Published: 12:10 AM, 20 April 2026
How Data And Algorithms Are Reshaping Public Policy Formation
MD. Noor Hamza Peash
Data structures and algorithms (DSA) are the core building blocks of computer science. Think of data structures as the containers or filing systems used to store information, and algorithms as the step-by-step "recipes" that tell a computer how to process that information to solve a problem.
The relationship between the two is symbiotic: an algorithm needs a data structure to work on, and a data structure is only useful if there are algorithms to manipulate it. For example, if you have a massive list of names (data structure), you need an efficient search algorithm to find one name quickly without checking every single person.
The transition from generative artificial intelligence to agentic artificial intelligence represents a significant turning point in the evolution of digital governance. In countries like Bangladesh, where public administration is gradually embracing digital transformation, this shift has far-reaching implications. It is not merely a technological upgrade but a structural change that can redefine how governments function, make decisions, and interact with citizens. As administrative systems become more complex, the demand for intelligent, adaptive, and autonomous digital tools is increasing, positioning agentic AI as a transformative force.
Generative AI, which has gained widespread attention in recent years, primarily operates as a prompt-based system. It generates responses, content, or solutions based on user input and predefined data patterns. While it has proven useful in areas such as communication, data processing, and service delivery, its limitations become apparent in complex governance environments. Decision-making in public administration requires not only information generation but also contextual understanding, accountability, and alignment with legal and ethical standards.
Agentic AI introduces a new paradigm by enabling systems to act autonomously within defined frameworks. Unlike generative AI, which waits for instructions, agentic AI can initiate actions, analyze situations, and make decisions based on objectives and constraints. This capability is particularly relevant for governance, where timely and accurate decisions are essential. By integrating reasoning abilities and advanced data analysis, agentic AI systems can support more efficient and responsive administrative processes.
One of the defining features of agentic AI is its ability to combine logical reasoning with tool integration. Large Language Models, when enhanced with external tools and data sources, can move beyond simple text generation to perform complex tasks. These systems can analyze legal documents, interpret policy frameworks, and provide actionable recommendations. This integration allows governments to automate routine processes while maintaining a high level of accuracy and compliance with established regulations.
In the context of public administration, the adoption of agentic AI can significantly improve service delivery. Administrative procedures that traditionally require multiple layers of approval and manual processing can be streamlined through intelligent automation. Citizens can benefit from faster responses, reduced bureaucratic delays, and more transparent systems. This transformation has the potential to enhance trust in public institutions by making governance more accessible and efficient.
The application of agentic AI also extends to policy formulation and implementation. By analyzing large datasets, these systems can identify trends, predict outcomes, and suggest evidence-based policy options. This data-driven approach can improve the quality of decision-making and reduce the risk of policy failures. Governments can use these insights to design more effective programs that address the needs of diverse populations, ensuring that public resources are utilized efficiently.
However, the integration of agentic AI into governance systems raises important legal and ethical considerations. Decisions made by autonomous systems must align with constitutional principles, human rights, and administrative laws. Ensuring accountability in cases where AI systems influence or make decisions is a critical challenge. Clear guidelines and regulatory frameworks are necessary to define the scope and limitations of AI in public administration, preventing misuse and protecting citizen rights.
Another significant concern is data privacy and security. Agentic AI systems rely on vast amounts of data to function effectively. This includes sensitive information related to citizens, institutions, and government operations. Protecting this data from unauthorized access and misuse is essential. Robust cybersecurity measures and strict data governance policies must be implemented to ensure that the benefits of AI do not come at the cost of privacy violations or security breaches.
The successful adoption of agentic AI also depends on the availability of skilled human resources. Public sector employees must be trained to understand, manage, and oversee AI systems. This requires investment in education, training, and capacity-building initiatives. Without a knowledgeable workforce, the implementation of advanced technologies may lead to inefficiencies and unintended consequences. Building technical expertise within government institutions is therefore a key component of digital transformation.
International experiences demonstrate that the integration of advanced AI technologies can significantly enhance governance systems. Countries that have invested in digital infrastructure and innovation are better positioned to leverage the benefits of agentic AI. For Bangladesh, learning from these experiences can provide valuable insights into best practices and potential challenges. Collaboration with global partners can facilitate knowledge exchange and support the development of effective AI strategies.
While the potential benefits of agentic AI are substantial, it is important to recognize that technology alone cannot solve all governance challenges. Institutional reforms, transparency, and public accountability remain essential components of effective administration. AI should be viewed as a tool that complements human decision-making rather than replacing it entirely. A balanced approach that combines technological innovation with strong governance principles is necessary for sustainable progress.
The evolution from generative AI to agentic AI marks a new chapter in the relationship between technology and governance. For Bangladesh, this transition offers an opportunity to modernize public administration and improve service delivery. However, it also requires careful planning, regulatory oversight, and ethical considerations. By adopting a strategic and inclusive approach, the country can harness the potential of agentic AI to build a more efficient, transparent, and citizen-centric governance system.
MD. Noor Hamza Peash is a legal
researcher and a columnist.
