agency (IEA), AI-based fault detection can reduce outage duration by 30% to 50%. For a growing economy like Kenya’s, where power interruptions carry a high economic cost, these gains are not just operational—they are strategic.
Optimisation of energy use in buildings and industry
AI enhances energy efficiency at the point of use. In commercial buildings and manufacturing plants, AI integrates with smart systems to regulate heating, ventilation, air conditioning (HVAC), and lighting.
These systems learn from occupancy patterns, weather conditions, and historical usage to optimise energy consumption without compromising comfort or productivity.
In Kenya’s urban centres, where commercial real estate and light manufacturing continue to expand, AI adoption reduces energy bills and helps businesses meet regulatory targets.
This supports the goals of Kenya’s Energy Efficiency and Conservation Strategy, which promotes lower carbon intensity and better resource management. Industrial players that operate within export-driven sectors can also gain a competitive edge by aligning with global sustainability standards.
Demand forecast and load management
Energy supply and demand must remain in constant balance. A mismatch can cause blackouts or force utilities to rely on expensive peaking plants.
AI improves this balance by enabling precise, real-time demand forecasting. Machine learning models analyse variables such as weather, historical load data, economic activity, and even social trends to anticipate consumption spikes.
Utilities in Kenya use this insight to implement demand response programmes. These programs encourage users—especially commercial and industrial customers—to reduce or shift consumption during peak hours.
By doing so, they stabilise the grid and lower operating costs. More importantly, demand response helps avoid the need for fossil-fuel-based backup generation, which remains both costly and carbon-intensive. The result is a cleaner, more flexible energy system that aligns with Kenya’s renewable energy ambitions.
Kenya is moving into a new stage of using AI, supported by its push for digital growth. Policymakers and utility leaders must prioritise digital infrastructure, data governance, and cybersecurity to enable this transition. For engineers and energy professionals, continuous skills development is essential.
Familiarity with AI tools, data science principles, and system integration will become vital competencies in the evolving energy landscape.
Kenya’s early investment in renewable energy—particularly in geothermal, wind, and solar—has positioned it as a regional leader. AI now offers the tools to manage this diverse generation mix more effectively. With strategic planning and technical readiness, AI can power Kenya’s journey toward a more reliable, efficient, and sustainable energy future. At Burhani Engineers Ltd, we recognise the impact of smart technology on electrical engineering, and assess how these innovations have the ability to shape the future of the electrical engineering industry.