Published Jun 07, 2026 | 7:00 AM ⚊ Updated Jun 07, 2026 | 7:00 AM
Representational image. (iStock)
Synopsis: While Bengaluru struggles with governance inefficiencies, AI alone cannot solve them. It’s a responsibility problem. AI could make governance more efficient, but not necessarily better, unless the accountability and responsibility issues are solved.
The people of Bengaluru face the constraints of governance daily. After years of data collection on mobility patterns, they still sit in traffic. They traverse various agencies and are expected to experience a smooth interaction with civic services. They face the prospect of flooding, waste management problems, infrastructure bottlenecks and more — regularly — in a city that is also known as the technology capital of India.
This is hardly surprising, as artificial intelligence (AI) has become a popular buzzword for the next big answer to public-sector inefficiency. AI is expected to transform governance — faster, smarter, and more responsive in various aspects, such as traffic management, urban planning, welfare delivery, and grievance redressal.
It’s natural to be hopeful. But it has the potential to mask a more fundamental truth. The issue of governance in India cannot be attributed to technology failure. It’s a responsibility problem. AI could make governance more efficient, but not necessarily better, unless this issue is solved.
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This differentiation is important because all too often governments confuse technological modernisation with institutional change. India has enacted a lot of reforms and taken steps over the last decade to make public services more digital.
A generation ago, citizens could obtain certificates, monitor applications and use government services only by office visits. Now, citizens can obtain certificates online, pay digitally, monitor applications, and interact with government portals — things which were inconceivable a generation ago.
However, despite the advances of digitisation, many of the frustrations faced by citizens remain. Slowness in the process, overlapping jurisdictions, poor coordination among agencies and inconsistent implementation are frequent occurrences.
While technology has often made existing systems more efficient, it hasn’t been the same in making them more accountable.
AI is now up to take this transformation ahead. AI systems can handle massive amounts of data, spot trends, forecast customer needs for services, and automate recurrent tasks. AI could be used to manage traffic lights, predict water levels in reservoirs, pinpoint infrastructure risks, or optimise waste collection routes, among other applications.
Advanced analytics could be applied to welfare departments to identify fraud and enhance the targeting of welfare beneficiaries. Predictive models can be created and shared with public health organisations to assist in the prediction of emerging disease outbreaks.
These are possibilities which have to be taken seriously. But it is not a straightforward “as is” relationship between technology and governance. In fact, there are many instances of governance failure despite adequate information.
Today, governments have more data at their disposal than ever. The challenge is frequently a lack of action or a lack of accountability.
Bring the governance issues of Bengaluru to the fore. Traffic cameras, sensors, GPS on public transport, digital records of properties, and citizen grievances and complaints generate huge volumes of data for the city. However, several civic issues remain pending since accountability is split among several agencies with overlapping mandates.
None of the algorithms can solve institutional fragmentation. Technology can help with decision-making, but it can’t replace administrative coordination or political accountability.
This is also true when it comes to welfare delivery. AI has the potential to clearly detect anomalies and optimise targeting. Automated systems can also produce fresh patterns of exclusion. Although the data may be accurate, the algorithms used could be flawed, or there may be incomplete data, resulting in deserving citizens being denied benefits.
If these types of errors are made, who is accountable? The software developer, the department using the system or the official responsible for the programme?
It’s important for democratic governance to have answers to such questions. An associated issue is the so-called “automation bias,” which refers to the tendency to overtrust the algorithmic suggestions.
Officials may hesitate to challenge the outputs of an AI tool due to the perceived objectivity or scientific nature of the results. AI-generated results can give the impression of being objective or scientific, which may lead to hesitation among officials to question them.
However, algorithms are only as accurate as the data and assumptions that go into them. Judgement is essential, especially when the rights, livelihoods and access to public services are at stake.
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That’s why innovation is not the only issue to be discussed when considering AI in governance. It should emphasise equal accountability. Three principles could shape the responsible use of AI by governments.
First, transparency. There is a need to ensure that citizens are informed regarding the use of AI systems in decision-making. The reasons and considerations behind these systems and their recommendations should be clearly explained by public authorities.
Second, auditability. The independent review process should evaluate and verify accuracy, fairness, and lack of systematic bias in algorithms. It is unfeasible for citizens to trust public institutions with systems that are essentially black boxes.
Third, human oversight. All important decisions made with the help of AI will be subject to human review and appeal. Citizens should be able to contest results and to approach a specific public authority for redress.
Karnataka is a unique state to spearhead this discussion. With its homegrown capabilities, the state has the knowledge and potential to showcase the transformative power of AI in enhancing governance while maintaining democratic protections. Rather than just a government with AI, it’s about creating the right government for AI. Its purpose is to provide responsible governance with the help of AI.
Governments can use AI to effectively digest information and process it on time, and it can enhance efficiency in many ways. However, efficiency alone is not a form of governance.
The true measure of technological advancement is not asking whether public institutions are using sophisticated tools. It is asking whether citizens have access to more transparent, responsive and equitable governance.
(Views are personal. Edited by Muhammed Fazil.)
