By Emily Troutman, MPP and Kathryn Troutman
Resume Place, Inc., Sept. 29, 2026, Baltimore, MD.
OPM IS ANNOUNCING USING AI FOR FEDERAL HIRING
AND RESUME REVIEWS
AI IS HERE FOR FEDERAL RESUME WRITING AND APPLYING FOR FEDERAL JOBS
This OPM Memo came out on August 27, 2026 and told us that the Federal Human Resources Staffing Specialists will be using AI for EVERYTHING relating to Federal Hiring, including RESUME REVIEWS FOR QUALIFICATIONS.
This means that YOU need to use AI to make SURE that your resume matches the qualifications in the job announcement! OR… you will not come up in any searches!
The Day Is Here for you to use AI for several methods to ensure that your resume matches a target job announcement!
Resume Place, Inc. consultants and writers are expert in keywords, accomplishments, targeting federal resumes. We have been doing this more than 30 years. And since we are experts in the HUMAN matching… we will be experts with the AI matching of your resume to the job announcement.
HERE ARE A FEW PARAGRAPHS FROM THE MEMO THAT ARE IMPORTANT FOR FEDERAL JOBSEEKERS — If you are breaking into government or if you are seeking a promotion:
To align policy and Federal hiring goals, this memorandum provides guidance on how agencies may approach hiring AI use cases, and advises agencies to adopt AI across the hiring lifecycle under the conditions below:
1. Content development for job opportunity announcements: this includes drafting the package of artifacts developed for a new job opportunity, including position descriptions, evaluation statements, announcement text, job analyses, qualification requirements, crediting plans, and interview questions, when the process of drafting content itself does not affect an individual’s access to employment. Before operational use, the material must be reviewed, validated, and adopted under applicable personnel requirements (classification under 5 U.S.C. Ch. 51; job analysis and validation under 5 CFR 300.103; subject matter expert (SME) involvement), obligations that apply independently of M-25-21.
2. Decision-support for applicant-level evaluations: this includes résumé screening, minimum qualifications and eligibility review, and candidate summarization when the AI output is not a principal basis for a decision or action. For example, when the AI locates, extracts, and summarizes the applicant’s documentation and how it aligns with agency-adopted eligibility and qualification criteria, with a reference back to the underlying documentation, and the deciding official independently reviews the underlying record and makes the determination on that basis, the AI output generally will not serve as a principal basis for the decision, because the official’s independent review of the record – rather than the AI summary – supplies the decision’s justification.
3. Pre-offer quality control: This includes review of the staffing case file and selection before a final job offer, when the AI is limited to administrative completeness and quality-control support and is not a principal basis for approving, delaying, or rejecting the selection or final offer.
4. Aggregate hiring program evaluation: this includes analysis of completed hiring actions, applicant flow, time-to-hire, and assessment performance, where no individual employment decision turns on the AI output.
Agencies must still assess their specific workflow and deployment context to affirmatively reach a non-high-impact determination, and an appropriate agency official must document that determination to the CAIO.
A non-high-impact determination changes nothing else. AI-assisted steps remain subject to job analysis and validation requirements under 5 CFR 300.103. Agencies must verify, before deployment and periodically, that:
1. AI-assisted rating, ranking, and referral correctly apply veterans’ preference;
2. AI-enabled steps meet Rehabilitation Act accessibility and reasonable accommodation requirements;
3. Applicant data is processed only in agency-authorized tools with applicable Privacy Act and privacy impact assessment protections;
4. Each hiring action remains documented and auditable; and
5. A reconsideration avenue remains available for adverse eligibility determinations.
What is Next?
OPM will continue introducing new AI features across the USA Suite of tools, including USA Staffing, USAJOBS, USA Hire, USA Class, and USA Performance. However, agencies should not wait for those features to begin adopting AI consistent with this memorandum.
OPM will also address AI-assisted processes in delegated examining oversight, and assist agencies on request, including through the Artificial Intelligence Governance and Adoption
Appendix A – Table 1. Approaches to Assessing Common Uses of AI in Federal Hiring
Screen résumés and match against minimum qualifications; review documents to determine veterans’ preference; review documents to determine other eligibilities (e.g., reviewing Interagency Career Transition Assistance Plan (ICTAP) documentation, reviewing documentation for Schedule A for individuals with disabilities, reviewing military spouse documentation, selective service.
Draft job analyses, qualification requirements, crediting plans, and interview questions
Generate a proposed recommendation of applicants who do not meet minimum qualifications; assess candidates and generate match rationales to support referral and selection decisions
Rate, rank, or score candidates against the adopted crediting plan; AI-scored assessments that produce candidate scores or rank order – with or without review and certification by an appropriate human official (including AI as sole scoring instrument)
Review staffing case file and selection before issuance of a final job offer to identify missing documentation, inconsistencies, procedural errors, or potential compliance concerns
Evaluate completed hiring actions and recruitment outcomes; analyze applicant flow, time-to-hire, certificate and selection patterns, and assessment performance; produce quality-of-hire and other program-evaluation analytics; assess whether completed hiring actions were carried out consistent with merit system principles; and identify adverse impact or other anomalies in aggregate hiring data to support process improvement and human capital accountability.
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