Gen AI in Governance: Can AI transform bureaucracy in developing countries?

Imagine needing a simple document or approval from your local government office, find yourself navigating a complex process involving multiple steps and long waiting times. For millions across developing economies, this isn’t just a minor inconvenience, it’s a common part of accessing essential public services. Whether it’s securing a food distribution card, an identity card, property-related stamping, or access to critical welfare schemes, ordinary people often spend days, sometimes weeks, navigating slow and complicated government systems. These delays don’t just waste time, they can decide whether a child attends school, a family receives food, or a business can open its doors. 

At a macroeconomic level, these often deter investments vital for several ongoing and proposed critical projects. Despite being the world’s fourth-largest economy, continues to experience service delivery challenges that are not uncommon in other developing countries. Persistent delays across various service levels continue to reflect challenges common to other emerging nations.

In 2023, rating agency, Moody’s Investors Service predicted that “the pace of investment in India’s manufacturing and infrastructure sectors could decrease due to slower policy implementation and bureaucracy despite the economy’s strong potential.” It added that factors like the lack of certainty around the time needed for land acquisition approvals, regulatory clearances, obtaining licenses and setting up businesses can “materially prolong” project gestation. 

Studies have corroborated the trend and have listed various reasons for bureaucratic delays in reforms across developing countries. According to research, Investigating the Challenges of Bureaucratic Reform in Developing Countries: A Case Study Approach, institutional resistance to change, political interference, and lack of transparency, administrative inefficiencies, and policy inconsistencies have collectively contributed to the difficulty of achieving meaningful reform in developing countries. 

In such a scenario, there is growing interest in how technology, especially generative AI, can help governments standardise and implement the services to serve the people more efficiently. Think of AI as a reliable digital assistant, tirelessly handling repetitive tasks that otherwise clog up the system: preparing standard procedures and documents, translating essential forms into local languages, or answering routine citizen questions online at any hour. In some countries, experiments with AI-powered chatbots and document processing are already reducing waiting times, and making services more accessible, even remotely.

But can widespread use of generative AI overcome the challenges and provide an easy fix? Some of these challenges remain complex, especially when the country is as big as India.

The challenges 

Complex or missing data: AI works best with clean and organised digital records. Many departments still rely on worn-out paper files or incomplete databases.

Patchy digital infrastructure: Millions, especially in rural areas across developing countries, do not have stable internet or reliable electricity, making high-tech solutions hard to reach those most in need.

Technology can be intimidating: Many public workers—and citizens—are just getting used to computers, let alone sophisticated AI tools. Changing habits takes patience and support.

Privacy and bias are real concerns: There is genuine concern that generative AI can be used to manipulate personal information or make unfair decisions, especially if not monitored closely. The recent case of Grok, the AI chatbot from Elon Musk, was reportedly amplifying and encouraging hate speech.

Political intervention and corruption: Bureaucracies often operate within legacy systems that have been around for decades. And while that can create a sense of order and consistency, it also means they often struggle to adapt when outside forces push for change. A lack of sustained political commitment to change and reform is another impediment to reform. At times, influence from various stakeholders may affect decision-making and contribute to reduced efficiency or transparency in certain processes – something that the use of AI will eliminate to a greater extent. 

In several instances, the use of AI has been seen as a disruption of the conventional process instead of an improvement. As a parallel problem, emerging economies often lack standards and process structures. India, for example, has successfully implemented certain standards and processes to regularise a few sectors including fintech, real estate etc.

How do we implement AI and create mass appeal?

So, how can we ensure that generative AI models become a helping hand, not another hurdle? The World Development Report 2025 by the World Bank suggests setting standards across the economy, society, environment, and government—and periodically revising and raising standards to increase efficiency in services. 

In line with this thought, there are things we must do to implement the use of generative. There is a need to digitise records and get the data sets organised, while building systems that protect people’s privacy. In addition, there is a need to channelise the investments in the expansion of the Internet and connectivity infrastructure. Rural communities should not be left behind in this expansion.

For developing countries to embrace change, training must reach both officials and citizens. True transformation lies in transparent AI use, where communities help shape standards and know how to raise concerns.

However, any policy execution is dependent on successful pilots. It is worth mentioning that both localised state-level services standards should be in sync with centre-led reforms and initiatives. Fragmented reforms will result in fragmented success. In this context, India has been leading in the active implementation of automation and generative AI. The country presents a few successful examples for other developing nations. India’s new BharatGen model, launched in June 2025, is capable of processing large policy documents in 22 languages, enabling faster file movement across departments. Similarly, Sarvam-1, India’s first sovereign voice-enabled Large Language Model or LLM, allows real-time conversational support for government officers in 10 regional languages.

AI has the power to reshape the governance in developing countries, making the bureaucracy more open, efficient, and responsive to everyday needs. Around the world, governments are experimenting with AI in limited ways. Estonia’s e-governance model has cut down approval times by 80% through AI-assisted decision-making.

Singapore is leveraging AI to address citizen grievances, while Denmark stands at the forefront of digital governance, topping the UN’s E-Government Development Index. Its targeted investments in ICT, human capital, and e-participation showcase how AI can empower transparent and effective governance. 

Implementation of AI could lead to significant success. For instance, as per India AI Mission data (2025) from the Ministry of Electronics and Information Technology (MeitY), nationwide adoption of GenAI in 10 high-impact government workflows could reduce processing times by 40–60% and save ₹15,000–20,000 crore annually.

However, these benefits will not come overnight—they require thoughtful planning, investment in skilled talent and appropriate technology, and a commitment to equity, accessibility, and inclusion. If governments prioritise citizen needs throughout this transformation, AI can help make the daily quest for public services simpler, faster, and more approachable for everyone.

This article was published in TimesTech on 11 August 2025. Read here