Indian businesses gearing up for responsible AI adoption: Nasscom
Based on analysis of the data collected through a survey of over 500 senior executives from across large enterprises, SMEs and startups engaged in the commercial development and/or use of AI (Artificial Intelligence) in India, the report offers a glimpse into the beliefs and perceptions of the tech industry about its key strengths and areas for improvement when it comes to compliance with the benchmarks for RAI adoption.
Nearly 60 per cent of businesses surveyed reported having either matured Responsible AI (RAI) practices and policies or having initiated formal steps towards adoption of such responsible practices, according to a report by industry body Nasscom.
About 30 per cent reported having basic awareness of RAI imperatives without a formal strategy or framework, the report said citing the early insights on the state of RAI in India.
Based on analysis of the data collected through a survey of over 500 senior executives from across large enterprises, SMEs and startups engaged in the commercial development and/or use of AI (Artificial Intelligence) in India, the report offers a glimpse into the beliefs and perceptions of the tech industry about its key strengths and areas for improvement when it comes to compliance with the benchmarks for RAI adoption.
The rising need for RAI among AI users and stakeholders is compelling industry leaders to invest in advanced RAI tools and strategies while emphasising transparency in their AI practices. As businesses scale up AI maturity, they also tend to report higher RAI maturity, it said.
"About 60 per cent of the surveyed businesses reported having either matured RAI practices and policies or having initiated formal steps towards RAI adoption. 30 per cent reported having basic awareness of RAI imperatives without a formal strategy or framework," it said. Developers are almost two times more likely than users to report higher levels of RAI maturity.
Large enterprises (those with annual revenue more than Rs 250 crore) are 2.3 times more likely than startups and 1.5 times more likely than SMEs to report matured RAI practices.
Moreover, majority of businesses across key industries are progressing to achieve "satisfactory levels" of RAI maturity.
Around two-thirds of businesses in sectors such as banking financial services and insurance; technology, media, and telecom; and healthcare reported having either matured RAI practices or having initiated formal steps towards RAI adoption. Workforce development remains central for businesses to ensure robust RAI implementation.
"As per the survey findings, 89 per cent of businesses that reported matured RAI practices and policies also reported commitments to continue investments in workforce sensitisation and training for RAI compliance," Nasscom said.
Over 60 per cent of businesses that reported lower levels of RAI maturity also reported commitments to improve compliance through investments in workforce sensitisation and training.
About 69 per cent of respondents suggested that the major share of accountability for RAI compliance should lie with the C-suite or the board of directors at their companies.
"Leadership support is crucial for successful RAI adoption and businesses lean towards top-down accountability for RAI compliance," it said. Debjani Ghosh, President of Nasscom noted that 2023 was the year of AI and brought to the fore both opportunities and risks that are central to its adoption.
It also spurred discussions on the need for ethical and responsible AI and its pivotal role in solidifying brand integrity and nurturing enduring relationships with stakeholders," she said.
"Insights from the survey are anticipated to catalyse the creation of stronger industrial policies and strategies aimed at ensuring compliance with RAI," Ghosh added. As Responsible AI adoption continues to evolve, large scale implementation is dependent on the mitigation of various technical, commercial, and regulatory challenges.
While businesses continue to focus on trust and transparency in commercial development and use of AI and AI-enabled technologies, lack of access to high-quality data and shortage of skilled technical and management personnel remain the biggest barriers to RAI implementation.
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