India’s approach to AI is shifting towards data-centric paradigm

BENGALURU: India, with its burgeoning digital economy, stands at the precipice of a transformative journey driven by artificial intelligence (AI) and generative AI (GenAI).

Sharath Srinivasamurthy, Research Director at IDC India Enterprise Solutions and ICT Practices, said that a significant paradigm shift is underway across various industries in India.

“While some sectors are scrambling to catch up with digital advancements, others are already deep into the exploration and deployment of AI-based use cases.”

Forecasts indicate that AI and GenAI spending in India will skyrocket to reach $6 billion by 2027 with a compound annual growth rate of 33.7 per cent for the period 2022-2027, IDC forecasts worldwide AI spending will exceed $512 billion by 2027, more than double its 2024 market size.

These statistics reflect an inexorable trend towards digital and intelligent ecosystems in enterprises, with as many as 62 per cent of Indian enterprises anticipating that over 50 per cent of their revenue will derive from digital models by the year 2026.

A crucial factor in this growth narrative, Srinivasamurthy said is the recognition by Indian organisations of the importance of robust data management strategies, with nearly 50 per cent of government entities planning to invest significantly in data management-oriented services.

Fostering innovation

“The shift from model-centric to data-centric approach emphasises the growing understanding that high-quality data is a fundamental pillar upon which AI applications can be successful.”

One noteworthy development is the introduction of Jugalbandi, a GenAI-powered chatbot deployed on WhatsApp in Haryana, which streamlines a myriad of processes from pension disbursements to college scholarship applications.

The initiative showcases how technology can significantly enhance the efficiency and accessibility of government services.

As Srinivasamurthy aptly noted, the government bears the dual responsibility of fostering innovation while ensuring that the deployment of these advanced technologies is governed responsibly.

The healthcare sector, in particular, exemplifies the profound impact of AI and GenAI adoption. With the increasing emphasis on patient-centric care, healthcare institutions are leveraging AI to manage and analyze an increasing volume of clinical data.

Notable examples include Apollo Hospital’s efforts to utilize AI for the early detection of tuberculosis (TB) from chest X-rays, as well as AIIMS Delhi’s “iOncology.ai,” aimed at early identification of breast and ovarian cancers. Such initiatives not only enhance diagnostic capabilities but underscore the inexorable trend of integrating AI into various facets of public health.

In the BFSI sector, institutions like JP Morgan have illustrated a long-term commitment to AI integration, a vision initiated six years ago.

BFSI sector faces myriad complexities

“BFSI sector faces myriad complexities, including stringent regulatory frameworks, substantial data management challenges, and the imperative to respond swiftly to market demand. Despite these hurdles, the rising importance of GenAI pilots within banks and financial services suggests a shifting paradigm, focusing on enhancing existing services and streamlining operations,” Srinivasamurthy said.

Moreover, he said that institutions are gradually recognising the potential of AI to address inherent pain points, such as cyber fraud risks and legacy IT infrastructure challenges.

The telecommunications industry in India is undergoing its own metamorphosis, aspiring to transcend traditional connectivity roles to emerge as digital leaders.

With India boasting the second-largest subscriber base globally yet grappling with low average revenues per user, telecom players are under pressure to innovate.

IDC forecasts predict that the number of total connections in India will reach 1.5 billion by 2028, accompanied by data traffic soaring to a staggering 468 exabytes.

In this context, he said the significance of AI becomes even more pronounced.

Automating network operations

“Telecom operators are adopting AI-driven strategies to enhance customer experience (CX) and optimize network operations, which are critical to balancing customer retention and profit margins. With the augmentation of AI technologies, operators can now address customer needs across various touchpoints, effectively combating churn while simultaneously enhancing profitability.”

The ambiguity inherent in billing processes can lead to significant customer churn, affecting both consumers and enterprises.

To mitigate this issue, Srinivasamurthy said the integration of AI  to clarify and analyse billing details—such as varying bill cycles, bill splits, multiple payment modes, loyalty rewards, and promotional offers—can significantly reduce the frequency and duration of calls to contact centers.

By streamlining communication and improving the understanding of bills, he said that AI can enhance customer satisfaction and retention.

On the network operations front also, he said that advancements in AI are facilitating a paradigm shift from reactive to proactive network management, ultimately guiding us towards predictive management.

“As networks become increasingly disaggregated due to virtualisation and edge deployments, the necessity for automating network operations becomes imperative.”

According to Srinivasamurthy, the transition to closed-loop network management must encompass both network operation workflows and Business Support Systems (BSS). The comprehensive approach ensures that network issues are addressed before they escalate, leading to improved performance and customer experience.

Supply chain disruptions

Moreover, for India to transform into a manufacturing hub, as Srinivasamurthy said, it is crucial to harness technologies such as AI, robotics, automation, the Internet of Things (IoT), and 3D printing.

Currently, China dominates global manufacturing with a 28 per cent share, while India accounts for a mere 3.3 per cent, competing with other Southeast Asian nations like Vietnam and South Korea.

One of the primary obstacles India’s manufacturing sector faces includes regular supply chain disruptions. According to IDC’s April 2024 Global Supply Chain Survey, over 30 per cent of manufacturers, retailers, and logistics companies in India anticipate supply chain challenges due to rising costs, talent shortages, and compliance issues.

AI’s adoption in the manufacturing sector is being accelerated by these challenges, he said and added that the technology offers critical competitive advantages that can enable scaling, reduce costs, and enhance efficiency.

Furthermore, he said the landscape of regulatory compliance is evolving; AI solutions are making it increasingly manageable to automate compliance monitoring and reporting, ensuring that businesses adhere to complex regulations effortlessly.