New Delhi, Oct 17 More than five in 10 (55 per cent) of organisations in the technology, media and telecommunications (TMT) sector have successfully implemented artificial intelligence (AI) at full scale for select use cases, according to a report on Thursday.
While 32 per cent of organisations are currently in the process of gradually scaling their AI initiatives and 13 per cent are still in the initial planning stages of adopting AI technologies, according to the report by KPMG in India launched at the ‘India Mobile Congress 2024.’
About 55 per cent of respondents anticipate that 30-50 per cent of their product or solution portfolios will be AI-led, with expectations that these AI-driven offerings will contribute 10-30 per cent of incremental revenue, the findings showed.
“The TMT industry stands at the cusp of a remarkable transformation, driven by the rise of artificial intelligence. As the global landscape rapidly embraces a digital-first future, AI is emerging as a transformative force, reshaping not just the TMT industry but all other industries,” said Akhilesh Tuteja, Partner and National Leader–TMT, KPMG in India.
Telecom executives are seeing high levels of AI adoption, with 30 per cent focusing on improving service quality. Additional areas of impact include revenue growth (26 per cent), fraud prevention (32 per cent), and delivering better customer experiences (12 per cent).
Purushothaman KG, Partner, Sector Head-Telecommunications, KPMG in India said that organisations adopting AI technologies are not merely enhancing their operations, they are also fundamentally reshaping customer experiences and driving innovation in ways we haven't seen before.
While 33 per cent of survey participants believe that 30-50 per cent of their workforce will be AI-ready by FY26, underscoring a strong focus on reskilling and upskilling initiatives, 80 per cent of CEOs agreed that investing in skill development is essential for organisations.
Moreover, the TMT industry needs to invest in 5G, cloud computing, and edge technologies to support AI solutions, focusing on network automation to improve reliability and reduce costs.
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