As digital transformation accelerates, the carbon footprint of computing has become impossible to ignore. From data centres and AI models to inefficient software architectures, digital systems now consume vast energy resources — but smarter coding, algorithmic efficiency, and sustainable infrastructure are rewriting the equation.
These 20 statistics reveal how “green code” — the practice of optimising software for energy efficiency — is reshaping sustainability in tech, helping companies cut costs, emissions, and latency simultaneously.
Market Size
- In 2020, the global green technology and sustainability market size was valued at $10.32 billion and is projected to reach $74.64 billion by 2030 (Allied Market Research, 2021).
- By 2030, the compound annual growth rate for the global green technology and sustainability market size is projected to be 21.9% during the period from 2021 to 2030 (Allied Market Research, 2021).
- In 2023, the global cloud sustainability market size was valued at $24.19 billion and is anticipated to reach $132.85 billion by 2033 (Spherical Insights, 2024).
- During the forecast period of 2023 to 2033 the global cloud sustainability market size is expected to grow at a compound annual growth rate of 18.57% (Spherical Insights, 2024).
Environmental Impact of ICT and Software
- By 2040, the information and communications technology sector is expected to account for 14% of the world's carbon footprint whilst in 2007 it was 1.5% (Harvard Business Review, 2020).
- As of 2025, software accounts for 2.1 - 3.9% of global greenhouse gas emissions (MarkAiCode, 2025).
Energy Efficiency Through Software and Code Optimisation
- Implementing lazy loading can decrease memory usage by 20-40%, reduce initial bundle size by 30-70%, and cut initial load time by 25-45% (MarkAiCode, 2025).
- Using more efficient algorithms can reduce energy consumption by 30-95% for common operations (MarkAiCode, 2025).
- Utilising effective caching strategies can reduce computation time by 50-80%, database load by 40-60%, and server requests by 70-90% (MarkAiCode, 2025).
- Asset optimisation techniques can decrease CPU usage by 25-40%, cut load times by 30-60%, and reduce page size by 40-80% (MarkAiCode, 2025).
- According to the Green Software Foundation the optimisation of code can reduce energy consumption by up to 30% (iDelsoft, 2024).
- A study by the Green Software Foundation found that Rust and C use up to 70% less energy in comparison to interpreted languages like Ruby or Python (bioscore, 2024).
- Modern Java applications that have efficient garbage collection and Just-In-Time compilation can reduce energy consumption by 30-40% (bioscore, 2024).
- On average to execute the same code, Python takes up as much as 76 times more energy than C (DataBeacon, 2023).
Data Center and Infrastructure Energy Consumption
- In 2023, data centers consumed 240-340 terawatt-hours of electricity, which is about 1.0-1.3% of total global energy use (FrontierGroup, 2023).
- By 2030, the electricity demand of the IT sector may reach 3,200 TWh (FrontierGroup, 2023).
- 10% of the global electricity supply will be used by the data centers by 2030 if its optimisation is failed (CASTAi, 2025).
- By 2028, Goldman Sachs analysts expect AI to represent about 19% of data center power demand (Goldman Sachs, 2024).
Investment
- US utilities will need $50 billion in new generation capacity to support data centers (Goldman Sachs, 2024).
- Apple has committed to spend over $500 billion in the US over the next four years in sectors such as AI infrastructure, data centers, and R&D (Data Center Frontier, 2025).
Green coding has evolved from a niche concept into a cornerstone of sustainable computing. As the software and cloud sectors race toward decarbonisation, every line of code and architectural choice carries measurable environmental weight.
