Digital GI Bill Automation Speeds VA Benefits Delivery
VA officials said Digital GI Bill upgrades have improved claims speed, enabling the department to process benefits with fewer staff.
The Department of Veterans Affairs’ Digital GI Bill (DGIB) program is making significant progress towards achieving its goals on technology upgrades, program management and contracts, a VA official told Congress.
Testifying to the House Committee on Veterans Affairs Wednesday, Kenneth Smith, executive director for education service for the Veteran’s Benefits Administration (VBA), said the VA’s efforts to improve the DGIB platform “have enabled the department to deliver benefits faster, enhance customer service and strengthen compliance with oversight activities.”
The VA’s end goal for DGIB is an automated system capable of one-day processing for 90% of claims received. The department is well on the way to achieving this. As of January 15, 2026, Smith said automation improved processing times for Chapter 35 claims by 69%, while claims for Chapter 33, Chapter 35 and Chapter 30 had improved by 58%. This totals more than 1 million claims annually, he said.
By January 22, 2026, Smith said it took 5.6 days to complete an education claim. While similar to previous years, this was done with fewer staff and increased automation. Automated claims completed in November 2025 were 97% accurate, comparable to the 98% accuracy of human claims processors, he said.
Automation and Improved Efficiency
The VA made major advances in streamlining and automating systems and processes to increase efficiency and improve outcomes, Smith told Congress. The DGIB modernization initiative seeks to restructure claims processing for all education benefits programs and enhance customer service for beneficiaries. This will be achieved by a fully integrated solution providing direct, online, one-stop access to GI Bill benefits and information, he said.
Smith noted the program successfully met its performance milestones via an updated processing platform, providing end-to-end automation for millions of benefits claims. “The success of this initiative has addressed many high risks to veterans and survivors who depend on these benefits,” he said.
Delivering functionality and replacing legacy systems were key to exceeding initial program goals. Central to this was decommissioning the nearly 50-year-old Benefits Delivery Network in 2025, Smith said.
The VA implemented two modifications in 2025 to improve program management. It moved from a waterfall-driven process to an agile methodology, allowing the department to quickly reprioritize to address new requirements. Second, because the VA consistently processed more claims than originally forecasted, additional annual funding was needed for its claims processing contract.
“Our focus has always been on the veteran: delivering benefits easier and faster to the veteran through simplified application interfaces and increased automation,” Smith said.
Overcoming Program Challenges
Responding to committee member’s questions about increased program costs and timelines, Smith acknowledged that the DGIB faced difficulties in the past. He noted that the original 2020 to 2021 contract underestimated the project’s complexity.
Challenges included transitioning from legacy systems running on COBOL, accommodating unplanned functionality changes required by new legislation and court mandates, and delays related to integration requirements with external systems that did not deliver on schedule.
“The reasons for these delays were prioritization and lack of an integrated approach to governance,” Smith said. He added that these issues were solved through close communication with external systems and a strengthened VA-level enterprise governance structure.
From 2021 through 2025, the VA processed 37% more claims at significant savings, when compared to the cost of hiring new staff, Smith said. As of December 2025, the VA automated and now delivers 65% of all claims without any human interaction, reducing costs and improving service delivery, he explained.
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