Artificial intelligence (AI) has transitioned from a futuristic notion to a vital element in the Indian startup landscape. It is reshaping the foundation of how startups are developed, operated, and scaled. AI has become integral to business models, allowing entrepreneurs to address challenges with speed, efficiency, and innovation. This technology is enhancing competitiveness and growth across various sectors, from logistics to customer engagement.
According to recent reports, India has established itself as a significant player in deeptech innovation, with approximately 3,600 deep tech startups as of 2025. This positions the country as one of the largest deep tech ecosystems globally. In 2024 alone, these startups collectively raised $1.6 billion, reflecting a 78% year-over-year growth and demonstrating increasing investor confidence in India’s ability to cultivate competitive tech firms. This expansion is attributed to a rich talent pool and rising investments in research and development.
Further corroborating this trend, a survey by the Competition Commission of India (CCI) reported that roughly 67% of Indian tech startups are focusing on AI application development. This indicates a shift from mere conceptual experimentation to practical product offerings. The study found that 76% of these startups utilize open-source platforms for AI development, primarily due to cost and accessibility considerations. Additionally, about 88% employ machine learning (ML), while 66% integrate generative AI models, with sectors such as healthcare, finance, retail, logistics, and e-commerce seeing significant AI applications. Research conducted by SAP India in conjunction with Dun & Bradstreet further revealed that 77% of Indian startups are investing in AI and advanced technologies, including ML, Internet of Things (IoT), and blockchain.
The trend of AI adoption is pervasive across various business functions within the Indian startup ecosystem. Industry studies indicate that over 70% of startups incorporate AI into operations such as analytics, automation, and customer experience. In logistics and supply chain management, AI is being utilized for route optimization and delivery scheduling. Conversational AI platforms are enabling startups to provide 24/7 customer support while simultaneously reducing operational costs. Consequently, AI-driven startups are enhancing financial viability, accelerating product development, and exploring new market opportunities.
“As AI and Generative AI dominate the technological landscape, AI constitutes the largest segment of deep tech, garnering 87% of all deep tech funding in 2024. The Generative AI ecosystem surged nearly 3.7 times to over 890 startups by the first half of 2025, securing cumulative funding of $990 million,” stated Rajendra Deshpande, industry expert and former CIO at Intelenet Global Services.
India’s technologically adept workforce has fostered an environment conducive to AI adoption and innovation. Data scientists, engineers, and developers are crafting solutions that are both relevant and competitive. Startups are also making use of open-source tools to boost agility and manage costs more effectively. Furthermore, some startups are addressing challenges related to linguistic diversity by developing AI models tailored for Indian languages, thus facilitating voice assistance for millions of non-English speakers.
“India’s startup ecosystem is shifting from a phase of rapid experimentation to one of strategic scaling and autonomy. Establishing robust, GPU-rich infrastructure in Tier 2 cities is not merely about cost savings; it is designed to empower founders to build, train, and deploy AI solutions locally while competing on a global stage. The next unicorn should not be hampered by compute costs or data latency,” asserted Narendra Sen, Founder and CEO of RackBank and NeevCloud.
Data from Indeed reveals that AI-related job postings in India rose to 11.7% in September 2025, up from 8.2% a year prior, positioning India second in global demand for AI talent, trailing only Singapore. While overall job postings dipped by 0.8% in September, the demand for AI competencies is escalating across various sectors, including data analytics, software development, and engineering.
AI adoption is beginning to influence sectors with substantial social implications. In the healthcare industry, predictive analytics, AI-driven diagnostics, and telemedicine solutions are enhancing accessibility and improving patient care. AI innovations are showcasing how startups leverage data and machine learning to refine diagnosis and treatment. Partnerships between academic institutions and startups are further driving innovations aimed at addressing systemic public service challenges.
However, obstacles remain on the path to AI adoption for Indian startups. Many face issues related to data quality and a shortage of qualified talent needed to develop effective AI solutions. Additionally, there exists a precarious balance between superficial AI branding and genuinely valuable products. Concerns surrounding data privacy, ethical usage, and design considerations require attention from both founders and regulatory bodies.
Critics argue that some startups have fallen victim to the “shiny toy syndrome,” becoming overly enamored with trends, particularly AI, over the past two years. Companies often attempt to apply AI indiscriminately to solve diverse business problems, which may not always yield intelligent decision-making outcomes. While AI can aid in information acquisition, making informed decisions may require different methodologies.
“Currently, many leaders are employing AI in a simplistic and unimaginative manner—as merely a tool for cost-cutting, role automation, and workforce reduction. Layoffs are framed as ‘efficiency gains’ leading to stock price surges and executive accolades for being ‘AI-first.’ However, real costs often emerge later. The case of Klarna illustrates this, having initially celebrated the replacement of numerous customer service positions with AI, only to later acknowledge declines in customer experience, necessitating a return to human support. This pattern—aggressive automation that compromises capabilities, followed by quiet reversals—is indicative of a lack of strategic leadership,” noted Ravi Venkatesan, former head of Microsoft India.
The trajectory of AI adoption in the Indian startup ecosystem is accelerating. As this technology empowers startups to scale and drives innovation across industries, the evolving business models will transition from imitation to impactful innovation.
“The future belongs to those who control their computing capability. By fostering sustainable, sovereign, and scalable digital infrastructure today, India can not only consume AI but also lead its development,” added Sen.
In the coming years, startups that can effectively marry AI with governance and operational excellence will be instrumental in defining the next chapter of India’s entrepreneurial narrative.
