As we enter the new phase of evolution of Digital India, several defining characteristics are becoming apparent. We will explore ten of the most significant aspects in this discussion.
1. Platform Version 2.0 is Already a Work in Progress
The various large-scale initiatives of the Digital India 2.0 era have developed into monolithic and disconnected platforms that fail to address current challenges. The outdated technology infrastructure is insufficient to support essential attributes such as scalability, speed, security, and sustainability. Therefore, there is a pressing need for a new enterprise architecture that facilitates the seamless integration of emerging technologies rather than relying on a patchwork approach. These platforms should enable integration both within and across systems, ensure smooth data flow, provide a high degree of automation and orchestration, leverage AI and machine learning across diverse use cases, incorporate middleware for connectivity, and include robust security measures.
Many of the previous large platform initiatives are expected to undergo significant transformations. In contrast to earlier platform versions that focused on static service delivery, the newer iterations are capable of managing complex logic autonomously to provide dynamic services. For instance, they can better handle contextualization, enable segmentation, and facilitate the operationalization of personalization.
2. The modernization of infrastructure and applications will become an essential requirement
A modular, cloud-native environment driven by microservices, DevOps, and DevSecOps is essential for supporting intricate processes and platforms. In the government and public sector undertakings, numerous platforms are advancing not only in their business logic but also in the foundational infrastructure that supports this complexity. If infrastructure and applications are not provisioned efficiently and swiftly, dynamic load balancing becomes unfeasible, and the development environment fails to align with business demands. Consequently, the critical attributes of modern platforms—scalability, speed, security, and sustainability—cannot be guaranteed.
3. Data-driven governance is expected to gain momentum.
Nearly all government digital initiatives incorporate a data strategy, though for most, this strategy tends to be a basic aggregation of data with limited analytical capabilities. However, a few initiatives are advancing the field by developing the ability to collect, organize, store, and manage substantial amounts of data both internally and across related sectors. Emerging platforms, such as API Setu, facilitate the secure and efficient exchange of data across different domains. Additionally, specialized organizations are being established to enhance data management and data science expertise.
Notable examples can be found in areas such as smart city initiatives, water management, agricultural practices, oil and gas, and banking. This trend signifies a growing recognition of the importance of data in governance, as it becomes increasingly accessible. Such initiatives are poised to inform policy-making, adopt a more detailed approach, incorporate feedback from real-world outcomes, and enable quicker adjustments, ultimately leading to a more robust governance framework for managing national resources and maximizing benefits for the intended populations.
4. AI is receiving systemic backing to facilitate its wider and more profound integration
AI encompasses a diverse range of applications and is not confined to a singular product; its utility varies based on the user and the intended purpose. To effectively integrate AI into governance, it is essential to establish a supportive environment. Digital India 3.0 aims to create an ecosystem that includes structural elements such as Centers of Excellence, cross-functional teams, and specialized programs, alongside necessary resources like financial and technical support. Additionally, it will focus on skill development through training and ongoing learning initiatives, promote data sharing and collaboration via programs like AI Kosh and API Setu, and provide opportunities to highlight grassroots AI innovations.
5. The theme of ‘AI Everywhere’ is expanding, leading to the emergence of various use cases.
In the past, we anticipated the emergence of AI and machine learning as isolated solutions or specific use cases. However, AI has now progressed beyond basic applications such as chatbots and voice assistants, evolving into sophisticated systems capable of multilingual communication. This advancement allows for the application of complex algorithms that can enhance autonomy and improve performance in various processes. With the vast amounts of data generated by transactional systems and external sources, AI and machine learning hold the potential to address intricate challenges. For instance, they can assist in determining the most suitable medications for local populations, enable personalized service delivery through segmentation, facilitate tailored policies based on detailed insights into micro-segments, enhance threat identification for proactive security measures, and improve fraud detection efforts.
