Powering India's multilingual AI future with resilient data

Time of India

5 days ago

India's linguistic diversity is both a cultural treasure and a technological challenge. With over 121 languages spoken by more than 10,000 people each, and more than 80% of internet users engaging primarily in vernacular content, the nation's AI aspirations hinge on an often-overlooked enabler: resilient, multilingual data systems. As industries invest in AI innovation, the conversation is rapidly evolving beyond data storage to how we can protect, optimize, and activate data to drive inclusive progress.India's multilingual data landscapeIndia's AI journey is unlike any other. While many global markets operate within relatively homogenous language ecosystems, India's linguistic richness presents both complexity and opportunity. From the informality of Hinglish (a Hindi-English hybrid) in urban digital interactions to the literary depth of Tamil expressions, these attributes complicate AI training. Yet, the complexity also presents an opportunity: multilingual data, when effectively managed, can power solutions tailored to India's uniquely flexible business environment.
However, these opportunities come with challenges. A study by Bengaluru-based market research firm Feedback Advisory found that only 34% of Indian users take full backups of their data, 48% take partial backups, and 18% don't back up their data at all. These inconsistent practices give rise to another issue: while data may exist, it is often structured for protection rather than optimized for accessibility. This limits its potential to train AI models that authentically reflect the country's multilingual and cultural reality.
For example, a healthcare provider storing patient data in regional languages like Marathi and Telugu might struggle to deploy diagnostic tools for non-English-speaking populations without unified, resilient systems that bridge data silos.
How resilience can empower AI for every voice
Data resilience is no longer just about disaster recovery; it is now a critical enabler of AI readiness. For business and technology leaders, this means thinking beyond backup and focusing on systems that allow AI to securely and ethically access multilingual datasets - while complying with regulations such as the Digital Personal Data Protection Act (2023).
The rise of hybrid cloud environments- combining on-premises and cloud systems - offers the flexibility needed to balance compliance and scalability across India's diverse and fragmented digital landscape. This is where Veeam plays a key role: delivering secure, reliable, and intelligent backup and recovery through the
Veeam Data Platform
. By providing immutability, rapid restore capabilities, and visibility across environments, Veeam ensures that data is not only protected but also always available and usable - regardless of format, location, or language.
Beyond securing data, it is equally important to fortify the AI models trained on this data to ensure they can adapt as regional demands evolve. This evolutionary approach transforms static data repositories into dynamic assets. For instance, anonymized patient records in regional languages such as Gujarati or Kannada could be used to develop multilingual chatbots that improve healthcare access in rural areas. Similarly, agricultural AI tools that analyse farmer helpline data in languages such as Odia or Punjabi could enhance crop yield predictions - helping bridge the rural-urban divide.
AI in every language to uplift lives, farms, and markets
Whether in healthcare, agriculture, or retail, AI models built on diverse linguistic data can unlock real-world benefits. In healthcare, local-language AI tools can reduce misdiagnosis by offering support in native languages. In agriculture, predictive analytics driven by regional language data can support farmers with insights on pest control or soil health. And in e-commerce, analysing reviews in Tamil or Bengali can boost product personalization and engagement.
For tech and business leaders, the priority must be balancing innovation with practicality. Transparency in data capture and usage is essential - especially given that 82% of Indians view data protection as a core factor in building trust, according to a PwC report. Data resilience solutions such as Veeam's Data Platform make trust possible in complex multilingual contexts by ensuring Indian enterprises have safe, secure, and reliable access to data. Its immutability, rapid restoration capabilities, and cross-platform visibility equip leaders to ensure AI preparedness and business continuity - freeing up time and resources for innovation.
Additionally, collaborating with academia and start-ups to develop language-specific AI tools, and investing in upskilling teams to manage multilingual data infrastructure, will be key to long-term scale and success.
Building a truly inclusive AI future
As India strides toward its $1 trillion digital economy goal, the integration of resilient multilingual data systems will determine whether its AI ambitions remain aspirational - or become transformative. The opportunity lies not in chasing global benchmarks, but in developing solutions that speak India's many languages.