What AI-ready should mean on a truthful job application

The surveys explain why a label needs detail

In a September 23 release, Express Employment Professionals reported that 93% of surveyed US job seekers believed they had the AI skills employers wanted, while 41% of surveyed US hiring decision-makers expected advanced or expert capabilities. These are responses from different populations to different questions. They do not establish that 93% demonstrated proficiency.^[1]

The Harris Poll surveyed 1,000 US job seekers from May 19 to June 8 and 1,006 US hiring decision-makers from May 13 to June 1, 2026, on behalf of Express. The release date is September 23; the attitudes were measured several months earlier. The results do not describe every employer or the Canadian hiring market.^[1]

iCIMS's September 10 release reports a separate commissioned survey of 1,000 US job seekers. It found that 47% had worked on their AI skills in the past six months and 61% described their proficiency as limited to general-purpose tools. The 61% figure describes reported proficiency, not how frequently those people used a tool.^[2]

Write one claim that a recruiter can examine

Start with a task relevant to the posting, then name the tool and your own contribution. Using a chatbot for a draft, integrating a model into software and developing a model are different activities. iCIMS separates general-purpose tool familiarity from specialized skills; describe the activity you actually performed rather than treating them as interchangeable.^[2]

Include your checking process. Express found that 45% of surveyed hiring decision-makers looked for awareness of privacy and security concerns, and 45% looked for clear communication of AI findings. Explain how you checked facts, protected confidential information or handled an incorrect output when those actions were part of your work.^[1]

A fill-in template for your own evidence is: Used [tool] to support [specific task]; checked [output] against [reference or test]; corrected [limitation]; achieved [documented result]. This is an editorial template, not a survey quotation or a real candidate's testimony. Remove any element that you cannot substantiate.^[1][2]

Separate a measured result from an impression

If you claim a numerical improvement, retain the baseline, measurement period, sample and method. If you did not measure it, state the observable outcome without inventing a percentage. Neither survey validates your project results; the supporting evidence must come from your own work.^[1][2]

Prepare to explain a failure as well as a success: what the tool produced, how you detected the problem and what you changed. A course or certificate can document study; a work example describes application. Match the depth of your claim to the role and avoid upgrading ordinary tool familiarity into expertise.^[1][2]