The interplay of automation, analytics, and artificial intelligence is developing in cycles, with each cycle witnessing a transformation in their interrelationship. Initially, these elements operated in isolation, but as they progress, the boundaries are blurring, leading to a more integrated approach. Government and public sector organizations are expected to establish enterprise-level platforms to harness AI and machine learning capabilities for identifying and designing complex use cases throughout the value chain.
6. Citizen experience is evolving beyond initial green shoots
The citizen experience has historically been overlooked, but this trend is now shifting. Experience encompasses various dimensions, including the aesthetics and usability of websites and applications, their speed and accessibility, multi-channel and omni-channel capabilities, and the efficiency of service delivery. To improve this experience, numerous initiatives are underway, such as the implementation of standardized web and app templates that adhere to international best practices, the adoption of modern infrastructure and application management to swiftly address issues, the automation of routine tasks through technology, and the utilization of AI and machine learning to maximize data for enhanced predictability at a systemic level. As a result, citizen experience is becoming a crucial focus in digital projects and is poised to receive the attention it deserves.
7. Digital shall reach every nook and corner of the country
Digital India 3.0 aims to extend its benefits to previously underserved regions. This includes areas such as the North East, the Andaman and Nicobar Islands, and certain rural interiors where internet access is either limited or slow. To ensure these regions are integrated into the digital growth vision, it is essential to either enhance internet connectivity or develop technology capable of functioning effectively in low-bandwidth environments. Alternatively, establishing physical service points for offline delivery that can later be synchronized with digital systems is also a viable approach.
8. Comprehensive and proactive cyber security will be increasingly preferred over fragmented and reactive approaches
Cybersecurity and threats are in a continuous state of competition. As new threats arise, poised to disrupt systems for their own benefit, organizations are actively working to address vulnerabilities across networks, computing, applications, endpoints, and data domains. They are also striving for greater integration of security products within these areas. Both Information Technology (IT) and Operational Technology (OT) face similar challenges. Additionally, the dark web presents a significant concern, as it is a marketplace for stolen information.
The threat landscape spans multiple levels, affecting individuals, organizations, industries, and nations. The importance of managing transactional data repositories and utilizing analytics, artificial intelligence, and machine learning to enhance capabilities is growing, enabling organizations to adopt a proactive stance that allows them to anticipate threats before they materialize. The scope of cybersecurity is expected to broaden and become increasingly proactive in the future.
9. Digital will become an engine of employment but will demand new skills
Numerous digital initiatives are characterized by their innovative approaches to addressing various challenges. For instance, the Kisan Drone project by IFFCO aims to empower thousands of rural residents to utilize drones for the application of nano urea in agricultural fields. This initiative not only requires individuals to acquire drone piloting skills but also has the potential to create job opportunities. A comparable scenario can be observed in the realm of data-driven governance, where there is a growing demand for data scientists proficient in data analytics, artificial intelligence, and machine learning. Additionally, skilled professionals in the cybersecurity sector will be essential to interpret the outcomes generated by AI and machine learning applications in security and network management. These examples underscore the increasing need for new skills and the potential for job growth in various sectors.
10. Increased focus on higher-level objectives will be prioritized
Fundamental objectives encompass performance, efficiency, productivity, and reach, whereas more advanced objectives focus on sustainability, the eradication of corruption, transparency, safety, inclusion, innovation, and the unlocking of human potential. Although most digital initiatives primarily target these basic objectives, there is a growing trend towards leveraging digital tools to achieve higher-level goals. Currently, there are instances that address these emerging priorities, either in conjunction with foundational objectives or independently. Often, the presence of these advanced objectives is understated, but over time, they are expected to gain greater visibility and significance.
11. A Strong Private Public Partnership Must Work
Digital India 3.0 can not be developed by government alone. There are few but successful examples that demonstrate the value that public-private partnership brings. With AI kind of technology that requires technology, business, and data experts to work together for building relevant and useful use cases, one cannot rule out the participation of private players, research organizations and academia.
