Balancing AI and green economy on the road to 2047

Neeti Neeti and Arvind Lakshmisha

As we move closer to our goal of becoming a developed nation by 2047, we must reimagine development as a multidimensional process – one that integrates economic growth with social equity and environmental sustainability. While traditional indicators, such as gross national income, industrial capacity, and technological infrastructure, remain important, they must be complemented by measures of social well-being and ecological resilience. In recent years, substantial progress has been made in this direction, reflected in the improvement of our Sustainable Development Goals (SDG) composite score – from 57 in 2018 to 71 in 2023–24.

To sustain and accelerate this momentum, we must place the green economy (low carbon, resource efficient and socially inclusive) at the heart of our development strategy. Key sectors, such as renewable energy, sustainable agriculture, green construction, environmental conservation, waste management, and eco-friendly transportation, offer not just environmental benefits but tremendous economic potential. According to the International Labour Organisation, the transition to a green economy could create 24 million new jobs globally by 2030, with projections suggesting 35 million new green jobs in India alone by 2047.

Parallel to this green transition is the exponential rise of artificial intelligence (AI). Between 2022 and 2023, the share of green talent in the workforce rose by 12.3 per cent across 48 countries, as per the World Economic Forum. During the same period, job postings requiring at least one green skill grew by 22.4 per cent. Candidates with green skills saw a 55 per cent higher hiring rate than the overall workforce, as per LinkedIn's Global Green Skills report. Increasingly, these roles intersect with AI, especially in sustainability-related fields, such as renewable energy, climate adaptation, and circular economy. AI is helping optimise solar and wind energy production, enabling precision farming through satellite data, and enhancing waste management systems by improving sorting, recycling, and resource use efficiency.

However, as Alan Moore aptly put it, ‘Technology is always a two-edged sword. It will bring in many benefits but also many disasters.’ The same is true for AI. While it enables new efficiencies and opportunities, it also threatens traditional jobs in manufacturing, accounting, customer service, and logistics. Predictions by leaders, like Bill Gates, suggest that AI could replace doctors and teachers within the next decade, potentially undermining livelihoods in key sectors.

Beyond employment, AI’s environmental footprint is significant. According to a study published recently in Nature Computational Science, the rapid growth of AI infrastructure contributes to rising greenhouse gas emissions and surging electronic waste, which reached 3.8 million metric tons in 2024. A recent study by Nomura Research Institute has estimated that India’s data centres are expected to grow exponentially, increasing their energy consumption from 0.5 per cent to 3 per cent of the total energy usage. Social concerns, such as data privacy, algorithmic bias, and increased isolation, add further complexity, raising questions about the kind of society AI is helping shape.

If we are not careful, we risk building a future that is efficient but unequal, high-tech but environmentally destructive. A future that moves forward at breakneck speed, leaving behind those unable to keep pace. This would run counter to the core promise of the UN Agenda 2030: to leave no one behind.

To ensure AI serves sustainable development rather than undermining it, a balanced and inclusive approach is crucial. This means establishing thoughtful regulations, designing ethical frameworks, and aligning technological progress with green economy goals. AI must be positioned not as a replacement for human capacity but as a tool to augment and empower it.

A critical component of this approach is the urgent need for reskilling and upskilling. As economies transition, existing workers must be equipped with new competencies in both AI and sustainability. Educational institutions must play a leading role in designing transdisciplinary curricula that combine technical AI training with practical applications in environmental and social domains. Programs must not only teach how to use AI tools but also how to apply them to real-world challenges – be it in smart grid energy management, AI-driven sustainable farming, or waste reduction systems.

Such training initiatives must also be inclusive. Without deliberate effort, AI can exacerbate existing inequalities. Under-represented groups—including women, informal workers, and rural populations—must have access to training and employment in AI-enabled green jobs. Ethical considerations, particularly around data use and algorithmic bias, should be embedded into all AI education and development initiatives.

Ultimately, the future of AI and sustainability is not simply a matter of technological innovation but of collective choice. If we choose wisely, prioritising equity, responsibility, and inclusivity, AI can be a powerful driver of green jobs and sustainable development. If we neglect these values, we risk accelerating toward a future that contradicts the very goals we set out to achieve.

We stand at a crossroads. The road we take will define not only our relationship with technology but also the kind of society we build for generations to come.

(The writers are faculty at Azim Premji University. Views are personal) 

Disclaimer: The views expressed above are the author's own. They do not necessarily reflect the views of DH.