India Predictive Analytics Market Size and Share Analysis Report: Forecast Trends and Outlook (2026-2035)

Key Trends and Recent Developments

India Predictive Analytics Industry Segmentation

India Predictive Analytics Market Share

By Component, Solutions Secure the Bigger Share of the Market

The demand for predictive analytics solutions in India is at its peak as an increasingly business-oriented world relies on advanced software tools to weigh a complex dataset and forecast future outcomes. The utility of data mining, statistical modelling, and machine learning algorithms by integrating them into core business operations is realized through these solutions. BFSI and retail industries use these tools to detect fraud, optimize inventory, and analyse customer behaviour.

Services are the fastest-growing sub-segment in the India predictive analytics market because of increased demand for consulting, implementation, and support services. Companies adopting analytics tools seek assistance from experts to tailor the requirements of these tools to their particular business environments. In addition, managed services and data science-as-a-service value offerings are gaining considerable traction, especially among small and medium enterprises.

By Deployment Mode, On-Premise Predictive Analytics Register the Major Share of the Market

On-premise predictive analytics solutions largely contribute to the India predictive analytics market value, particularly through large enterprises where data security and compliance needs are extremely tight. With stricter data governance, these solutions are the preferred choice in industries like BFSI and government, where any violation of data privacy is flagrant. In June 2025, the Government of Uttar Pradesh announced a comprehensive cyber security infrastructure upgrade for its Cooperative Bank network, involving integration into a secure, core-banking system with strict on-premise controls. This illustrates that in sectors like BFSI and government, where data privacy violations carry heavy penalties, organizations prefer hosting analytics internally to maintain tighter governance and meet regulatory requirements.

The growth in cloud-based predictive analytics solutions has been rapid due to their scalability and cost-effectiveness, thus driving the India predictive analytics market revenues. These solutions allow companies to analyse and process large volumes of data in real-time, thus enabling rapid decision-making and enhanced agility. Cloud platform use is therefore extremely beneficial for SMEs since these platforms offer advanced analytics without investment in expensive infrastructure.

By Enterprise Size, Large Enterprises Account for the Dominant Share

Large businesses dominate the India predictive analytics market revenue share owing to huge amounts of data and the use of sophisticated analytics solutions. Companies utilize predictive models for various applications, including risk management, customer segmentation, and supply chain optimization, which provide them with a competitive advantage. A compelling example is Jaguar Land Rover (JLR), a Tata Motors subsidiary, which in June 2023 partnered with Everstream Analytics to integrate AI-powered risk prediction into its global supply chain. By embedding real-time analytics and machine learning, JLR can now detect potential disruptions, like natural disasters or shipping delays, before they impact production. This operational foresight enables better planning, inventory management, and resilience, demonstrating how large businesses capitalize on predictive analytics across complex, global operations.

Small and medium enterprises (SMEs) are quickly embracing predictive analytics, propelled by the cost-effectiveness of cloud-based solutions and the imperative to optimize operational efficiency. SMEs are using predictive models to maximize marketing campaigns, enhance customer service, and streamline processes, resulting in increased growth and profitability.

By End Use, BFSI Leads the Predictive Analytics Market in India

The BFSI industry continues to be the biggest consumer user of predictive analytics. The predictive analytics demand in BFSI rises from the increased need for credit scoring, fraud detection, and customer retention programs. Predictive models assist in evaluating risk and tailoring financial products to enhance customer satisfaction and operational efficiency. In early 2025, SBI implemented predictive analytics for real-time fraud detection, analyzing transaction patterns and user behavior. This reduced fraud losses by 40%, showcasing the BFSI sector’s growing reliance on predictive models for security, risk management, and customer trust.

A significant spurt in predictive analytics adoption in India is witnessed in the healthcare industry. The sector extensively uses these analytics for patient outcome prediction, disease outbreak forecasting, and resource allocation. These applications enhance patient care while optimizing healthcare delivery systems. In June 2025, AIIMS Patna deployed AI-powered predictive analytics to screen tuberculosis using handheld X-ray devices and image-based algorithms. This innovation enables early TB detection in rural regions, streamlining patient triage and treatment protocols for thousands in Bihar.

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If you choose to purchase the full report at a later stage, the amount already paid will be adjusted, and you will only need to pay the remaining balance.

India Predictive Analytics Market Regional Analysis

By Region, South India Holds the Largest Market Share

Growth in the South India predictive analytics market is majorly contributed by mature IT ecosystem and a concentration of tech hubs like Bengaluru, Hyderabad, and Chennai. This region hosts the biggest analytics firms and startups, all supported by skilled talent, superior infrastructure, and collaboration with R&D centres of global players. In May 2025, Punjab Agricultural University collaborated with BITS-Pilani to deploy predictive models using IoT sensors, AI, and satellite imagery for crop yield forecasting and irrigation planning. These systems help farmers make data-backed decisions on fertilization and water use, reducing costs and improving productivity. The success of such models in Punjab is encouraging similar rollouts across Haryana and Maharashtra, promoting smart, analytics-driven farming and enabling sustainable agricultural development. Moreover, the market enjoys a favourable policy environment nurturing innovation for further development and adoption.

North India is emerging as the fastest-growing region in the Indian predictive analytics market because of the rapid digital transformation taking place in Delhi and its neighbouring states like Haryana and Uttar Pradesh. Smart city schemes, along with government initiatives and startup ecosystems, are boosting adoption, particularly through healthcare, logistics, and government sectors. Growing investments in AI infrastructure and data-centric services are setting the pace for analytics adoption in both public and private sectors.

Competitive Landscape

Other players in the India predictive analytics market include AVEVA Group Limited, and Altair Engineering Inc., among others.

Key Highlights of the India Predictive Analytics Market Report:

• Detailed segmentation and trend analysis across component types, deployment modes, enterprise size, end-use sectors, and regional adoption
• Reliable historical datasets and accurate forecasts through 2035
• Insights into emerging technologies such as generative AI-based modelling, real-time predictive engines, and sector-specific analytics solutions
• In-depth competitive landscape featuring top analytics firms and AI startups operating in India
• Regional focus highlighting growth in South India’s IT clusters and innovation hubs in Delhi-NCR and Pune
• Investment outlook shaped by digital transformation, data governance mandates, and government-led AI initiatives

Why Choose Expert Market Research?

• Specialized knowledge from analytics, AI, and digital transformation experts
• Tactical insights crafted for product innovation and analytics adoption
• Methodology rooted in primary expert interviews and trusted data sources
• Strategic guidance driven by machine learning forecasts and behavioural data analytics

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