# GS Federal AI Procurement Safeguards Index

**Research draft — numerical findings not cleared for publication**  
**Study period:** January 1, 2024–August 28, 2026

## Executive summary

GS Consulting analyzed a fixed candidate frame of 1,532 public federal AI solicitation notices
and their available public packages. Acquisition, extraction, OCR, provenance, and descriptive
analysis are complete. The central prevalence estimates and headlines are intentionally withheld
until two independent reviewers complete both the AI-eligibility and safeguard-validation samples.

The report will answer:

- How often public AI solicitation packages include each of ten acquisition safeguards.
- Which safeguards are most and least observable in public requirements.
- How observed language differs by agency, opportunity type, and set-aside status.
- Whether observed language differs before versus after OMB M-25-22.

## What was analyzed

- 1,532 candidate notices in the fixed study window
- 1,509 successful archived-resource lookups and 23 unavailable notice resources
- 4,699 public attachments with zero unresolved download failures
- 5,143 text-bearing files, including 353 OCR-processed PDFs
- 47,870 deterministic document/category evidence rows within the exact study frame
- 1,000 weighted safeguard-validation judgments across ten categories

These are acquisition and workflow facts, not substantive safeguard findings.

## Findings

### 1. Overall safeguards index

`[PENDING: validated category estimates, 95% confidence intervals, and composite-index rule]`

### 2. Vendor lock-in, portability, and interoperability

`[PENDING: independently verified portability, IP-rights, and interoperability estimates]`

### 3. Testing, performance, and monitoring

`[PENDING: independently verified testing, metrics, and monitoring estimates]`

### 4. Agency and procurement-type differences

`[PENDING: validated comparison tables with denominator and missingness checks]`

### 5. Before and after M-25-22

`[PENDING: descriptive pre/post comparison; no causal language]`

## Interpretation

Every final claim will be limited to language found in public solicitation packages. “Not found”
will not be restated as proof that an agency lacks the safeguard internally. Agency rankings will
include minimum sample-size rules and public-text missingness. Award data will appear only for
human-accepted exact-identifier links.

## Methods and limitations

See [methodology.md](methodology.md) and [data-dictionary.md](data-dictionary.md). The public report
will include classifier precision/recall, safeguard-rule precision/recall, reviewer agreement,
Cohen’s kappa, confidence intervals, exclusions, and missing-data rates.
