The "Redefining TMT with AI" report offers valuable insights on the adoption of artificial intelligence (AI) technology in India's Technology, Media, and Telecom (TMT) sector. The report covers an in-depth analysis of the sector, providing statistical data on key emerging trends in AI's adoption across TMT organisations in India. The report also provides insights on challenges faced by organisations in adopting effective AI strategies. The report surveyed senior executives from 123 TMT companies, including CTOs, CIOs, and CDOs, to gather opinions and views on the impact of AI on their businesses. It reveals that 55% of TMT organisations in India have achieved full-scale AI implementation, while 37% are in the gradual scaling phase. AI technology is transforming the TMT sector, enhancing operational efficiency and customer engagement. AI-driven predictive network analysis and automation techniques enhance network operations and quality of service (QoS) of 5G networks. By analysing customer data, personalised experiences are delivered to improve customer experience. AI-driven fraud prevention in telecom is also on the rise, involving the use of machine learning models to detect and prevent fraudulent activities in real-time. The report also highlights key challenges faced in AI implementation in India, including high implementation costs, a lack of skilled workforce, inadequate or inaccurate data, IT security and privacy concerns, and difficulty in demonstrating a clear ROI from AI initiatives.
The report suggests recommendations to overcome these challenges and promote the growth of AI adoption in the TMT sector in India. It recommends the need to invest in scalable infrastructure with a focus on 5G networks, cloud computing, and edge technologies to support AI solutions by building more robust AI talent pipelines and investing in upskilling and training initiatives for employees and collaboration with universities and research institutions to develop AI curricular. The report also stresses the need to adopt responsible AI practices by ensuring fairness, transparency, and accountability across operations through regularly auditing AI-based models to avoid bias. Finally, encourage AI research and development by providing incentives for AI research, especially in sectors where AI can drive national growth, and encouraging public-private partnerships for collaboration between governments and the private sector to accelerate AI use in critical areas like network infrastructure and public service delivery.
In conclusion, the "Redefining TMT with AI" report sheds light on the adoption and implementation of AI in India's TMT sector offering valuable insights into the sector's changing technological landscape. The report emphasises the significance of AI as a key driver of growth and digital empowerment and offers recommendations for overcoming challenges and promoting the growth of AI in the TMT sector in India. By adopting scalable AI solutions, fostering cross-sector collaboration, improving workforce skills, adopting responsible AI practices, and encouraging public-private partnerships, the TMT industry in India can adapt and thrive in a rapidly changing technological age.
