10 ways AI-powered public services are driving innovation in government

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Public services and innovation in government are entering a new era of speed and satisfaction, thanks to the power of AI.

A good example of this transformation is the tax chatbot by the Internal Revenue Service, which assists taxpayers with filing their tax returns.

Since its implementation, it has led to a 30% reduction in calls to the IRS helpline.

Despite such advancements, innovation in government still faces challenges, including inefficiencies and high costs in public service delivery. 

In 2023, the U.S. Government Accountability Office (GAO)  highlighted over 100 new actions that could reduce costs or boost revenue, such as optimizing procurement processes and reducing program redundancies.

In this context, AI offers solutions by automating processes, improving decision-making, and enhancing citizen engagement. This article will go into detail about ten ways that AI-powered public services are promoting innovation in government.

What is the role of AI in government?

AI-driven innovation in government utilizes advanced technologies such as deep learning, predictive analytics, and robotic process automation (RPA) to streamline operations. Deep Learning models analyze complex datasets for insights, while predictive analytics forecast trends for proactive decision-making. 

Let’s take a closer look at some of the latest developments to paint the complete picture:

• The White House’s FY 2023 budget proposal allocates $974.7 million for non-defense AI research and development—an increase of more than 20% compared to FY 2022. 
• According to a 2022 Deloitte survey, 45% of government executives plan significant investments in robotic process automation (RPA). 
• McKinsey Global Institute has projected that by 2030, AI could help generate up to $3.5 trillion annually in value for public-sector organizations worldwide.
  

• The World Government Summit's "Government 2071 Guidebook" explores future government interactions with citizens, emphasizing the role of AI and innovation in public service delivery. 

Role of AI in governance

1. Machine Learning (ML): ML algorithms can identify patterns and make predictions for tasks such as fraud detection, resource allocation, and predictive maintenance.
2. Natural Language Processing (NLP): This technology powers chatbots and virtual assistants to handle citizen inquiries, provide information, and even process applications.
3. Computer Vision (CV): It uses advanced algorithms to interpret and process images or video content. In governance, it can assist in public safety measures, infrastructure monitoring, and automated document processing.
4. Predictive and Prescriptive Analytics: Predictive analytics enable agencies to allocate resources more effectively, improve policy decisions, and anticipate citizens’ needs.
5. Robotics and RPA (Robotic Process Automation): RPA utilizes software “bots” to automate repetitive tasks, such as data entry and form processing, freeing employees to focus on higher-value services. Physical robotics can assist in search and rescue operations, disaster response, and infrastructure maintenance.
6. Edge AI: It processes data locally on devices, enabling faster decisions, stronger privacy, and real-time services like traffic and environmental monitoring, as well as emergency response in governance.
7. Cybersecurity and Threat Detection: AI-driven cybersecurity can detect suspicious behavior or anomalies in real time. Governments can deploy machine learning tools to automate threat detection, prioritize risks, and respond swiftly to potential breaches.
8. Citizen Engagement and Feedback: AI-powered chatbots, virtual assistants, and sentiment analysis tools enable governments to engage with citizens. 
9. Interoperability and Data Governance: Robust data governance frameworks and standardized protocols help agencies securely exchange information, maintain data integrity, and provide unified, efficient services to citizens.

Example:

The US Department of Defense (DoD) uses AI and machine learning tools to analyze data from various aircraft systems, predicting when maintenance is needed before failures occur. 

This approach, known as Condition-Based Maintenance Plus (CBM+), has been integrated into the Air Force's Predictive Analytics and Decision Assistant (PANDA) system. 

10 ways AI is driving innovation in government

A 2023 PwC survey revealed that 75% of public sector leaders believe AI is crucial for improving operational efficiency, while 68% reported enhanced citizen satisfaction due to AI-driven services.

The following points illustrate how AI supports this transformation for innovation in government:

Automating citizen services

Automated citizen services enhance service delivery and build greater trust, communication, and engagement between citizens and their governments. For example, in June 2023, the U.S. General Services Administration (GSA) introduced the Automated Contact Center Solutions (ACCS) Special Item Number (SIN) on the Multiple Award Schedule. This will help government agencies streamline their communications, improve citizen satisfaction, and increase overall efficiency in executing their missions.On the other hand, predictive analytics help agencies like the U.S. Social Security Administration proactively address service delivery issues. 

Streamlining welfare distribution

AI systems use machine learning techniques to examine large datasets and identify irregularities that could be signs of fraud or mistakes in welfare distribution. Research by the University of Exeter shows that AI predicts welfare dependency with 20% greater accuracy than traditional methods. Analyzing socio-economic and demographic data from Australia's social security system, AI algorithms identified individuals at risk of becoming long-term benefit recipients.

Enhancing public safety

Predictive policing systems use AI to analyze historical crime data and identify patterns that can forecast future criminal activity.In the Netherlands, predictive policing systems have been implemented in pilot cities to bolster innovation in government, resulting in a noticeable reduction in crime rates and contributing to community safety.

Improving disaster response

AI-driven systems process real-time data from sensors, satellites, and social media to predict and respond to natural disasters.In Japan, AI on drones predicts natural disasters like earthquakes and typhoons, enabling faster, more effective responses to save lives and reduce damage. 

Optimizing urban planning

Urban development policies are informed by AI technology that evaluates data on population trends, energy usage, and traffic flow.Barcelona's state-of-the-art traffic management systems have reduced congestion by 21%.

Personalizing citizen services

In healthcare and education, AI provides individualized recommendations by customizing services according to each user's needs. Estonia's e-government platform uses AI to analyze user data and deliver customized interactions, such as personalized healthcare recommendations and educational resources.

Facilitating data-driven policy-making

AI uses data mining and machine learning techniques to detect patterns of tax evasion and improve collection efficiency. A recent example of AI facilitating data-driven policy-making is in Singapore, where the government has implemented AI to analyze data. 

Modernizing tax collection

Through the analysis of financial data, AI detects trends in tax evasion and increases the effectiveness of tax collection. The French tax administration utilized AI and satellite imagery to identify 20,000 undeclared swimming pools. This approach resulted in an additional €10 million in property tax revenue. 

Enhancing healthcare services

Predictive analytics and virtual healthcare assistants are powered by AI, which also enhances patient outcomes. The NHS in the UK uses AI for early diagnosis of diseases like cancer, enabling timely treatment and improving patient survival rates.

Supporting cybersecurity efforts

By examining network data and spotting irregularities, AI systems are able to identify and eliminate cybersecurity threats.Governments that implemented AI-based security measures saw a significant reduction in cyber breaches in 2023, protecting sensitive data and maintaining public trust.