No more excuses for data privacy violations!

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We’re excited to introduce JANZZanonymizer!—the game changer for handling large volumes of personal data, especially CVs and resumes.

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IT: From Red-Carpet Treatment to Unemployed Status

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Between 2020 and 2022, IT professionals were in high demand as lockdowns forced companies to digitize overnight: job offers for software developers, IT architects and data analysts surged. Since mid-2022, however, the tide has turned.

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What the Unemployment Rate isn’t Telling You

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If unemployment is low, why are hospitals still short of caregivers and restaurants desperate for qualified staff? Read Chapter 2 of our white paper to understand why today’s historically low unemployment rates can backfire—deepening, not easing, the shortage of skilled workers.

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Neither Cash nor Campaigns: The Unstoppable Decline in Birth Rates

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For Hungary’s Prime Minister Viktor Orbán, nothing is more important than babies. But they must be “home-made.” In his words: “Migration for us is surrender.” Orbán, himself a father of five, has set a bold target: raising Hungary’s fertility rate to 2.1 by 2030, the level needed to maintain the population size.

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Could Qualified Professionals From Indonesia Help to Solve the Acute Skills Shortage in Switzerland as Well?

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Switzerland, like much of Europe, faces a growing labor crisis. Retail, logistics, hospitality and healthcare are in critically short supply. With fertility rates falling and young people choosing academic careers over vocational training, the talent gap is widening.

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Bridging the Skills Gap in an AI-Driven World

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It’s not jobs we’re running out of; it’s alignment. Too often, the skills people bring to the market don’t match what employers demand and vice versa. But the debate about “AI replacing humans” is misleading.

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Microsoft Study Reveals Who’s Really Using AI at Work—And Who Isn’t

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A new Microsoft research paper has just dropped, and it’s one of the more ambitious attempts to map out how generative AI is actually being used in the workplace.

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JANZZ Named Sample Vendor in Gartner’s AI in Human Resources Hype Cycle

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JANZZ Named Sample Vendor in Gartner's AI in Human Resources Hype Cycle

JANZZ Named Sample Vendor in Gartner’s AI in Human Resources Hype Cycle

 

Leading research firm recognizes JANZZ’s AI-driven recruitment solutions for the 5th consecutive year

 

June 17, 2025—JANZZ, a global leader in AI-powered human resources technology, has been listed as a trusted Sample Vendor in Gartner’s prestigious Hype Cycle for AI in Human Resources, 2025. This recognition underscores the company’s continued innovation and market leadership in artificial intelligence applications for talent acquisition and workforce development.

The inclusion in Gartner’s Hype Cycle marks a tradition: JANZZ has been recognized by the world’s leading research and advisory company in 6 different publications. For the first time in 2020, JANZZ was chosen as a Sample Vendor for Skills Ontologies (listen to Podcast) in Gartner’s Hype Cycle for Human Capital Management Technology, highlighting the company’s semantic approach to HR technology solutions.

 

“Being repeatedly selected among the most trusted vendors by Gartner validates our ongoing investments in product development and innovation,” said JANZZ spokesperson Doris Hofer. “This recognition from the sector’s most respected authority confirms that our AI-driven solutions are meeting the evolving needs of modern governments and businesses.”

Industry Context and Market Trends

Gartner’s research indicates that by 2025, 60% of enterprises will adopt a responsible AI framework for their recruitment procedures. However, Jeff Freyermuth, Director Analyst in the Gartner HR practice, cautioned that “most of the innovations haven’t lived up to their overinflated hype,” emphasizing the importance of carefully evaluated technology adoption.

The Gartner Hype Cycle serves as a crucial decision-making tool for organizations planning to upgrade their recruitment systems. It provides an objective assessment of emerging technologies, helping companies understand the real risks and opportunities of innovation while avoiding premature adoption or delayed implementation. According to Gartner, innovations typically require 3–5 years to move through the full Hype Cycle, with some technologies falling off entirely during this maturation process.

JANZZ’s Competitive Advantage

What distinguishes JANZZ in the competitive landscape is its comprehensive multilingual skills ontology JANZZon!—the most extensive in the world. While many providers claim to offer ontologies suitable for AI applications in talent acquisition, JANZZ’s solution goes beyond simple skill libraries to establish contextual understanding when matching skills to job requirements.

This semantic capability addresses a critical gap in the market, where inadequate matching technologies can lead to missed top talent and suboptimal hiring decisions (watch on YouTube). The company’s approach ensures accurate skill-to-job matches across multiple languages and cultural contexts.

Global Reach and Compliance

JANZZ’s technology platform demonstrates its commitment to global scalability and data security. The company’s ISO 27001-certified solutions are fully compliant with GDPR and CCPA regulations, while supporting over 60 languages. This extensive language support reflects JANZZ’s understanding of regional labor market characteristics and cultural nuances in different geographical areas.

JANZZ.technology utilizes advanced semantic technologies to parse, classify, and match various professional attributes, including occupations, job titles, qualifications, hard and soft skills, experiences, education, and training credentials. This comprehensive approach enables rapid matching of candidates with open positions across multiple languages and platforms.

