HR-7972-119
Placed on the Union Calendar, Calendar No. 706.
Sponsored by David Schweikert (R-AZ)
What it does
This bill would require the IRS to establish a fellowship program by September 30, 2026, recruiting private-sector data scientists to work alongside IRS tax law specialists. Fellows would serve 2–4 year terms (with unlimited 1-year extensions) and be paid at least at the GS-15 federal pay grade. The bill would also create a joint task force to apply data analytics, artificial intelligence, and statistical modeling to audit case selection, offshore tax evasion detection, and overall tax administration improvements. The IRS Commissioner would submit annual reports to Congress on the program's costs, benefits, and return on investment.
Who benefits
Compliant taxpayers broadly, who may benefit if improved enforcement reduces the estimated $600+ billion annual "tax gap" (the difference between taxes owed and taxes collected). Private-sector data scientists seeking public service opportunities at competitive pay. IRS junior employees who would receive training in advanced analytics. The federal government, which could see increased tax revenue from improved audit targeting. Taxpayers who interact with the IRS and may benefit from operational service improvements.
Who is hurt
Taxpayers — particularly high-income individuals, large corporations, and those with complex offshore holdings — who may face more accurate and frequent audits as a result of improved IRS targeting capabilities. IRS employees whose existing audit selection methods may be displaced or scrutinized. Privacy advocates concerned about expanded government data collection and analytics on taxpayer information. Taxpayers who believe current IRS enforcement is already burdensome may see this as an expansion of that burden.
Supporters argue
Supporters argue that the IRS faces a significant technological gap relative to the private sector, and that the estimated $600+ billion annual tax gap — much of it attributable to complex, hard-to-detect evasion — requires sophisticated data science tools to address. They contend that recruiting private-sector experts on a fellowship basis is a cost-effective, targeted approach that avoids the rigidity of permanent hiring while building lasting institutional capacity through training and potential permanent conversion of fellows.
Opponents argue
Opponents argue that expanding IRS data analytics and AI-driven audit selection raises serious concerns about algorithmic bias, due process, and the potential for disproportionate scrutiny of certain taxpayer groups — concerns that have already emerged in IRS audit rate disparities documented by academic researchers. They contend that the program adds new spending and bureaucratic infrastructure without addressing underlying IRS resource and management problems, and that annual reporting requirements may be insufficient oversight for a program with broad discretion over audit targeting.
Constitutional context
No significant constitutional tension is present. Congress has broad authority under the Taxing and Spending Clause (Art. I, §8, cl. 1) to fund and structure federal tax administration. This bill is an organizational and workforce measure within an existing agency and does not raise issues related to the tax-vs-penalty distinction, direct tax apportionment, or the unresolved realization question from Moore v. United States (2024).
Checks and balances
The Executive Branch (IRS/Treasury) gains new hiring authority and discretion over program design and audit targeting; Congress retains oversight through mandatory annual reports on costs, benefits, and return on investment submitted by the IRS Commissioner.
Historical precedent
The IRS has previously used limited-term hiring and interagency detail programs to bring in specialized talent, but no directly analogous statutory fellowship program of this structure has been enacted at the IRS.