Indian Firms Accelerate AI Deployment But Maintain Budget Caution, EY-CII Study Reveals

Indian businesses are rapidly shifting from just experimenting with Artificial Intelligence (AI) to deploying it in their daily operations. A joint study by EY and the Confederation of Indian Industry (CII), titled "The AIdea of India: Outlook 2026," reveals that 47% of companies are now using multiple Generative AI applications in their core workflows, a significant increase from last year's pilot-focused approach.

However, this rapid rollout is coupled with cautious spending. Over 95% of these organizations allocate less than 20% of their Information Technology (IT) budgets to AI and Machine Learning (ML). This highlights a noticeable gap between their ambitious AI goals and the actual financial investment.

Impact

This news is highly relevant for the Indian stock market. The report details a major shift in how Indian businesses operate and plan for the future. Companies that successfully leverage AI for efficiency, customer service, and marketing may see improved financial performance, potentially leading to stock price appreciation. Conversely, companies slow to adopt or facing significant talent shortages might fall behind. The overall trend towards AI adoption suggests a long-term evolution in India's corporate landscape, impacting competitiveness and investor sentiment across various sectors.

Impact Rating: 7/10

What This Means for Businesses:

Business leaders are optimistic, with 76% expecting Generative AI to significantly transform their companies and 63% feeling prepared to leverage it. The focus is on speed, with companies often choosing rapid implementation over lengthy in-house development. Future investments are targeted at key business functions like operations, customer service, and marketing, directly tied to performance.

The definition of success for AI is also evolving. Return on Investment (ROI) is no longer just about cutting costs; it now encompasses efficiency gains, optimizing time, achieving business advantages, securing a competitive edge, and building long-term resilience.

Collaboration and Workforce Changes:

Indian firms are increasingly looking outside for innovation. Nearly 60% are co-developing AI solutions with startups or Original Equipment Manufacturers (OEMs), moving away from purely internal efforts. Most (78%) use hybrid models, combining their internal teams with external experts to speed up development and deployment.

The rise of AI is also changing jobs. 64% of companies report shifts in roles for standardized tasks, while a significant talent shortage worries 59% of leaders, who cite a lack of AI-ready professionals. New roles are emerging in the mid-office and innovation departments as companies redesign their structures for an AI-first future.

Despite budget constraints, the trend of AI adoption is strong. Companies that started early are now scaling AI across their departments, ushering in what the report terms a "performance-led phase" for enterprise AI in India.

Difficult Terms Explained:

• Generative AI: A type of artificial intelligence capable of creating new content, such as text, images, music, or code, based on the data it has been trained on.
• AI/ML: Artificial Intelligence (AI) is the broader concept of machines performing tasks that typically require human intelligence. Machine Learning (ML) is a subset of AI that allows systems to learn from data without explicit programming.
• IT Budgets: The financial plans allocated by organizations for their Information Technology resources, including hardware, software, services, and personnel.
• ROI: Return on Investment. A performance measure used to evaluate the efficiency of an investment. It's calculated by dividing the net profit by the cost of the investment.
• OEMs: Original Equipment Manufacturers. Companies that produce parts and equipment that may be marketed by another manufacturer. In this context, it refers to companies that build AI components or platforms.
• PSUs: Public Sector Undertakings. Government-owned corporations in India.
• Hybrid Models: In this context, it refers to a strategy combining internal company resources with external expertise or solutions for development and deployment.
• Workforce Structures: The organization and arrangement of jobs and employees within a company.
• Talent Crunch: A situation where there are not enough skilled workers available to fill the jobs that need to be done.
• Performance-led Phase: A stage where the primary driver for AI adoption is achieving tangible business results and measurable improvements, rather than just exploration or initial implementation.