74% Indian Enterprises Are Investing In AI Adoption: Report – Entrepreneur

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By Shrabona Ghosh
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In the last two years, 74 per cent of Indian enterprises already working with AI, have accelerated their investments in the sector, finds IBM Global AI Adoption Index 2023. Top factors driving adoption in India are advances in AI tools that make them more accessible (59 per cent), the need to reduce costs and automate key processes (48 per cent), and the increasing amount of AI embedded into standard off the shelf business applications (47 per cent).
“The increase in AI adoption and investments by Indian enterprises is a good indicator that they are already experiencing the benefits from AI. However, there is still a significant opportunity to accelerate as many businesses are hesitant to move beyond experimentation and deploy AI at scale,” said Sandip Patel, MD, IBM India & South Asia. “To harness its full potential in the coming months, data and AI governance tools are going to be critical for building AI models responsibly that enterprises can trust and confidently adopt. Without the use of governance tools, AI can expose companies to data privacy issues, legal complications, and ethical dilemmas – cases of which we have already seen plaguing many across the world,” he added.
Over the last several years, AI adoption has remained steady, 59 per cent of IT professionals at large organizations report that they have actively deployed AI while an additional 27 per cent are actively exploring using the technology. The top barriers hindering successful AI adoption at enterprises both exploring or deploying AI are limited AI skills and expertise (30 per cent), lack of tools/platforms for developing AI models (28 per cent), AI projects are too complex or difficult to integrate and scale (27 per cent), ethical concerns (26 per cent) and too much data complexity (25 per cent).
The need for trustworthy and governed AI is well understood, but barriers are making it difficult for companies in India to put into practice. In 2024 addressing these inhibitors would be a priority, like providing people with the relevant skills to work with AI and having a robust AI governance framework.
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