Man in a suit touches holographic blue UI panels against a nighttime city skyline.

AI and Managing Public Governance

 

By Waqar Naeem Qureshi | Director General, Information Technology Solutions, Punjab Information Technology Board

 

There is pressure on governments around the world to do more, do it better, and act faster–while staying within financial constraints.

The ubiquity of the internet, mobile, computing and digital platforms has led to a major shift in citizen expectations.  Citizens today expect a participatory, evidence-based and time-sensitive approach to policymaking, coupled with speedy, digitized and personalized delivery of public services.

The public sector leaders respond by continuing to explore ways to improve governance with digital technologies. There have been rapid advancements in emerging technology including Artificial Intelligence (AI), robotics and tools for predictive analytics that provide promising solutions.

As public sector organizations become more data driven, the policy cycle itself continues to evolve into a framework that allows continuous evaluation and timely policy tweaking. 

Better real-time data from new technologies is possible today. For instance, mobile applications, satellites, ground-sensors, internet of things, vehicles, and social media enables AI and machine learning systems to provide continuous evidence-based insights to improve policy outcomes and delivery of public services. These new technologies allow for governments to better manage citizen expectations, becoming more responsive, working at faster speeds and with much more transparency. 

The adoption of AI based systems in the public sector offers exciting prospects. However, governments must continue to develop and refine AI policy and governance frameworks by ensuring the following elements below. 

  • Ethical use of AI technologies with human oversight. 

  • Data protection and security.

  • Rights of data providers and appropriate legislation.

  • Fairness and agency accountability.

  • The goal should be to promote human-centered use of AI systems.

Government AI Use Cases from Around the World

According to the World Bank, governments are actively integrating AI-based systems for policy improvement and delivery of public services.1 These initiatives include:

  • Citizen engagement: AI has been used to analyze citizen sentiments from 21 million comments received on US Government’s policy on NetNeutrality shared online.

  • Compliance and risk management: In Armenia, AI has helped the revenue agency increase its revenue by six times.

  • Fraud detection, prevention and investigation: In Brazil, AI detected 500 firms owned by the state officials responsible for supervising these firms’ contracts.

  • Robotic process automation: The UK Rural Payments Agency was able to process the backlog of 30,000 pension claims in two weeks, a task estimated to take thousands of hours of manual work requiring many months.

  • Personalized service delivery: AI is helping countries deliver personalized public services in countries like Estonia, Denmark, UK, USA, Singapore, Korea and Japan.

  • Analytics and decision-making: AI is routinely used by government regulators and financial institutions to track illicit financial flows, estimated at US$80 billion in Africa alone.

Public Sector Adoption of AI-based systems in Pakistan

In Pakistan, initiatives on adoption and integration of AI-based systems for improving public sector governance is relatively recent and entrepreneurial.

  • The Government of Pakistan has enacted the Digital Nation Pakistan Act 2024. The act tasks the Pakistan Digital Authority to “carry out oversight, set standards, enforce compliance, and establish any necessary framework and processes in areas assigned by the Commission, including data management and governance, artificial intelligence, virtual assets, and other emerging technologies.”3

  • AI-based systems are being developed for predicting crop yields by analyzing historical data, weather patterns, satellite imagery and ground sensor data. 

  • AI models are being developed to achieve sustainable water usage by analyzing soil moisture, precipitation trends and evapotranspiration rates. 

  • AI systems are also being prototyped for automatic vehicle detection, license-plate recognition, and for predictive crime-analytics. 

Public Sector Challenges in AI Adoption

The government faces several challenges in AI adoption in the public sector. Some key challenges are outlined below.

  • There are inadequate policies and legislation on AI. 

  • There is still an inadequate digital infrastructure for effective and widespread AI adoption.

  • There is lack of data standards and data governance.

  • There is still a lack of digital talent and skills.

Two drones hover over a greenhouse as a control screen shows crop data; leafy beds in foreground.

Recommendations

  • As the internet becomes more pervasive and faster, and big-data becomes even bigger, governments must make efforts to improve overall data literacy within organizations and create a data culture.

  • Appropriate legislation and AI policy formulation must be given careful attention with emphasis on data protection, rights of data providers, human oversight, transparency and agency accountability.

  • Data standardization and governance are critical for achieving effectiveness and interoperability of AI systems.

  • Governments should take a whole-of-government approach towards AI adoption. However, implementation should be iterative. This means identifying the problem and conceptualization, followed by rapid prototyping, deployment and then moving to scale. 

  • Feedback loops must be built into the design and deployment processes of AI systems at every stage. 

  • In addition to effective collaboration with relevant academia and the private sector, governments must take meaningful steps to attract and retain a highly capable technology workforce.

1.    World Bank, Artificial Intelligence in the Public Sector: Summary, World Bank, 2021, [online] Available at: https://documents1.worldbank.org/curated/en/746721616045333426/pdf/Artificial-Intelligence-in-the-Public-Sector-Summary-.pdf 
2.    McKinsey & Company, ‘Unlocking the Potential of Generative AI: Three Key Questions for Government Agencies’, McKinsey & Company, 2024.  Available at: https://www.mckinsey.com/industries/public-sector/our-insights/unlocking-the-potential-of-generative-ai-three-key-questions-for-government-agencies
3.    Government of Pakistan, The Pakistan Code, Government of Pakistan, [online] Available at: https://pakistancode.gov.pk/pdffiles/administrator2c2fd2fe7da1a657c40589a0705b3e20.pdf