Intelligent Automation in Government: Top Examples for 2024

Government agencies worldwide are adopting intelligent automation to modernize operations and better serve citizens. This guide will explore top use cases with examples, benefits, and advice for implementation.

What is Intelligent Automation?

Intelligent automation combines robotic process automation (RPA) with artificial intelligence (AI) technologies like machine learning, natural language processing (NLP), and computer vision.

While RPA bots automate repetitive digital tasks, AI allows systems to process unstructured data like text, image, and voice. Together, they can automate increasingly complex end-to-end workflows.

According to Deloitte, intelligent automation could free up 1.3 billion hours for US government workers. Let‘s examine key use cases driving adoption.

Legacy System Integration

Modernizing legacy systems is a top priority for governments globally. In the US alone, legacy systems cost $337 million annually to operate.

Intelligent automation provides a bridge to integrate legacy systems with modern cloud platforms:

  • Screenscraping – Computer vision bots can log into legacy green screens, understand the interface, and extract data.
  • Data migration – Bots can transfer legacy data to new systems on-demand or at scheduled intervals.
  • Data validation – Automating checks between systems improves data accuracy.

For example, the UK Home Office used RPA to extract case data from legacy immigration systems into a new caseworking system. Bots automated the migration of 11 million records, enabling retirement of the legacy system.

Automated Reporting

Public agencies produce volumes of financial statements, performance reports, and operational analytics. Report generation requires:

  • Logging into multiple legacy systems and databases
  • Extracting and combining structured and unstructured data
  • Manual effort to create insights

RPA bots can log into systems, scrape data, and create scheduled reports automatically. NLP and optical character recognition (OCR) can extract insights from unstructured data.

The Australian Taxation Office reduced report generation from 4 hours to 4 minutes using RPA. Humans just verify outputs instead of manual reporting.

Enhanced Citizen Experience

Intelligent automation improves government services across channels:

  • Chatbots handle common citizen inquiries with NLP, route complex issues to the right agents.
  • Document processing bots extract data from forms and paperwork digitally submitted by citizens.
  • Back-end automation updates government systems during and after citizen interactions.

For example, New Zealand‘s Immigration Department uses chatbots to answer visa and application questions. The bots resolve 78% of inquiries automatically, improving applicant experience.

Public Sentiment Analysis

Government agencies can apply NLP and machine learning to:

  • Extract public sentiment data from news, social media, surveys.
  • Classify text as positive, neutral or negative sentiment.
  • Identify key themes and topics.

This allows agencies to monitor public opinion and perceptions of government services.

For instance, the Singapore government uses sentiment analysis to analyze feedback about COVID policies across media and adapt their pandemic response.

Intelligent Automation in Action

Leading government agencies worldwide already benefit from intelligent automation:

Utah Unemployment Insurance

Utah‘s Department of Workforce Services automated the processing of over 200,000 unemployment insurance claims during COVID-19. Bots extracted handwritten data from forms, validated it, and updated systems. This kept up with a 13X increase in claims.

Canada Border Services Agency

The CBSA applied RPA to automate publishing reports for the agency‘s website. Bots log into systems, extract data, and create publishable CSV files. This saves 4,000 manual hours per year.

Department of Human and Health Services, Victoria, Australia

Victoria‘s DHHR used RPA to speed up timesheet processing across 6,700 employees. Automation saves 45,000 hours per year, improving payroll accuracy and freeing up 5 FTEs.

Challenges in Government Automation

Despite the benefits, governments face unique barriers to automation:

  • Legacy systems with fragmented, siloed data.
  • Outdated technologies limit integration with modern platforms.
  • Tight budgets and long procurement cycles restrict technology upgrades.
  • Organizational resistance from change-averse bureaucracies.

That‘s why taking an iterative approach is recommended – starting with proofs of concept in targeted functions like reporting and citizen services.

Gradually scaling across the enterprise can help agencies adapt while optimizing costs. Monitoring success metrics like hours saved, costs reduced and citizen satisfaction is key.

The Future of Intelligent Automation

Intelligent automation is reaching an inflection point for government. Per Deloitte, 82% of government executives believe it can improve mission outcomes and 63% plan to adopt automation within 2 years.

Beyond efficiency gains, AI-enabled automation can provide predictive insights to enhance decision making across policy, operations, and service delivery.

However, thoughtful adoption is crucial to avoid pitfalls like biased algorithms that inhibit equitable access to government services. With the right strategy, automation can make government more efficient, responsive, and empowering for citizens worldwide.

Ready to Automate your Agency?

Hope this guide provided useful insights into intelligent automation‘s potential in government. To learn more about use cases, vendors, and implementation support, see:

Let me know if you have any other questions!