"AI helps governments drive innovation as well as economic growth, and this is about much more than developing an indigenous AI-startup ecosystem. Countries that don’t adopt AI will be left behind," observes the Tony Blair Institute for Global Change.  

This sentiment underscores the critical need for AI-driven transformation within government services worldwide. As countries race to harness AI's potential, the stakes have never been higher. With the potential to double economic growth rates and an International Data Corporation predicted 33.7% CAGR in AI from 2022 to 2027, the imperative for transformation is both immediate and inevitable.  

Governments must meet the growing expectations of their citizens, who demand smarter, faster, and more efficient services. Globally, AI-augmented service delivery is becoming the norm, opening up new opportunities and avenues for revenue generation. 

Global AI Adoption in Government Services 

The international landscape shows a clear commitment to AI integration in public services. Around ten countries are already delivering AI-enabled services to their citizens, and 75 nations have released their AI strategies by 2024. The United States has requested a staggering $3 billion for AI in the FY25 budget, while Singapore plans to spend $1 billion on AI over the next five years. South Korea is set to invest $6.94 billion in AI by 2027. These figures highlight the global momentum towards AI, with significant investments being made to ensure that governments can leverage this technology to its fullest potential. 

India's Position in AI Transformation 

India is steadily advancing in the global AI landscape, with a $1.2 billion budgetary commitment to the India AI mission over the next five years. The FY24-25 budget allocates 552 crores specifically for AI mission. India's standing in the Global AI Index has improved, currently ranking at 14th. The Government of India is actively pushing for AI adoption across various departments and states, guided by the seven pillars of the India AI mission, which focus on infrastructure, skilling, and startups. Despite this progress, only about five Indian states have formal AI policies, with most others still relying on IT policies. NITI Aayog has recommended multiple AI transformations, but a more unified approach is needed while adopting these recommendations across Departments and State Governments. 

Honorable Prime Minister Narendra Modi's recent call for promoting competitive federalism among states, coupled with honorable Andhra Pradesh Chief Minister Chandrababu Naidu's advocacy for the Public, Private, People Partnership (P4) model, signals a strategic push towards collaborative and responsible AI development. The establishment of a Data Governance and Ownership Platform, as discussed in the 2024 CII Meeting, and the workgroup recommendations from the India AI Report 2023 to set up the India Datasets Platform (IDP) and National Data Management Office (NDMO), are critical steps in this direction. The Digital Personal Data Protection Act, 2023, further emphasizes the need for robust data governance and data protection which is the foundation for AI transformation. 

Current Situation in India 

Data is the cornerstone of government service delivery, and it plays a crucial role in AI adoption. However, this data is often scattered across various government bodies, creating challenges in integration and access. Key government entities such as the Ministry of Electronics & IT, the Department of Telecom, UIDAI, NITI Aayog, and the National Data Analytics Platform (NDAP) are responsible for managing different aspects of data, IT policies, and AI initiatives. Additionally, platforms like NIC, NeGD, ODG and APISetu handle data hosting, e-governance, and public service integration. Proposed Data Protection Board of India (DPBI) will oversee data protection under the 2023 Digital Personal Data Protection Act. 

India already has an extensive network of Government provided data, services and APIs available for public consumption. The NDAP provides access to 3,745 downloadable analytical datasets, while over 13,755 government services and 5,716 APIs are listed on platforms like Services and APISetu respectively. Furthermore, Government sponsored AI models such as language, translation services provided by Bhashini are already in place, serving as a foundation for future AI-driven public service initiatives. 

