Every recruiting team has an onboarding process for new hires: a job description, clear responsibilities, a point of contact, a probation period with feedback conversations. But the moment that same team introduces an AI tool for sourcing, screening, or scheduling, all of that instinct disappears. The agent gets switched on, given access to the ATS – and just runs. No job profile, no clear boundaries, no first feedback conversation. That's exactly where an analysis by Joseph

Works council elections, a stricter Federal Labor Court line on Section 87 BetrVG, transparency duties since August 2026: why the works council is becoming the first hurdle for AI recruiting software, not the last.

There’s a moment that many Talent Acquisition teams are increasingly familiar with: you’ve equipped your screening process with AI, application volumes are higher than ever, shortlists arrive faster – and yet the quality of hiring decisions doesn’t feel any better. Sometimes it actually feels worse. That’s not a coincidence. It’s the logical consequence of a system that has undermined itself. The Dilemma: When AI Goes Up Against AI Think of the selection process as a communic

The Digital Omnibus pushes the EU AI Act's high-risk obligations for recruiting AI to December 2027. What has applied since August 2026 anyway – and why waiting is the most expensive option.

Recruiting, learning and development, and workforce planning are merging into one role: what the AI-powered Talent Portfolio Manager means for TA teams in the DACH region – and what it isn't.

Recruiting automation is no longer a vision of the future. Adoption has grown from 26 to 43 percent of all HR functions in a single year — and Gartner predicts that by 2027, around 81 percent of all recruiting functions will be using AI-powered tools. The pressure is real: organizations that don't automate lose time, money, and competitive advantage. And yet the critical question isn't whether to automate. It's where. Many teams are automating the wrong things. They save time

Twenty years of the AGG have changed the language of recruiting. The next round is decided inside the model: why Section 22 AGG makes algorithmic pre-selection riskier than human selection – and what the 2026 reform changes.

Imagine you've been booking your favorite restaurant for months at the introductory price — fresh Wagyu steak for the price of a burger. You get used to it. You plan birthdays there. And then, one day, the new menu arrives. Welcome to reality. That's roughly what's happening right now with AI tools in recruiting. The good news: AI-powered recruiting software has never been more capable or more affordable than it is today. Sourcing agents that scan qualified profiles around th

How AI matching engines turn internal talent marketplaces from a digital bulletin board into a genuine hiring engine – the tech, the numbers, the limits.

An update on the OpenAI Jobs Platform: what's actually happened since the Certifications launch, the Indeed integration in ChatGPT, and Fidji Simo's departure – and what it means for recruiting.

In his column for Personalwirtschaft, my highly esteemed colleague Marcus Merheim writes about a recruiter who received 340 applications for a single job posting — 280 of them obviously written with AI. No typos, no odd phrasing, no rough edges – just consistently competent-sounding text that could just as easily have gone out to a hundred other companies. Roughly 80 percent AI share in a single applicant pool. Not an isolated case, but a preview of what is becoming the new n

AI in recruiting is currently an easy sell. Nearly every HR tech demo promises faster processes, smarter decisions, and more productive teams. The presentations look impressive. The investment requests often do too. Usually, things only become difficult afterward. At budget review, someone asks, “And what exactly did this deliver for us?” Talent Acquisition organizations often run into trouble—not because AI solutions are ineffective, but because their impact is mismeasured o

Few professions are currently being scrutinized as intensely for their future relevance as recruiting. With every new AI application, every autonomous agent, and every new wave of automation, the same question resurfaces: Will recruiters even be needed in the future? The answers vary dramatically. Some predict the end of the profession altogether. After all, artificial intelligence can already analyze résumés, identify candidates, write job advertisements, prepare interviews,

Job interviews are essential for personnel selection. Leaders trust them. They provide direct, personal interaction. You observe, question, and believe you have a strong impression. The impression rarely matches daily work. Interviews capture an exceptional moment. A recent Journal of Business and Psychology article highlights this. Bayón, Kleinmann, Ryan, and Heimann studied whether asking about maximum versus typical performance matters. Is the interview capturing the best

Recruiting is currently undergoing profound changes. Artificial Intelligence (AI) is no longer just an experiment in innovation labs. In many organisations, it has become part of the operational recruiting process: résumés are automatically screened, interview transcripts analysed, and candidate communication partially automated. However, the adoption of AI is only part of the story. The main argument of this text is that, in recruiting, the greatest challenge today is not th

Recruiting is often seen as an objective process. Résumés are reviewed, interviews conducted, and decisions documented. Many organizations, therefore, assume that bias—systematic distortion in decision-making—is primarily an individual issue: an unconscious impression in an interview or a gut feeling during selection. The reality is less comfortable. Bias does not arise solely in individuals' minds. It is often embedded in the system itself. Job profiles evolve over time, sou

AI-created applications are now the standard. The key question is no longer whether to approve, but what follows next. In many companies across the DACH region, no hiring process is completed without a personal meeting before signing a contract. And that is precisely why AI-driven candidate fraud often remains invisible for a long time. Not because it works in face-to-face interviews—but because it ends there. The real issue emerges one step earlier. In digital pre-selection

Artificial Intelligence (AI) has firmly arrived in recruiting. Résumés are pre-screened, active-sourcing messages are auto-generated, and interviews are transcribed and analyzed. Efficiency gains are real. At the same time, the competency focus is shifting—away from purely operational process management toward a more fundamental question: Who takes responsibility for the human dimension? A widely discussed idea, highlighted in Fast Company , captures it well: in an AI-shaped

Recruiting rarely suffers from a lack of activity. What it often lacks is clarity. Jobs are posted, sourcing lists are built, and interviews are conducted. Still, the underlying feeling remains: we are reacting more than we are steering. This is exactly where Talent Mapping comes in. Not as a buzzword, but as a structural response to a fragmented labor market – and as a discipline that becomes truly scalable through artificial intelligence (AI). What Talent Mapping Actually I

The labor market feels paradoxical. Companies invest in AI, automation, and efficiency programs. Meanwhile, hiring freezes, layoffs, and closed entry points increase—often in roles recently touted as “jobs of the future.” For many employees and candidates, this signals uncertainty rather than momentum. This simultaneity is not an anomaly or a temporary fluctuation. It marks a structural transition. Organizations seek productivity gains before adapting role models, qualificati