By: Varun Gupta, Vice President, Head Digital Solutions India, Iron Mountain
It’s no surprise in this data-driven world where information is a business-critical asset that brings both opportunities and challenges, that we are seeing rapidly increasing volumes of data. In fact, 90% of the world’s data was generated in the last two years alone, increasing to an estimated 120 zettabytes in 2023 from only 2 zettabytes in 2010. To put this into perspective, if you attempted to download 120 zettabytes at the average current internet connection speed, it would take 1.2 billion years to download. As a result, organisations of all shapes and sizes are now seeing the value of investing in good information governance practices to manage their data across multiple formats, networks, systems, software, and hardware
The convergence of AI and digital transformation is propelling Indian cities like Bengaluru, Hyderabad, and Pune to become global AI hubs, driving innovation and economic growth. In fact, AI is not just changing the face of urban centres, it’s also evolving rural communities too. This expansion is fuelled by the Indian government’s initiatives such as “AI for All” and the National AI Strategy. Both of which are designed to work towards a future where AI uplifts society and creates opportunities for everyone.
However, with more data comes an ever-evolving privacy and regulatory landscape. For instance, India’s Digital Personal Data Protection Act (2023) and the Information Technology Act (2000) are stepping-stones towards more comprehensive AI governance in India. But there still lacks a robust AI-specific regulation that addresses the country’s unique challenges and opportunities in the digital age.
So, amidst this regulatory flux, how can organisations truly unlock data’s potential and effectively manage their data?
What information governance means for organisations?
Information governance is the overall strategy for an organisation to effectively manage its information. It provides a consistent and logical framework to handle information through policies and procedures that guide appropriate behaviour. By doing so, organisations can ensure that they are managing data properly to extract its full value while minimising any potential risks.
Developing and implementing a robust information governance strategy requires an organisation to understand its organisational goals, it’s legal and regulatory obligations and its risk appetite. With this understanding, an organisation can undertake a four-step process to implement a strategy across multiple domains and specialisms.
The steps to developing a robust information governance strategy
Firstly, an organisation must assess and benchmark its existing practices, policies and operational models against best practice to understand its current state and where potential gaps exist. Additionally, it needs to gauge employee awareness of information governance to identify any necessary training requirements. The next step is to outline the information governance strategy’s goals, which could include responding to audits, mitigating risks, ensuring compliance, improving efficiency, or reducing costs.
Following this, organisation’s need to justify a business case for implementing the strategy and secure funding to establish a formal change program as implementing an information governance strategy typically requires new people, policies and technology. At this stage, the organisation must identify the specific changes needed to execute the roadmap effectively.
With new measures in place, the next crucial step is to look at the remediation of legacy data and information. As AI technology adoption accelerates, prioritising legacy data remediation becomes essential to ensure data quality, integrity and security, which are critical to the successful implementation of AI systems. However, reviewing all legacy data and technology is a time-intensive process that cannot be accomplished manually. To address this challenge, organisations should look for technological solutions that can identify, remediate, and automatically classify digital content to effectively remove redundant, outdated or trivial (ROT) data.
The Importance of an information governance strategy
Fundamentally, developing and implementing a comprehensive information governance strategy is crucial for organisations to effectively manage their information assets, mitigate risks and ensure compliance. Having an information governance framework in place helps to uncover and address data risks, such as breaches and privacy non-compliance while ensuring that an organisation is complying with regulatory requirements.
India is already making significant strides toward responsible AI innovation through initiatives such as the India Datasets platform, which provides access to anonymised public and private datasets to enhance AI model training; or NITI Aayog’s roadmap for fostering a responsible and ethical AI ecosystem. Additionally, the Economic Advisory Council to the Prime Minister has proposed a Complex Adaptive System (CAS) framework for AI governance, focusing on mechanisms such as human intervention and multi-factor authentication to prevent undesirable AI behaviours. These measures are crucial for India’s rapidly evolving AI-driven economy, where over 58% of AI applications are already being implemented, surpassing the global average.
While a fully consolidated national AI governance framework is still evolving, these initiatives reflect India’s strong commitment to shaping a future where AI drives positive, ethical, and impactful innovation. Therefore, adopting a comprehensive information governance strategy is essential for organisations in India to navigate the complex landscape of data management and compliance. By doing so, organisations not only future-proof their data but also position themselves to harness the full potential of emerging technologies while balancing compliance with strategic business goals.