Recruitment specialist Eursap has set out a set of practical changes it says job seekers need to make as automated screening plays a larger role in hiring decisions heading into 2026.
The company said employers and screening systems now make faster judgements about relevance. It pointed to closer matching between CV wording and job descriptions, more prominent skills sections, and bullet points that show outcomes rather than duties.
Daniel Patel, Director at Eursap, said applicants should move away from high-volume applications with a single general CV.
"The first update job seekers need for 2026 is sharper role targeting. One resume for every application no longer works. Hiring systems and recruiters both look for alignment fast. Titles, skills, and achievements must mirror the language of the role. If the job description says 'financial forecasting' and the resume says 'budget planning,' the match weakens even if the work overlaps. Updating wording to reflect how roles are advertised now directly improves screening outcomes.", said Daniel Patel, Director, Eursap.
Targeting and outcomes
Eursap framed the change as a shift in how relevance gets measured at the earliest stage. Patel argued that role alignment now depends on whether a CV uses the same terminology as the advert. He said candidates can lose visibility even when their experience fits the role, if they describe it in a different way.
Patel also pointed to a stronger emphasis on measurable impact. He said employers now expect a candidate to show what changed as a result of their work, rather than a list of responsibilities.
"The second update is outcome-led bullet points. Responsibilities alone no longer hold weight. Employers want proof of impact. Strong resumes show what changed because of your work. Numbers help, but clarity matters more. For example, 'managed monthly reporting' says little. 'Reduced reporting errors and shortened close timelines' shows value. In 2026, results signal readiness far more than task lists.", said Patel.
Skills near top
Eursap also highlighted the position of the skills section as a factor in screening. It said both automated systems and human reviewers tend to scan the top of a document first, which makes early placement more important than before.
"The third update involves skill placement. Skills should sit near the top, not buried at the end. Both AI tools and recruiters scan early sections first. A concise skills summary using current terminology helps systems classify candidates correctly and helps humans understand fit without digging.", said Patel.
AI-optimised CVs
Patel described an "AI-optimised" CV as one that uses standard headings and direct wording. He said screening tools score relevance through phrase matching and classification, which puts more weight on conventional structure.
"An AI-optimised resume in 2026 reads clean, literal, and structured. Systems score relevance by matching exact phrases from job descriptions. This means using standard section headings like 'Skills,' 'Experience,' and 'Education.' Creative labels confuse screening tools and reduce visibility. Clear hierarchy helps both machines and people.", said Patel.
He added that candidates should treat language as a practical signalling device rather than a narrative style.
"Language choice matters more than people expect. Use direct phrasing rather than storytelling. 'Led a cross-functional team' performs better than poetic descriptions of leadership. AI tools look for known role language, tools, and competencies. Matching those terms improves ranking before a human ever opens the file.", said Patel.
Structure and formatting
Beyond wording, Eursap said layout and formatting still shape what automated tools can read. Patel said some designs continue to create issues when systems parse content. He recommended a simple structure that keeps information scannable.
"Structure also matters. Bullet points should follow a simple pattern. Action first. Outcome second. Context last. This keeps information scannable and reduces misinterpretation. Dense paragraphs slow both systems and reviewers.", said Patel.
He said single-column formats remain the safest option for screening tools.
"Formatting still matters when it affects readability. Clean layouts with clear section breaks remain essential. Single-column formats perform best across screening tools. Multi-column designs still cause parsing errors. Visual design should support clarity, not decoration.", said Patel.
Patel also pointed to practical considerations such as font, document length, and file type. He said candidates should prioritise consistency and readability over visual distinctiveness.
"Font choice matters less than consistency. Use common fonts like Arial, Calibri, or Times New Roman. Fancy fonts distract reviewers and sometimes break systems. Font size should stay readable. Nothing below ten points.", said Patel.
He said CV length has become more dependent on career stage and relevance than on fixed rules.
"Length rules have shifted. One page no longer fits every career stage. Early professionals benefit from one page. Experienced candidates often need two. What matters is relevance. Every line should earn its place.", said Patel.
On file formats, Patel said candidates should avoid image-based documents that automated systems cannot read.
"File type still matters. PDFs remain safest for formatting, but only when text stays selectable. Image-based resumes fail screening. Word files work well when formatting stays simple.", said Patel.
Using AI tools
Eursap also addressed the increasing use of generative AI tools by candidates. Patel said such tools can speed up drafting and improve clarity, but he warned against generic wording that lacks detail.
"AI tools help with structure and clarity when used as a drafting assistant. They work well for turning rough notes into clean bullet points or tightening language. They save time during the early stages.", said Patel.
He said hiring managers can react negatively when a CV appears overly polished but vague.
"The red flag appears when resumes sound generic. Hiring managers spot AI phrasing quickly. Overly polished but vague language raises trust issues. Phrases without detail signal low ownership.", said Patel.
Patel said candidates still need to supply specific achievements, tools used, and problems solved. He said that personal detail remained central to credibility in hiring decisions.
"The part candidates must always customise involves achievements and skills. AI tools lack context. Only the candidate knows which results mattered, which tools they used daily, and which problems they solved. Personal detail builds credibility. AI supports writing. It does not replace judgment.", said Patel.