IBM: Almost 59% of Indian Enterprises Engage with AI, Skillset and Ethics Remain Concerns
- ByStartupStory | February 15, 2024
The adoption of emerging technologies like artificial intelligence (AI) has seen significant growth in recent years, prompting India Inc. to catch up, according to a report. The ‘AI Adoption Index 2023’ by Morning Consult and commissioned by IBM revealed that approximately 59% of Indian enterprises are actively leveraging AI for various organizational purposes, positioning the country among the top surveyed nations in this regard.
Nearly 6 out of 10 IT professionals in enterprises reported active implementation of generative AI, with 74% accelerating investments or rollout of AI in areas such as R&D, reskilling, workforce development, and developing proprietary AI solutions. These insights stem from a survey conducted with 1,000 Indian technology employees.
Driving the adoption of AI are factors such as the rise of user-friendly AI tools and the imperative to cut costs through process automation. Companies are turning to AI to address labor shortages by automating tasks, enhancing customer self-service, and improving recruitment and HR processes.
Despite enthusiasm for AI adoption, concerns persist regarding ethics and limited skill sets. A significant portion of employees, around 30%, cited limited AI skills and expertise, while 27% expressed concerns about the complexity of integrating and scaling AI projects.
Sandip Patel, Managing Director of IBM India and South Asia, commented, “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.”
A quarter of respondents found AI to involve “too much data complexity,” highlighting a need for transparency and ethical AI practices. However, the report notes that only a minority are actively taking steps towards ensuring trustworthy AI, such as reducing bias and developing ethical AI policies.
IBM’s report identifies barriers to developing trustworthy and ethical AI, including the lack of an AI strategy, company guidelines, and AI governance. Patel emphasized the importance of data and AI governance tools in building AI models responsibly, to avoid potential data privacy issues, legal complications, and ethical dilemmas.
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