Indian TMT Sector Scaling AI Adoption, But High Cost, Skill Shortage Key Challenges: Report

Artificial intelligence is playing a vital role in reshaping technology, media and telecommunications, or TMT, operations by improving efficiency, personalising experiences and enhancing decision-making. From automating networks in telecom to delivering customised media content, AI is streamlining processes, a report by KPMG India shows. However, key challenges exist, including shortage of skilled talent and the high cost of AI implementation in the sector.

The report, based on a survey of industry leaders, showed that 55% of TMT organisations have fully integrated AI, with 37% in the scaling phase. AI-driven innovations have delivered improved results, including a 5-10% reduction in operational costs and over 10% returns on AI investments for 67% of study respondents.

Around 55% of TMT organisations in India have successfully implemented AI at full scale for select use cases, while 32% are gradually scaling their AI initiatives. Additionally, 13% are still in the initial planning stages of adopting AI technologies.

Of the respondents, 55% anticipate that 30-50% of their product or solution portfolios will be AI-led, with expectations that these AI-driven offerings will contribute 10-30% of incremental revenue.

Telecom executives are seeing high levels of AI adoption, with 30% focusing on improving service quality. Additional areas of impact include revenue growth (26%), fraud prevention (32%) and delivering better customer experiences (12%).

Almost 65% of Indian CXOs  agree that leveraging generative AI will provide a significant competitive advantage for TMT organisations. Over half (52%) reported enhanced customer service by utilising AI.

Of the companies surveyed, 67% have begun generating returns in excess of 10% on their AI implementations, building a compelling case for widespread adoption across the sector. Also, 40% are adopting AI within finance and HR functions to achieve better predictability in operations and decision-making.

Over a quarter (26%) of respondents cite a lack of skilled workforce and awareness as significant inhibitors to AI adoption. A third of survey participants, however, believe that 30-50% of their workforce will be AI-ready by FY26, underscoring a strong focus on reskilling and upskilling initiatives.

Around 27% also reported high overall costs of implementation as the top barrier. Lack of accurate data and IT security and privacy concerns were some other challenges cited by the respondents.