Every day, millions of constituents depend on tax and motor vehicle agencies for essential services such as filing returns, renewing registrations, and updating licenses. Yet many of these agencies are stretched thin, managing aging systems, fragmented data, and rising constituent expectations for fast, digital-first service. AI offers a practical path forward.

AI transforms how tax and motor vehicle agencies serve constituents and manage operations. AI makes it possible to improve customer service through expanded self-service options with multilingual capabilities. AI can boost employee productivity by improving data integration and access while breaking down data siloes.

In this post, we explore how Amazon Web Services (AWS) AI capabilities can transform constituent services and business operations. We also highlight some customer success stories and offer some practical advice on how to get started.

How to get started

Start with the business problem, using data to quantify and qualify it as necessary. Identify your pain points in the constituent experience or in your operations. Understand if you’re meeting your agency’s standard for hold times or application processing times. Set a measurable business outcome for your problem.

Next, think about data strategy. Your data will be what differentiates your AI solutions and drives business value.

It’s also important to review AI policies for your agency. There might be limitations for using AI with customers externally, but you can still use AI to gain efficiency. Another approach can be to start your AI project using information that is publicly available, such as content on your website and instruction books for tax forms and driver licensing. This helps you manage risk while your agency learns how to use these tools effectively and responsibly.

Improving constituent experience with AI

Constituents aren’t calling between 8:00 and 5:00 anymore—they’re texting at midnight, emailing on weekends, and expecting instant answers. Traditional phone-only contact centers can’t keep up, and they don’t meet the expectations of diverse and younger constituents. Amazon Connect Customer is a turnkey solution that delivers AI-powered support meeting constituents where they are, whenever they need help.

The Kentucky Transportation Cabinet (KYTC) transformed their operation in only 6 weeks with Connect Customer. They added a chat-based assistant to enable self-service for their customers, and it’s now averaging 900,000 interactions per month. KYTC is also using a question-and-answer chat assistant, call-back queues, and real-time conversational analytics to become more efficient. Their average call duration has dropped from 3–4 minute per call to less than 2 minutes with Connect Customer.

You can modernize your existing interactive voice response (IVR) systems quickly with Connect Customer and Amazon Lex while offering multilingual capabilities too. https://aws.amazon.com/lex/Amazon Lex supports natural language understanding to implement conversational AI into existing business processes.

The Alabama Department of Revenue built and deployed an AI-powered IVR system in only 8 days with AWS. The transformation increased call capacity from 150 to 2,000 calls per day during peak tax season and reduced call duration from 20 minutes to 3. The IVR is multilingual, providing service in both English and Spanish. This functionality didn’t exist before.

You can reduce costs with Connect Customer. The Wisconsin Department of Revenue saved up to 66% over previous call center solutions with Connect Customer pay-as-you-go pricing—no more locked-in contracts or licensing fees.

These results aren’t outliers; they reflect what’s possible when agencies pair modern cloud infrastructure with AI-powered automation.

AI can improve business operations

Your agency collects vast amounts of operational data, but extracting timely insights often requires specialized skills or lengthy report requests.

Amazon Quick changes that equation. Staff can use plain language to ask questions such as, “What were the most common in-person transactions last month?” or “Show me payments by tax type year to date” and get instant, interactive visualizations without relying on data experts or requiring any technical skills.

Amazon Quick provides insights to quickly improve business operations. You can use it to determine average processing times by transaction to help allocate staff. Another use case is identifying which department of motor vehicle (DMV) stations have the highest failure rates for skills tests.

Consider the volume of paper your agency processes daily such as tax returns, title applications, and registration forms. Amazon Bedrock Data Automation enables intelligent document processing (IDP) that extracts, classifies, and routes information from these documents automatically. With IDP, you can speed up processing time, reduce errors, and optimize the use of agency resources. Amazon Bedrock provides a secure infrastructure to modernize document-heavy processes while maintaining data governance and audit trails.

Amazon SageMaker AI is a fully managed service that enables AI model development for tax and DMV use cases. Agencies can train machine learning (ML) models on historical tax return data to identify patterns indicative of fraudulent filings or underreported income. These models can score returns by fraud probability, helping auditors prioritize high-risk cases. This improves audit yield while reducing manual work.

Customers can also combine SageMaker AI with Amazon Bedrock to automate processing of license applications, vehicle titles, and registration documents. ML models can flag inconsistencies, detect fraudulent documents, and verify identity matches. This reduces manual processing time and improves fraud prevention.

Responsible and ethical use of AI

Preserving public trust is a nonnegotiable requirement. Constituents expect their personal data to be protected, and agency leaders need confidence that AI systems are fair, transparent, and auditable. Here’s how AWS helps you meet that standard.

For AI services such as Amazon Bedrock, AWS and third-party model providers don’t store, use, or access prompts, inputs, or outputs for training purposes. Data used with Amazon Nova or third-party models stays private and isn’t used to train or improve large language models (LLMs). For services such as Amazon Connect, customers can opt out of data usage.

AWS provides tools to help you assess and measure AI safety and ethics. Through offerings such as Amazon Bedrock Evaluations and Amazon SageMaker Clarify, you can evaluate models across key responsible AI metrics. AWS supports human-in-the-loop evaluation workflows, which incorporate human review to validate model outputs, provide qualitative feedback, and align AI decisions with agency values and ethical standards.

Security and compliance considerations

You need security and compliance controls when building AI solutions. AWS provides robust security and compliance controls that millions of customers use to protect their most sensitive AI workloads.

AWS provides tools that help you meet IRS Publication 1075 requirements for AWS GovCloud (US) Regions, which call for FedRAMP High, and commercial AWS Regions, which call for FedRAMP moderate. If you’re securing call center interactions, securing AI workflows or building compliant AI applications, AWS offers services such as AWS CloudTrail, which records API calls and account activity for audit trails, and AWS Security Hub, which provides security monitoring across your AWS environment.

You also keep complete control over your data with AWS layered security. This includes customer managed encryption keys through AWS Key Management Service (AWS KMS), geographic storage selection, and granular access controls.

AWS Nitro System provides confidential computing through hardware-isolated environments. AWS personnel can’t access your data, so you build without compromising constituent trust while meeting stringent compliance requirements.

Modernizing government

You can modernize constituent services while reducing costs and maintaining compliance with a thoughtful integration of technology. A small proof of concept is a great way to get started because you can test the feasibility of your ideas and gain confidence without spending a lot of money. Here are other ideas for you to explore:

Ready to go? Contact your AWS account team or AWS Sales supportfile:///C:/Users/ebegan/Downloads/link to discuss your agency’s specific use cases for AI to improve operations.