How India is set to redefine AI maturity and data leadership in 2025
It’s easy to forget that the new AI revolution heralded by ChatGPT and OpenAI kickstarted just two years ago and has been quickly embraced by both businesses and consumers. But unknown to many is India’s meteoric rise to become a global leader in AI adoption and it is one to watch: what happens in the Indian market in 2025 will set the scene for the rest to follow.
Atlassian’s AI Collaboration Index found that nearly half (46%) of Indian knowledge workers are advanced AI users, significantly higher than in other nations. In the US (34%) and Germany (32%), only about one-third of workers have advanced knowledge of AI usage, and Australia (23%) is even further behind.
India leading AI adoption thanks to vast data reserves
The Indian market has several qualities that have helped advance AI, as well as in its adoption and use. Firstly, India is home to the world’s largest pool of mobile data and is the second-fastest-growing data market globally. In 2023, India was ranked 15th in the list of top 25 AI nations but was considered to have the greatest potential thanks to its data pools.
With initiatives like Digital India further encouraging digital inclusion across its massive population, the country generates an unparalleled wealth of data, providing fertile ground for AI applications.
India also has the skills and infrastructure needed to succeed with AI. Like everywhere else, there is still a skills shortage in India, but with some of the world’s best engineering and IT institutes, the country has a better capacity to build the skills base it needs to design and implement cutting-edge AI solutions.
Finally, India’s thriving start-up ecosystem, coupled with government initiatives such as Startup India, is increasingly focused on AI innovation across sectors like healthcare, agriculture, education, and fintech, and that investment infrastructure will directly result in further acceleration in both AI creation and adoption.
Thanks to these drivers, India is poised to be a leader in AI in 2025, but fully capitalising on that opportunity relies on data governance, ethical considerations, and operational challenges.
The role of governance in data and AI maturity
AI needs to have the structures and guardrails in place to ensure the technology retains the confidence of both business and individual users for a long-term and sustainable growth trajectory.
When asked about the governance priorities India should focus on in 2025, Dilip George, Managing Director in India, Quest, points towards recent findings from Quest’s The State of Data Intelligence report.
“The first is responsible AI development. With AI playing a central role in decision-making across industries, ensuring transparency, fairness, and accountability is essential to build trust and mitigate risks,” explains George. “Data privacy and security follow closely behind. With the increasing flow of sensitive data, frameworks like India’s proposed Personal Data Protection Bill and the upcoming National Data Governance Framework are essential to ensuring compliance and safeguarding user data.”
Given the increasingly sophisticated threat landscape, it’s no surprise cybersecurity makes the list. The Indian Computer Emergency Response Team (CERT-In) guidelines and the Cybersecurity Policy aim to bolster resilience against cyber threats, creating a safer environment for AI-driven applications.
Looking beyond governance, George shares the five strategic priorities business leaders should keep in mind to capitalise on the AI opportunity:
- Risk management: Organisations should prioritise building governance frameworks to align AI initiatives with legal, ethical, and operational standards, ensuring risk is managed proactively.
- AI-driven ROI: Businesses must grow their focus on demonstrating tangible returns from AI investments, integrating advanced analytics to measure performance, optimise operations, and drive decision-making.
- AI and sustainability: Sustainability goals should be highly considered, with AI being used to monitor environmental impact, reduce waste, and optimise resource usage.
- Operationalising AI at scale: Scaling AI beyond pilot projects will be key. This requires investing in infrastructure, breaking down data silos, and fostering cross-functional collaboration. Gartner predicts that one in three AI projects will be abandoned after the proof-of-concept-stage, and organisations should be focused on scalability early on to avoid this risk.
- Real-time decision-making: Leveraging AI to enable instant, data-driven decisions will become a critical differentiator, especially in sectors like finance, healthcare, and supply chain.
Governance at the state level
Looking more broadly from a national lens, India’s push towards digital transformation further highlights the growing importance and focus being placed on data governance. Key drivers include:
- Regulatory frameworks: The development of the Personal Data Protection Bill, data localisation norms, and sector-specific guidelines ensures data use aligns with national priorities and international standards.
- Economic drivers: Data is now seen as a critical economic asset. With the rise of digital payments platforms like UPI and innovations in fintech, businesses process vast amounts of personal and financial data, requiring stringent governance mechanisms.
- Digital inclusion initiatives: The Digital India programme aims to empower citizens and businesses, creating a framework for managing and leveraging data responsibly across sectors such as healthcare, education, and agriculture.
Data readiness is key to de-risking AI adoption
In a nutshell, effectively embracing AI requires companies to prioritise data readiness by investing in systems and processes to clean, manage, and ensure data accessibility for AI applications.
“Establishing strong governance frameworks is equally essential as it fosters compliance, accountability, and trustworthiness in AI implementations,” adds George. “Organisations should also democratise data access, allowing broader access across teams to encourage innovation and facilitate faster decision-making, ultimately enabling the scalable application of AI.”
Additionally, businesses must focus on agility and adaptability, remaining prepared to swiftly embrace new tools, techniques, and trends as AI technology continues to evolve
India has every opportunity to turn 2025 into a milestone year for enterprise-wide AI implementation.
“The rigours being applied to AI are going to be more substantial than in previous years, but those businesses that can harness this potential within the regulatory framework will not just keep pace but set the standards for AI success worldwide,” concludes George.
For the latest insights on current data intelligence initiatives and planned investments by some of the largest organisations in the world, visit The 2024 State of Data Intelligence report.