A quick glance into evolution of Government services delivery 

Government service delivery has undergone significant evolution, progressing through five distinct maturity stages. Initially, services were entirely manual in the Pre-era of Digitization, with limited efficiency and reach. The Dawn of Digitization introduced basic digital tools, paving the way for e-Governance, which brought about more accessible and streamlined services. As digital capabilities expanded, the integration of workflows, analytics, automation, and personalization in the E-Governance phase enhanced the efficiency and responsiveness of services. Today, we stand at the cusp of the AI-enabled Optimized Services era, where intelligent systems drive value-added services, proactive support, and predictive citizen engagement. To fully realize the potential of this stage, we must focus on effectively managing data, services, APIs, and AI models, ensuring that government services are not only efficient but also intelligent and citizen-centric. There is an urgent need to expand and establish governance on this emerging ecosystem both at Center and State levels. 

Key elements for AI enabled transformation in Government services delivery 

To fully realize AI's potential in transforming government services, key elements that must be considered are: 

DataXChange: Breaking down silos in data availability is crucial for efficient public service delivery. Initiatives like eGovernance and eGramSwaraj have already started digitizing data, but a more cohesive approach is needed to streamline data integration and access across government departments, states and local bodies. While keeping the ownership with respective bodies, DataXChange could be a single source of information for Services consumption, AI model training and public data consumption. Enabling access end points with relevant security measures thru platforms like ODG will help meet this goal. Central, State and local bodies participation is crucial in meeting this goal. 

ServiceXChange: Governments alone cannot provide all the value-add services. Promoting services exposure and participation from private organizations in the era of AI enabled transformation can enhance public service delivery. ServiceXchange can provide services as API's end points which are available for public and internal departments consumption. Platforms like API Setu and user-facing services such as Umang is a good example, but there is room for greater collaboration and innovation with private participation.  

A Third-party startups consortium can be formed to onboard and extend value add services with an agreement to Government. These can be provided through APISetu platform for consumption extending limited set of Third-party services that are available now in APISETU. Consortium can be either state managed or central government managed initiative to onboard such marketplace solutions and provide value added services in multiple sectors. Services utilized from third parties can be paid (based on API consumption) either by Govt. or by end users based on policy decisions. Existing support infrastructure provided through eMarketPlace and MEITY Startup Hub can be used to promote participation of startups & adoption in Government provided services. 

AIXChange: This involves creating a collection of AI models tailored to specific government service needs. These models could include government-sponsored initiatives like Bhashini, free / open platforms like OpenNyai, Jugalbandi and commercial third-party models like Kisan AI Dhenu. Extending models specific to each sector needs is the key to bring in Intelligence in Government Services. Based on value proposition in Services such AI models can provide value added services. 

Governance & Regulatory Authority: Establishing a regulatory and ownership body to oversee data, services, and AI models is essential. This authority would manage security, policies, access control, and data governance, ensuring that AI models are developed and deployed responsibly and effectively. A central authority could handle common functions, while state governments manage entities specific to their regions. This regulatory body can perform Governance and regulatory functions similar to that of TRAI in telecom and IRDAI in Insurance domain. 

Conclusion

Adopting AI for government service transformation offers numerous benefits: 

Speed of Execution: AI can significantly accelerate service delivery, reducing waiting times and improving efficiency. 

Building Trust: Transparent and efficient AI-driven services can increase public trust and attract investors. 

Wider Reach: AI enables governments to reach more people, addressing diverse needs and achieving multiple goals simultaneously. 

Cost Reduction: AI can optimize resource use, leading to cost savings and more sustainable operations. 

Innovation: By reducing complexity and fostering innovation, AI can transform public services, making them more responsive and effective. 

Early Threat Detection: AI's predictive capabilities can help identify and mitigate risks before they escalate. 

Partnerships: Public-private partnerships can drive AI-based transformation, leveraging the strengths of different stakeholders to achieve common goals. 

Data Governance: Robust data governance and regulation are essential to ensure the success of AI initiatives, protecting personal data and maintain public confidence & trust. 

In conclusion, the transformation of government services through AI is not just a possibility, it is an imperative. With right strategies, governance, and partnerships, AI can revolutionize public service delivery, making it faster, more efficient and more transparent. India, with its growing focus on AI, is well-positioned to lead this transformation, but a concerted effort is required to fully realize its potential. 

Multiple External Sources