AI for People, with Purpose
Artificial intelligence is changing how government works, but the most successful projects begin with mission needs and human judgment. Abt helps public sector organizations use AI responsibly because we combine deep subject matter expertise with technical capability. This means our clients get tools that solve real problems rather than tech for its own sake.
Across health, justice, environment, and economic policy, agencies are looking for ways to handle unstructured information, make sense of growing datasets, and deliver services more efficiently. Abt works alongside program staff to automate routine tasks, improve decision making, and strengthen program integrity. Our work spans the entire AI landscape including natural language processing, predictive analytics, and generative AI. At the same time, we focus on practical use cases that lighten workloads, reduce errors, and free public servants to focus on mission outcomes.
We have helped agencies analyze millions of public comments, detect patterns in healthcare data, modernize critical data systems, and build AI ready workforces around the world. Because our approach blends secure technology with real world experience, our solutions are useful on day one and evolve as policies, programs, and datasets change.
Explore the examples below to see how Abt is helping government clients adopt AI with purpose and deliver measurable impact for the people they serve.
Methods
Whether piloting new ideas or delivering impact on the ground, Abt is helping government clients harness AI. Here’s how:
- Fraud, waste, and abuse detection. Abt builds tools that embed fraud detection methods directly into agency workflows using flexible low code frameworks. This gives investigators real time insights that evolve as programs and policies change.
- Literature review. Abt supports evidence based policymaking by pairing AI with subject matter expertise to accelerate literature scans, extract relevant claims, and organize findings for review.
- Quality control. Abt worked on a demonstration for the Army Corps of Engineers to show how it could use AI and machine learning for cost estimates to incorporate more data than traditional methods and thus produce more accurate forecasts.
- Policymaking Simulations: Abt worked with Centers for Medicare & Medicaid Services (CMS) to develop a simulation of Nursing Home staffing levels to understand impacts to patient care and costs to the nursing home industry of a proposed rule on Minimum Nursing Home Staffing Levels.
- Data Ecosystem: Abt worked with the Bureau of Justice Statistics to pilot a generative AI tool that takes the description of each felony in a state’s criminal code and matches it to a standardized set of crime values.
- Prediction. Health agencies could use AI to predict extreme weather events and provide warning to populations with special health needs. With the predictions in hand, social services agencies could connect those affected to the care they need and send money to residents’ checking accounts before a natural disaster hits.
Relevant Experience
Support to the Per- and Polyfluoroalkyl Substances (PFAS) Work
Client: Centers for Disease Control and Prevention
Per- and polyfluoroalkyl substances (PFAS) are man-made contaminants found in drinking water that lead to a variety of health impacts, from low birthweight to impaired immune systems to increased cancer risk. Understanding the amount of PFAS in a given person’s blood is important for that person and for governments and agencies trying to set clear guidance on risk levels in communities. But PFAS blood monitoring is not readily accessible. Our team used AI predictive analytics to develop a model both for researchers and the general public to predict blood levels based on drinking water exposure. They focused on two parameters and incorporated hundreds of datapoints from multiple studies to refine the estimates of those two parameters. The model improves our ability to estimate PFAS blood levels. Learn more.
Intermodal Transportation Recommender System
Client: U.S. Army Corps of Engineers
Abt built a recommender system using vessel types, commodity properties, dock properties, and intermodal transportation availability to recommend alternative docks when the intended dock is inaccessible.
Workforce Readiness
Client: Substance Abuse and Mental Health Services Administration (SAMHSA)
The best AI solutions fail without a workforce prepared to implement them. Abt worked with SAMHSA to ensure community-based organizations (CBOs), often reliant on outdated technology, could adopt AI responsibly and effectively. We developed and delivered a multi-day training for 30 CBOs, covering prompt engineering, AI ethics, and practical uses in behavioral health settings. We also established a peer learning network to foster continuous collaboration. By equipping frontline case workers and outreach specialists with real-world AI skills, Abt is helping government partners ensure that innovation enhances, not disrupts, service delivery. Learn more.
Accountable Health Communities Evaluation
Client: Centers for Medicare and Medicaid Services
Abt used NLP to analyze 4,711 open-ended survey responses for the Accountable Health Communities Evaluation Beneficiary Survey. The goal was to identify the 10 most discussed topics. The analysis identified that respondents discussed food-related topics most commonly. The NLP model also enabled the research team to efficiently identify the most relevant responses for a manual analysis on barriers to accessing community services. Learn more.
Streamlining Medicaid Data
Client: Centers for Medicare and Medicaid Services
Abt supports CMS as they work to make sense of large volumes of Medicaid managed care data that arrive from states in formats that are difficult to analyze such as PDFs and spreadsheets. Because analysts were spending valuable time cleaning and validating submissions, Abt brought together policy and data engineering expertise to automate quality checks and validation steps using AI tools on a Databricks platform. This created a smoother data pipeline that ingests, integrates, and verifies state submissions. CMS now uses interactive dashboards that update in real time with quality controlled information. Analysts can identify emerging patterns and potential risks, while remaining in full control of decisions. The result is faster insight generation, stronger program integrity, and better support for the Medicaid population. Learn more.
Linking Public Health Data
Client: Centers for Disease Control and Prevention (CDC)
CDC needed faster ways to spot disease patterns after the triple demic of flu, RSV, and Covid in the fall of 2022. Abt helped by integrating large billing datasets that covered about fifty million Americans to identify comorbidities that increase risk. We then linked that information across all states to census data so analysts could see which populations might be most vulnerable based on age, income, and where they live including nursing homes and other congregate settings. Because the data was incomplete, Abt used a statistical approach called multilevel regression and poststratification to account for missing values and produce realistic population estimates. CDC gained real time visibility into symptoms and emerging outbreaks, which supported resource planning and outreach to communities that needed public health support most. Learn more.
Helping EPA Gain a Clearer View of Chemical Transfers
Client: Environmental Protection Agency (EPA)
Abt partnered with EPA to improve the quality and usability of off site chemical transfer data within the Toxics Release Inventory. By pairing deep subject matter expertise with advanced AI engineering, the team increased accurate standardization of records from about seventy percent to ninety seven percent and reduced a year of manual review to just weeks. The improved dataset now gives EPA a clearer view of where chemicals are going, strengthening risk analysis, transparency, and long term AI readiness across the agency.