Enhance productivity with generative AI

  • 15 minutes

One of the ways that AI can make a significant impact in the public sector is by enhancing productivity. When public sector organizations use AI, they can empower the workforce and open up new avenues of efficiency and creativity in areas like:

  • Simplifying case management by helping case workers manage heavy workloads with AI-generated drafts, insights, and automation
  • Simplifying rule making and accelerating the process by using AI to help draft and refine policies, gather public comments, and then analyze the comments
  • Empowering constituents to engage with public sector organizations more effectively, which results in shorter wait times, faster resolution, and informed support
  • Helping IT teams migrate legacy apps by documenting their functionalities, translating legacy code, and creating translations of app functions

Let’s explore each one of these use cases.

Simplify case management

In the following video, Sara Nagy, Senior Director of Customer Engagement at Microsoft, explains how generative AI can enhance productivity for case workers by managing heavy workloads with AI-generated drafts, insights, and automation.

Simplify rulemaking

Rulemaking is a long, complex, and costly process that includes several challenges. For example:

  • Writing and understanding the style and language of regulatory text can be difficult
  • Public participation can be a laborious process with many stakeholders
  • Rulemaking can involve contentious topics with conflicting interests and the possibility of litigation
  • Public employees need to maintain inclusive, fair, and equal access across both marginalized and powerful groups

AI can help enhance employee productivity around rulemaking in the drafting phase. Teams can use an AI assistant to create initial drafts with natural language prompts and feedback. When the draft undergoes refinement, which involves many internal stakeholders like subject matter experts and legal counsel, the AI assistant can help flag potential errors. Then, during the public comment review stage, different stakeholders can engage with an AI assistant to understand and provide feedback on the proposed rule. Lastly, after gathering public comments, public affairs staff can use generative AI in the comment analysis phase to summarize the comments and find trends, concerns, and insights to inform their decision making.

Empower constituents

Generative AI can help constituents engage with public sector organizations more effectively by:

  • Decreasing call center wait times and hang-up rates
  • Offering constituents quicker options to connect through chat or email support
  • Making constituent data and information more accessible for agency support agents
  • Regaining trust with constituents who might already associate public sector organizations with poor support experiences

AI-powered conversational assistants use natural language and contextual understanding to comprehend and interpret user inputs with high accuracy.

The assistant also uses semantic search to search concepts and meaning when the user asks a question. The conversational continuity of the assistant provides a longer dialog and helps the user feel more at ease, but—more importantly—the use of the AI-powered assistant frees up human employees to focus on more complex tasks.

Migrate legacy applications

Many public sector organizations run legacy applications, which in today’s technology environment, can cause problems for an organization and its employees. Problems with managing legacy applications might include:

  • Shortage of skilled programmers
  • Dependence on outdated hardware
  • Scalability challenges
  • Knowledge transfer
  • Compatibility issues
  • Limited vendor support
  • Security concerns
  • Regulatory compliance

Generative AI can help public sector organizations modernize legacy applications and outdated code. AI can help public sector organizations migrate legacy algorithms and functions using AI in the following areas.

Grounding

Developers submit examples of the current code to the generative AI model. The AI model learns the pattern and syntax.

Assessment

Generative AI reviews the code and helps document its functionalities to determine which part of the code can be migrated.

Initial drafting

Developers make initial translations of the legacy algorithms and functions and assess the baseline performance. If developers see flaws, they might choose other sample code and go back to step one and ground the model on the new material.

Development and iteration

The development team uses AI to create a first draft, which the development team reviews and edits. Generative AI might help refactor the new code to improve quality and efficiency.

Once the code is complete and thoroughly tested, the legacy application can be retired, and the new cloud-based application can go live.