Introduction

AI in HR and Recruitment Statistics: AI is increasingly shaping the future of Human Resources (HR) and recruitment, offering innovative solutions that streamline processes and improve decision-making. The global AI in HR market is projected to grow from $2.4 billion in 2021 to over $11 billion by 2027, reflecting the widespread adoption of AI technologies.

These tools are revolutionizing areas like resume screening, candidate sourcing, and interview processes, improving efficiency and reducing hiring biases. AI’s ability to analyse vast datasets enables HR professionals to make data-driven decisions, while also enhancing candidate experience.

According to a 2019 survey, the trend that is most likely to shape the global recruiting industry is employee experience, with ** percent of respondents identifying this as a top trend. Recruiting industry Globally, the most common way for new staff to be recruited is through online job postings, either on job boards or career websites. However, these are also the least effective recruitment channels. The most effective recruitment channels, measured in terms of the number of hires to applicants, were candidates sourced by a hiring manager and internal applicants. Both these channels have a reduced ability to reach jobseekers though, reducing the potential pool talent.

Introduction

Online Recruitment Statistics: Online recruitment statistics provide valuable insights into the changing dynamics of the hiring process. As businesses increasingly turn to digital platforms, these statistics highlight the efficiency, effectiveness, and broad reach of online recruitment strategies.

Important trends such as the growing role of social media in talent sourcing, the widespread adoption of Applicant Tracking Systems (ATS), and the shift toward remote and hybrid work arrangements are reshaping how companies connect with potential candidates.

By examining these statistics, organizations can refine their recruitment strategies, improve hiring efficiency, and enhance the candidate experience, ensuring they remain competitive in the fast-evolving digital job market. These insights are essential for understanding how technology is shaping the future of recruitment and the workforce.

Introduction

Recruitment Automation Statistics: Automation in recruiting is revolutionizing the way we hire globally, and there is a great space for AI solutions that can lead this revolution. 87% of companies use AI in their hiring processes. The use cases are for searching for candidates, filtering them ou,t and nurturing them along the way. This broad application is based on the productivity gains that AI provides, with some companies achieving a 70% reduction in time to hire with AI recruitment tools, for example.

Monetarily, the adoption of AI has led to a 30% decrease in cost-per-hire, showing us that it pays for itself! But there are challenges as well that come with this transition that must be addressed. While AI is, without a doubt, a big part of recruitment, balancing technology with morality is still as important.

Laos Number of Recruitment data was reported at 168,380.000 Person in 2017. This records an increase from the previous number of 83,811.000 Person for 2016. Laos Number of Recruitment data is updated yearly, averaging 70,645.500 Person from Mar 2012 (Median) to 2017, with 6 observations. The data reached an all-time high of 168,380.000 Person in 2017 and a record low of 43,670.000 Person in 2013. Laos Number of Recruitment data remains active status in CEIC and is reported by Lao Statistics Bureau. The data is categorized under Global Database’s Laos – Table LA.G008: Employment Statistics: Number of Recruitment and Registrant.

This statistic shows the ease of recruitment of data analysts for big data positions in the United Kingdom (UK) in 2014. The recruiters did not encounter great encounter difficulties with finding candidates for the positions as ** percent of them stated that it was "very easy" or "fairly easy" to fill in the positions.

Laos Number of Recruitment: Abroad data was reported at 49,386.000 Person in 2017. This records a decrease from the previous number of 58,301.000 Person for 2016. Laos Number of Recruitment: Abroad data is updated yearly, averaging 35,961.500 Person from Mar 2012 (Median) to 2017, with 6 observations. The data reached an all-time high of 92,900.000 Person in 2015 and a record low of 7,414.000 Person in 2012. Laos Number of Recruitment: Abroad data remains active status in CEIC and is reported by Lao Statistics Bureau. The data is categorized under Global Database’s Laos – Table LA.G008: Employment Statistics: Number of Recruitment and Registrant.

Introduction

Employee Referral Statistics: Employee referral programs continue to be a mainstay of contemporary recruitment strategies, providing a fast and effortless way to acquire talent from employees' networks. The rapid hiring put into place by these programs also brings better hires, decreases costs, and increases retention.

Nonetheless, employee referrals have, in 2025, become a compelling point of its own, delivered by mighty employee referral statistics stating how employee hires land at the top in the competitive job market.

Historical Employment Statistics 1990 - current. The Current Employment Statistics (CES) more information program provides the most current estimates of nonfarm employment, hours, and earnings data by industry (place of work) for the nation as a whole, all states, and most major metropolitan areas. The CES survey is a federal-state cooperative endeavor in which states develop state and sub-state data using concepts, definitions, and technical procedures prescribed by the Bureau of Labor Statistics (BLS). Estimates produced by the CES program include both full- and part-time jobs. Excluded are self-employment, as well as agricultural and domestic positions. In Connecticut, more than 4,000 employers are surveyed each month to determine the number of the jobs in the State. For more information please visit us at http://www1.ctdol.state.ct.us/lmi/ces/default.asp.

Contracts registered by municipality, gender and age group, sector of activity and occupation group. Most contracted occupations by municipality, sex and age, and level of education.

In 2024, around ** percent of people said that there was a very high chance that they would use AI in order to decide the personnel selection when going through the recruitment process. Over ** percent said there was a high chance of using AI to analyze gestures and facial expressions of potential employees.

