<p>Carbon dioxide emission mitigation is more essential to prevent global warming and to promote a low-carbon economy. The primary source of climate change is carbon dioxide emissions. Due to the increase in carbon dioxide emission the problems arises are extreme changes in weather, rise of sea level, melting of polar ice caps, and glaciers. It is well known that climate change is one of the greatest challenges humanity faces as it strives to achieve sustainable development goals, especially in terms of limiting CO2 emissions. This significant rise of emissions continually occurs from 2000 to 2026 for various reasons, such as the pressure of population growth, energy consumption, industrialization and urbanization, technological development and economic growth. High- and low-income countries diverge both in capacity to mitigate and emissions produced. A carbon trading system, therefore, bestowes favour on rich nations and exacerbates inequalities with poor countries benefiting little or not at all. To have control over the sectors to reduce the CO2 emission, we use a machine learning algorithm, such as an LSTM-based CO2 forecasting model, in all the GDP sectors. The research suggests a framework to reduce carbon dioxide emissions in GDP sectors through Government policies. This research also highlights that policy-makers should consider carbon emissions before framing a policy, and an AI-enabled planning tool is necessary for monitoring, system optimisation, and risk management.</p>