Responsible AI Challenges: HCLTech-MIT Study

New Delhi, Jan 22 (PTI) Even as companies are increasingly recognising the competitive advantage that responsible AI can provide, many executives express concerns over their organisations' capabilities to address various risks associated with AI deployment, a recent report has revealed.

A study by HCLTech and MIT Technology Review Insights has shown that whereas 87 per cent of corporate executives surveyed think it is important to embrace responsible AI principles, only 15 per cent of respondents feel very prepared to implement them.

The report gathered insights from 250 global executives and senior leaders across various industries to assess the current landscape of responsible AI practices and their implementation within organisations.

In a rapidly evolving digital landscape, responsible AI is essential for fostering trust and ensuring that AI technologies are fair, transparent, and beneficial to society. This is particularly pertinent in India, where the integration of AI across sectors like customer service, healthcare, and finance is accelerating.

The report underscored that while there is significant enthusiasm for the potential of AI in India, the journey toward responsible implementation is fraught with challenges.

According to a survey, executives are not confident in their company's capacity to apply ethical AI practices to solve a variety of AI-related issues. Many expressed concerns over their organisations' capabilities to address various risks associated with AI deployment. For instance, only 23 per cent of respondents felt highly capable of managing user adoption and change management challenges, while just 26 per cent felt equipped to tackle issues related to bias and fairness in AI systems.

With evolving regulations around AI, particularly in sensitive sectors like finance and healthcare, only 34 per cent felt prepared to navigate compliance challenges.

"It is important for organizations to institutionalise the right AI governance policies and implement the tech guardrails--for example, algorithmic audits, bias detection tools, explainability frameworks (such as SHAP and LIME), and human in the loop systems—to reduce incident risks," said Vijay Guntur, Chief Technology Officer and Head of Ecosystems, HCLTech.