2_use_case_name: Integrate Google Doc AI for Digitalization
3_agency: Department of the Treasury
3_abr: TREAS
4_bureau: Internal Revenue Service
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: This Digital Enablement Platform (DEP) implementation has the goal to increase access to high quality data extraction, reduce reliance on paper and manually intensive processes utilizing artificial intelligence. Therefore, eliminating the need for transcription and manual data corrections by the Business.
DEP Artificial Intelligence (AI) will include updates to the existing business unit processes to leverage the UiPath Robotic Process Automation (RPA) platform. The UiPath RPA platform will also integrate with Google Document AI to implement a new extraction engine that will work in conjunction with and in support of the DEP.
The UiPath Automation Suite software for RPA platform in the Integrated Enterprise Portal (IEP) Amazon Web Services (AWS) provides support for multiple optical character recognition (OCRs), included the native UiPath OCR engine for intelligent document processing. Eliminating the need for transcription and manual data corrections by the Business.
Humans in the loop will validate AI OCR classification and extraction within the UiPath Action Center. Any extraction confidence levels that fail both UiPath and Google DocAI confidence level requirements necessitate human verification as well as 10 percent of all documents that are processed through the DEP AI system.
The benefit of the DEP AI system revolves around the of transition to being a modern, digitally capable, customer-centric agency. It will ensure taxpayers file accurate returns as well as allowing for the IRS to identify inconsistencies and streaming correspondence. 
The DEP AI aims to enhance efficiency by transitioning to end-to-end digital processes, eliminating paper backlogs, and improving accuracy in translating return data. These digital tools will be accessible to individuals with disabilities and offered in taxpayers’ preferred languages. Additionally, this commitment to digitalization reduces the environmental impact by minimizing paper usage and storage. Overall, the decision benefits taxpayers, improves operations, and contributes to environmental conservation efforts.
IRS business units tied to paper-driven processes as well as U.S. taxpayers.
12_outputs: The output is a metadata file that contains the data that has been extracted from the images we have scanned.
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 11/20/2023
19_date_acq_dev_began: 11/20/2023
20_date_implemented: 6/30/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: TIRNO-17-D-00004 WR2730
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: We have used CP2000 letter responses, Form 709 tax data, Form 94X tax data, SCOIC (offer in compromise) data.
34_data_docs: Documentation is widely available: Documentation is not only complete, but is widely accessible within the agency, and has an owner and a regular update cadence.
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: Digital Enablement Platform
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Use of existing data platforms: This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.
50_internal_review: Documentation has been developed: Complete documentation detailing model performance across a range of benchmarks, architecture, relevant features and information regarding the appropriate use of the model for predictive tasks has been created.