In 2025, there were estimated to be approximately *** billion people employed worldwide, compared to **** billion people in 1991 - an increase of around *** billion people. There was a noticeable fall in global employment between 2019 and 2020, when the number of employed people fell from due to the sudden economic shock caused by the COVID-19 pandemic. Formal vs. Informal employment globally Worldwide, there is a large gap between the informally and formally employed. Most informally employed workers reside in the Global South, especially Africa and Southeast Asia. Moreover, men are slightly more likely to be informally employed than women. The majority of informal work, nearly ** percent, is within the agricultural sector, with domestic work and construction following behind. Women’s employment As the number of employees has risen globally, so has the number of employed women. Overall, care roles such as nursing and midwifery have the highest shares of female employees globally. Moreover, while the gender pay gap has shrunk over time, it still exists. As of 2024, the uncontrolled gender pay gap was ****, meaning women made, on average, ** cents per every dollar earned by men.

The company's annual new employee recruitment quota, statistical data on the number of employees in various categories.

🚀 Welcome to the Naukri.com Job Portal Dataset! 🌟

Are you ready to embark on an exciting data journey? Naukri.com, India's premier recruitment platform, is your launchpad into the world of job opportunities. Here, you'll find a treasure trove of data that opens doors for job seekers, companies, and recruiters alike. Let's dive in and explore what this dataset has to offer!

Data Quest:

🔍 Data Expedition: To assemble this treasure chest of data, we embarked on a digital adventure through the vast oceans of naukri.com. Using the magical powers of Python and the mystical Selenium, we extracted job listings from the realms of Naukri, all with the noble intent of sharing this knowledge with the world. For those curious, the spellbook (code) we used can be found on GitHub.

Unearthed Artifacts:

Within this dataset, you will discover an array of artifacts, each bearing unique insights:

1. 📋 job_post: Behold the mystical role of the job, a beacon of opportunity.
2. 💼 company: The name of the recruiter company, as solid as the mountains.
3. ⭐ company_ratings: Witness the ratings of companies on naukri.com, stars guiding your path.
4. 📢 company_reviews: The number of reviews, a chorus of voices sharing their experiences.
5. ⏳ exp_required: The level of experience required, a key to the kingdom.
6. 💰 salary_offered: The treasure chest itself, revealing the bounties offered.
7. 📍 job_location: The map to your destiny, the location of the job.
8. 📜 job_description: A parchment filled with the description of your quest.
9. 🛠️ required_skills: The tools you'll need for this grand adventure.
10. 📆 Posted_as_on_22_5_2022: The celestial calendar, indicating when the job was posted relative to May 22, 2022. 🗓️

Magical Applications:

🪄 With this dataset, you possess the power to:

1. Data Alchemy: Transform raw data into a gleaming gem through the art of data cleaning.
2. 🪙 Feature Conjuring: Create new features and weave them into your data spells.
3. 🌌 Astrological Data Analysis (ADA): Explore the constellations of data and uncover hidden patterns.
4. 🧙‍♂️ Enchantment of ML/DL: Cast the spells of Machine Learning and Deep Learning to predict future job availabilities.

🎉 We thank you for joining us on this mystical data journey. May your adventures with this dataset be filled with triumphs and revelations! 🚀✨

Provisional experimental publication of NHS vacancy statistics created from administrative data related to published vacancy adverts obtained from NHS Jobs, the main recruitment website for the NHS. The statistics referred to in these tables are exploratory and provide information on the administrative data available from NHS Jobs as much as on the recruitment of staff. This publication provides figures which are an insight to recruitment in the NHS but which should be treated with caution, and users are discouraged from attempting to draw any conclusions from this data at this time. Due to a change in methodology (moving from a count of vacancy adverts to advertised vacancy full-time equivalents) these figures are not directly comparable to to each other, therefore this data should not be used to extend that time series. For further details on the change in methodology please refer to the 'Points to note' section of the publication report.

The Current Employment Statistics (CES) program produces detailed industry estimates of employment, hours, and earnings of workers on nonfarm payrolls. CES State and Metro Area produces data for all 50 States, the District of Columbia, Puerto Rico, the Virgin Islands, and about 450 metropolitan areas and divisions. Each month, CES surveys approximately 142,000 businesses and government agencies, representing 689,000 individual worksites. For more information and data, visit: https://www.bls.gov/sae/

Laos Number of Registration: Service data was reported at 9,248.000 Person in 2016. This records an increase from the previous number of 5,790.000 Person for 2015. Laos Number of Registration: Service data is updated yearly, averaging 4,625.000 Person from Mar 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 9,248.000 Person in 2016 and a record low of 3,984.000 Person in 2014. Laos Number of Registration: Service data remains active status in CEIC and is reported by Lao Statistics Bureau. The data is categorized under Global Database’s Laos – Table LA.G008: Employment Statistics: Number of Recruitment and Registrant.

This data set contains personnel data for DOT new hires and recruits. This data is maintained by the current HR and payroll provider (Department of Interior's IBC) and USAJobs. The data contains PII (Employee Name, SSN, Date of Birth, Home Address, etc.), Civil Rights (Disability, Gender, Race) and other sensitive data (Background Investigations and Security Clearance).

Recruiting and retaining top talent in the U.S. workforce continues to be a significant challenge for employers in 2024. Salary expectations and work-life balance are the leading factors influencing recruitment and retention, with ** percent of respondents citing these as primary concerns. This underscores the evolving priorities of the modern workforce, where compensation and quality of life hold equal importance.

Taichung City Amusement Tax Collection Statistics - Previous Year