New Delhi, Dec 23 (IANS): As Generative AI continues to expand its footprint within enterprise functions, business and enterprise leaders need to balance technology and trust to unlock higher levels of productivity in 2024, say industry experts.
Generative AI or GenAI, which uses Large Language Models (LLM) to address complex tasks, has the potential to add a cumulative $1.2-1.5 trillion to India's Gross Domestic Product (GDP) over the next seven years.
India can potentially add $359-438 billion in FY2029-30 alone, reflecting a 5.9-7.2 per cent increase over and above baseline GDP, according to a latest EY India report.
Approximately 69 per cent of the overall impact is expected to be derived from sectors such as business services (including IT, legal, consulting, outsourcing, rental of machinery and equipment, and others), financial services, education, retail and healthcare.
Geeta Gurnani, IBM Technology CTO and Technical Sales Leader, IBM India & South Asia, told IANS that boosting productivity with GenAI requires redesigning operating models, keeping in mind three things.
“Establish AI management and oversight roles like having a Chief AI Ethics Officer; expand AI skills beyond the IT department to optimise its use with greater transparency and AI-relevant knowledge across the enterprise; and introduce clear AI governance to explicitly address explainability, bias, and reliability,” she said.
As we navigate the transformative landscape of GenAI tools in 2024, it's evident that enterprises stand at the intersection of unprecedented productivity gains and inherent risks.
“The widespread adoption of AI-powered tools has become a business imperative, with IT leaders prioritising these technologies to enhance efficiency and customer service,” according to Cloud security provider Zscaler.
“On one hand, empowering employees through tools like ChatGPT opens new frontiers of innovation, but on the other we are introducing potential threats — especially when we look at cybersecurity. To harness the full potential of AI while mitigating risks, enterprises must adopt a multi-layered defense strategy,” a Zscaler spokesperson told IANS.
AI-driven sandboxing, App segmentation, and ML-driven data classification are pivotal in preventing compromise, eliminating lateral movement, and protecting against data loss.
“These best practices align with the current cybersecurity landscape, allowing enterprises to stay ahead in the AI and LLM-driven arms race,” said Zscaler.
As Indian enterprises are substantially increasing their investments in AI, about 42 per cent of enterprises plan to spend more than Rs 50 crore on AI initiatives in FY2024-25.
According to CyberMedia Research (CMR), 93 per cent of enterprises in India that leveraged AI have experienced growth in profit.
Generative AI has firmly established its presence in the enterprise landscape, with the majority actively using GenAI.
GenAI is significantly contributing to the development of customer-centric products (60 per cent), data-driven decision-making (59 per cent), and improved customer services (47 per cent).
The primary challenges faced by enterprises in AI deployment include technical complexity (91 per cent), AI bias (67 per cent), and security and privacy of sensitive data (59 per cent), according to the report.
“Trust is not a new concept for business success, but it’s become more challenging with GenAI, intensifying competition, and the rise of cyber threats. By addressing the trust issue, adoption of GenAI tools will increase, which in turn will lead to the development of more innovative use cases to augment human productivity and operational efficiency,” Gurnani added.
As we look ahead to 2024 and beyond, AI is set to become increasingly pervasive in enterprises.
“Early adopters will tap into the full potential of both Traditional and GenAI. However, for most, their success will hinge on embracing and customising AI to their specific needs while being aware of the inherent risks," said Anil Chopra, VP-Research and Consulting, CMR.