Blitz Bureau
NEW DELHI: Harnessing frontier technologies like AI, advanced materials, digital twins, and robotics can help create 100 million jobs and contribute over 25 per cent to India’s GDP, positioning the country among the top three global hubs for advanced manufacturing by 2035 towards Viksit Bharat at 2047, a NITI Aayog report said on October 29. NITI Aayog’s Frontier Tech Hub unveiled a roadmap, titled “Reimagining Manufacturing: India’s Roadmap to Global Leadership in Advanced Manufacturing”, which identifies Artificial Intelligence and Machine Learning, Advanced Materials, Digital Twins and Robotics as high-impact enablers and maps their implications across 13 priority manufacturing sectors.
The roadmap, unveiled by Maharashtra Chief Minister Devendra Fadnavis, Deputy Chief Minister Ajit Pawar, NITI Aayog CEO BVR Subrahmanyam, and other senior officials, lays out a sector-focused path to harness frontier technologies and elevate India’s manufacturing competitiveness. Fadnavis said that Maharashtra expresses its gratitude to NITI Aayog for preparing this visionary roadmap for Bharat’s manufacturing growth powered by frontier technologies, and for choosing Pune to lead this journey. “Maharashtra will be the first state to fully align with the National Mission on Manufacturing and become the global hub for advanced manufacturing,” he noted.
According to Subrahmanyam, India’s economic ascent inextricably hinges on the strength of our manufacturing sector, but incremental change will not suffice. This roadmap sets a decisive, time-bound course to become an Advanced Manufacturing Powerhouse by 2035; integrating frontier technologies to build precision, resilience, and sustainability into our manufacturing DNA, creating a globally competitive ‘Made in India’ identity,” he said. The roadmap also cautions that India will risk a historic window of opportunity if the country fails to adopt key frontier technologies in high-impact sectors, with a potential loss of $270 billion by 2035 and $1 trillion by 2047 in additional manufacturing GDP.