About JANZZ

JANZZ specializes in AI-driven recruitment solutions that address the unique characteristics of labor markets across different regions. The company’s secure, cloud-based solutions and white-label products serve businesses and governments worldwide, helping organizations identify top talent efficiently while supporting economic development and workforce optimization initiatives.

For more information about JANZZ’s AI-powered human resources solutions, contact JANZZ and book a call to explore your hiring needs.

Are you kidding me? JANZZsme!, the only real alternative to the daily nightmare of AI-powered job and skills matching

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In this new episode of our Uncovers Series, we clarify what matching really means and the key factors that ensure a quality match in HR.

The challenge of matching individuals with jobs has persisted for decades, and it remains a colossal issue. Despite numerous attempts to find a solution, nearly all existing options fail miserably—not just underperforming, but outright ineffective. The results are often absurd or laughably inadequate, even on global platforms like LinkedIn, which boasts millions of users and vast amounts of data. How is it possible that a platform with such extensive user data struggles to connect people with suitable jobs? Why do other major platforms and HR systems continue to send us the same ridiculous recommendations without making any real progress?

The answer lies in the outdated methods these platforms and systems employ. They rely on antiquated techniques that have never truly worked. They use keywords and algorithms that cannot hope to capture the complexity of human personality or the nuanced requirements of a job. They lack contextual understanding, are utterly illiterate when it comes to semantics, and, unfortunately, have little to no grasp of the subject matter. To make matters worse, they often operate with illegal, highly biased training data and are typically oblivious to their astonishingly poor results. Surely, they would have changed their approach long ago if they were aware.

But there is an alternative: JANZZsme! This patented solution is already utilized worldwide in over 60 languages, assisting millions of people daily in finding the right jobs. JANZZsme! is built on a patented, unique methodology that genuinely honors the concept of matching.

If you’re tired of the daily nonsense and the ridiculous outcomes, take a few minutes to watch this video. We promise you’ll learn everything you’ve always wanted to know but were afraid to ask. JANZZsme! is the solution you’ve been searching for. It’s time to revolutionize the matching of people and jobs and usher in a new era in global job markets.

Feel free to reach out to us; we’d be delighted to showcase the capabilities of JANZZsme! in a live demo.

The Pitfalls of Incorrect Data in Taxonomies, LMIs, Labor Market Forecasts, and HR Analyses

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In this new episode of our Uncovers Series, we delve into the critical issue of incorrect data in taxonomies, labor market information (LMI), labor market forecasts and predictions, and HR analyses. We explore the challenges posed by the use of unsupervised, unverified data from various sources, which is then applied without critical examination to processes such as matching, gap analysis, labor market forecasts, and demand/supply predictions.

The Quality of Skills and Job Data

In this post, we aim to shine a spotlight on the overall quality of skills and job data that permeate official and commercial taxonomies, language models, and various applications. Often sourced from the internet, this data is integrated into collections and models without rigorous scrutiny, leading to alarming deficiencies in its reliability and accuracy. Our investigation, presented in a revealing video, exposes the unsettling standards adopted by numerous companies and governments in their HR processes and labor market analyses. Despite the gravity of the situation, the video offers a blend of humor and disquiet, providing both insight and entertainment.

The Imperfections of Official and Commercial Data Sources

It is vital to recognize that even esteemed taxonomies and data sources, such as ESCO, CEDEFOP/Eurostat, O*Net, as well as popular collections from Lightcast, Textkernel, LinkedIN, and others, are susceptible to errors. Regrettably, these sources are widely utilized across various processes without comprehensive verification of their accuracy. While these taxonomies were developed with the noble aim of facilitating precise categorization and enhancing labor market research, their implementation has often fallen short of the mark.

Impact on Labor Market Forecasts and HR Analytics

The repercussions of working with inaccurate data, including that sourced from official taxonomies, can be profound. Such data can lead to flawed decision-making, misallocation of resources, and ineffective workforce planning. Furthermore, biased or misleading information can distort insights, resulting in misguided recruiting strategies, inadequate employee development initiatives, and suboptimal organizational performance.

Overcoming the Challenges

To address these challenges, organizations must prioritize data quality and integrity in their collection and analysis processes. Implementing robust data validation and cleansing mechanisms, utilizing multiple data sources for cross-verification, and leveraging advanced data analytics techniques, ideally by labor market experts, can significantly enhance the accuracy and reliability of labor market forecasts and HR analytics. In summary, the poor quality of data and potential errors in official taxonomies present significant hurdles for labor market forecasting and HR analytics. By addressing these challenges and placing a premium on data quality, government labor market organizations and companies can unleash the true potential of data-driven insights for informed decision-making and strategic HR management. For comprehensive insights and solutions, organizations can turn to JANZZon!, the world’s most comprehensive, complete, and hand-curated labor market data ontology, available in over 60 languages and tailored to hundreds of labor markets globally.