Candidate Experience Metrics in 2026: What to Track When Software Screens Most of Your Applicants
Here’s an uncomfortable detail from the 2026 Hiring Benchmarks Report from Starred. Nearly 90% of candidate survey invitations in 2025 went to rejected candidates, and about 70% of those rejections happened at the application stage. For most applicants, the whole candidate experience is a form, a wait, and an email. Often with no human anywhere […]
AI Recruiting Software for Candidate Screening in 2026: What’s Actually New
Every January for the last four years, someone has published a list of “AI recruiting trends to watch,” and every year the list looks suspiciously similar to the one before it: faster screening, less bias, better candidate experience. Readers have learned to skim past it. 2026 is actually different, and not for a flattering reason. […]
AI Candidate Screening Software for Staffing Agencies: How to Compare Tools
Every guide to “comparing AI screening software” is written for one hiring manager, one job description, one set of requirements. A staffing agency doesn’t work that way. On any given afternoon, your recruiters are screening for a client that wants five years of SAP experience, a client that just needs someone who’ll show up for […]
Ready to Use Quality of Hire Questionnaire: 20 Questions to Ask
Most companies measure hiring the way they measure a delivery service: how fast, how cheap, how many boxes shipped. Time-to-fill and cost-per-hire answer those questions well. Neither one tells you if the person you hired was actually good at the job. That’s what a quality of hire questionnaire is for. It’s a set of structured […]
Candidate Screening Software: How to Choose the Right One
Most candidate screening software gets sold the same way: a big accuracy number on a slide, a promise to cut screening time in half, and a tool that barely talks to the ATS your team already uses. Weeks later, nobody can explain why it ranked one candidate over another, and the “accuracy” number turns out […]
Savos vs. Greenhouse: Two Different Bets on What AI Can Do for Hiring
If you are evaluating recruiting technology right now, Greenhouse is likely on your shortlist. It is one of the most widely used applicant tracking systems on the market, and it has been adding AI features at a significant pace over the last year. Several of those features are genuinely worth understanding. Savos is a different […]
Internal Hiring vs External Hiring: Cost, Culture, and Speed
Every time a role opens up, HR teams face the same fork in the road: do you look inside the building, or outside of it? It sounds like a simple call. In practice, it’s one of the most consequential decisions a talent team makes — and getting it wrong costs more than most leaders realize. […]
Savos Featured in AI Verify Foundation’s Global AI Assurance Case Studies at ATxSummit 2026
At ATxSummit 2026 last week, Singapore’s Minister for Digital Development and Information, Josephine Teo, spoke about the strategic importance of the AI Verify Foundation’s latest assurance case studies as part of Singapore’s broader push toward responsible and large-scale AI adoption. We are proud that Savos by impress.ai was featured among them. This is not our […]
The 2026 Playbook for Transitioning to Skills-Based Organizations
Traditional hiring is facing a structural breaking point. For decades, enterprises and government agencies have filtered talent through the blunt instruments of university degrees and linear job titles. Yet, paradoxically, global skills gaps continue to widen. The talent that organizations claim they cannot find isn’t missing, it is simply trapped behind legacy credential filters. For […]
Predictive HR Analytics: How to Spot Flight Risks and Improve Retention
Every HR leader knows the feeling of a surprise resignation. One day your top performer is hitting their KPIs, and the next, they are handing in their notice. The financial blow is immediate. Replacing a specialized employee usually costs between 50% and 200% of their annual salary. But the hidden costs are often worse: Morale […]