On November 6, the U.S. Bureau of Labor Statistics reported that employers added 165,000 jobs in October, higher than the average monthly gain of 48,000 over the prior 12 months, and the unemployment rate changed little at 4.1 percent. Professional and business services added 70,000 jobs, health care added 42,000, transportation and warehousing added 25,000, and manufacturing added 19,000. Revisions added 84,000 jobs to August and September combined. Hiring is moving again after months of slow growth, and the requisitions opening now will meet an application pile that has changed character.
For CIOs, CISOs and VP IT Operations leaders and the talent leaders who hire for them, the question is whether the first step of the hiring workflow can still tell a real candidate from a polished file. The evidence says the check between application and first conversation is now the step that decides the hire.
What did the October jobs report actually show?
The October report is a re-acceleration, not a boom. Total nonfarm payroll employment rose by 165,000, and the three-month average gain reached 137,000. Within professional and business services, professional, scientific, and technical services added 33,000 jobs and administrative and support and waste management and remediation services added 28,000. Manufacturing added 19,000 jobs, including 7,000 in computer and electronic product manufacturing. Average hourly earnings rose 14 cents, or 0.4 percent, to $38.00, and are up 3.1 percent over the past 12 months.
One caution: these are industry payroll changes, not hiring demand for specific roles, and the October figures are preliminary. Read them as the direction of demand, not as a count of open firmware or cyber roles.
What is in the application pile now?
Candidates are using the same technology employers are. A Gartner survey of 3,290 job candidates in the fourth quarter of 2024 found that 39 percent said they used AI during the application process. Of those, most used it to generate resume text (54 percent) or cover letter text (50 percent), and 29 percent used it for answers to questions on an assessment. A separate Gartner survey of 3,000 job candidates in the second quarter of 2025 found that 6 percent admitted to interview fraud. Gartner predicts that by 2028, one in four candidate profiles worldwide will be fake.
Trust is falling on both sides. Only 26 percent of candidates in a first quarter 2025 Gartner survey of 2,918 job candidates said they trust AI will fairly evaluate them, while 52 percent believe AI screens their application information, and only half trusted that the jobs they were applying for were legitimate. On the employer side, Criteria's 2026-2027 Hiring Benchmark Report, a survey of 1,027 U.S. hiring professionals in the summer of 2026, found that 41 percent struggle with candidates using AI to misrepresent themselves, 35 percent say their current process cannot reliably detect it, and 24 percent have lost confidence in resumes as a reliable signal. In technology, 60 percent say applicants use AI to misrepresent themselves.
Why does the check decide the hire now?
Put the two halves together. Hiring volume is rising again, and the application itself carries less reliable information than it did a year ago. Every additional unverified application adds work without adding signal, so sourcing more candidates before verifying them makes the bottleneck worse, not better. The constraint moved from finding people to proving which ones are real, and the workflow has to move with it. Criteria found that 55 percent of hiring professionals name finding high-quality candidates with the right skills as their biggest challenge.
Picture a hiring manager at an operating company who opens a requisition for a firmware engineer the week the October report lands, and the posting draws a full pile within days. Four in 10 hiring professionals now say applicants use AI to misrepresent themselves, and about a third say their process cannot reliably tell when it happens. The team can spend its week reading polished files, or it can spend it checking the few claims that matter: the identity of the person, the firmware work the candidate says they did, and a live technical conversation that shows whether they can explain it. Only one of those weeks ends with a hire the team trusts. The check is not an extra step. It is the step that makes the rest of the workflow worth running.
Candidates want the check too. Gartner found that 62 percent of candidates said they are more likely to apply to a position if the organization requires in-person interviews. Trust is now scarce: only 51 percent of candidates accepted a job offer in their most recent application process in the second quarter of 2025, down from 74 percent in the second quarter of 2023.
What should the workflow do first?
Verify identity and claimed skill before the human conversation, not after it. Gartner's guidance for employers is a three-step sequence: set clear expectations and communicate hiring standards, including the legal consequences if fraud is detected; use the assessment process to uncover fraud, with safeguards such as in-person interviews; and refine methods throughout evaluation, with system-level validation, tighter background checks, and identity verification.
Automation belongs on the check, not on the decision. Gartner's advice is to use AI agents when decisions are needed, automation for routine workflows, and assistants for simple retrieval, and to judge the result on cost, quality, speed and scale. That matches where the market is heading: 82 percent of HR leaders plan to use some form of agentic AI by May 2026, according to a May 2025 Gartner survey, and Gartner predicts that by 2030, 50 percent of current HR activities will be AI-automated or performed by AI agents. Gartner also predicts that 33 percent of enterprise software applications will include agentic AI by 2028, up from less than one percent in 2024. Human oversight stays in the workflow: most jurisdictions require ongoing human oversight of hiring decisions.
What should talent leaders measure instead?
Measure time to a verified shortlist, not time to the first application. An application count measures how many files arrived; a verified shortlist measures how many people passed a check. Track the share of the shortlist that is verified, the time from application to verified shortlist, and the offer acceptance rate.
The caution is real. Gartner predicts that over 40 percent of agentic AI projects will be canceled by the end of 2027, citing escalating costs, unclear business value and inadequate risk controls. SHRM's research gives the same shape: 87 percent of HR professionals report improved efficiency from AI and 75 percent report improved work quality, but about half see no improvement in decision-making. Efficiency is real. Better decisions are not automatic. The demand is there: Criteria found that 64 percent of hiring professionals expect to hire more next year.
What does this mean for technical hiring?
For CIOs, CISOs and VP IT Operations leaders hiring hardware, embedded, firmware, test, QA, cyber, network, SRE, field-service, ERP and data-center roles at operating companies in the United States and Canada, the check is a live technical conversation, not a keyword screen. A candidate who cannot explain the firmware work they claim has failed the check before a hiring manager spends an hour. SHRM found that AI is 5.7 times more likely to shift job responsibilities and three times more likely to create new roles than to displace jobs, so the skills being verified are the ones that keep changing.
The October report says hiring is moving again. The application data says the pile cannot be taken at face value. Put the check first, keep the decision with people, and measure the verified shortlist. UPPER works with talent leaders who hire this way, through sourcing channels their own recruiters operate, for the technical roles their businesses run on.