Recruiting trends 2024

Digitalization in recruiting

Digitalization has revolutionized the talent acquisition process by opening up new ways of interacting and increasing efficiency. Modern recruiting software, AI-supported applicant tracking systems and digital communication platforms make it easier for companies to automate and optimize the application process. This is because these tools make it possible to identify suitable candidates more quickly and accurately.

They also simplify the pre-selection process and enable a targeted approach. They also support the analysis of applicant data - a fact that can contribute to more informed decisions in the selection process. According to an MIT study, productivity increases of up to 14% are possible if generative AI is integrated into everyday recruiting in a targeted manner. The use of digital technologies in recruiting also makes a significant contribution to increasing efficiency. In addition, it can promote diversity in staffing and improve the candidate experience by tailoring the entire application process to the individual needs of candidates.

Examples of digitalization in recruiting include

1. Automated application processes: Software to automatically capture and manage applications speeds up the screening process with the help of automated pre-selection of CVs and cover letters.
2. Applicant tracking systems (ATS): ATS track the applicant status and optimize the selection process. Artificial intelligence (AI) identifies the best candidates based on predefined criteria.
3. Digital communication platforms: Email, social media and chatbots make it possible to communicate with candidates quickly and easily. Video interviews bridge physical distances and offer flexible discussion options.
4. Data analysis and reporting: Applicant data can be analyzed to identify trends and potential for improvement. The success of recruiting campaigns can be tracked thanks to automatically generated detailed reports.

Artificial intelligence and machine learning in modern recruiting

AI and machine learning are fundamentally changing how organizations attract talent, evaluate their skills and hire them. It is important to note that AI does not make automated decisions in recruiting - AI helps recruiters to focus on what their job is all about: the candidates. This in turn has an impact on their skillset: soft skills such as emotional intelligence, empathy and appreciative communication at eye level will become even more crucial in the future. The new technologies can achieve this:

1. Automation of manual tasks

AI algorithms simplify the candidate search and selection process by analyzing and pre-sorting CVs, job descriptions and relevant data. This makes it easier to identify qualified candidates and relieves recruiters who would otherwise have to sift through countless applications manually.

2. Precise assessment of qualifications and skills

AI can quickly process large amounts of data and efficiently and accurately evaluate qualifications, skills and experience based on CVs and other documents. Natural language processing (NLP) and machine learning play a major role in the further development of the technology.

3. Improving the candidate experience

AI-powered chatbots and virtual assistants interact with candidates in real time, answering inquiries, scheduling interviews and providing personalized updates. This interactive communication improves the candidate experience and can help candidates feel valued and engaged throughout the hiring process.

4. Efficient candidate search

AI tools search and analyze large amounts of data from various online platforms, social media and professional networks. They identify potential candidates who meet specific criteria. This allows suitable candidates to be found more quickly.

5. Objective assessment of skills

AI technologies objectively assess candidate skills and qualifications by analyzing multiple data points. However, AI is not error-free and was trained by humans who did not necessarily act neutrally (-> data bias). For this reason, all applications should be reviewed again by experienced recruiters. Advanced algorithms evaluate technical skills, cognitive abilities and behavioral characteristics, which can give recruiters valuable insights into the suitability and potential of applicants.

6. Background check and reference check

AI can collect and analyze data automatically. This makes it easier for recruiters to process large amounts of information and identify potential discrepancies. AI can also help analyze reference responses and quickly identify key findings for an efficient, standardized reference checking process.

7. Onboarding and employee experience

AI can play an important role in the onboarding process by providing personalized training materials and answering employee queries. AI tools can also help organizations to continuously develop employees. For example, they can provide the manager with initial incentives for personalized development suggestions, which can promote a positive employee experience.

AI and machine learning have many advantages in recruiting. They optimize the recruitment process, automate tasks and increase efficiency. They also improve the experience of applicants and employees.

Two things are important in all of this: Firstly, the focus must be on people, and in particular on the candidates. Secondly, AI should only support recruiters and not make their own decisions.

Recruiting analytics: data-based decision-making in human resources

Recruiting analytics is an indispensable part of human resources today. Companies use data-based analyses to refine their recruitment strategies and make informed decisions. Several key elements play a role here:

1. From basic data to in-depth analyses

70% of company managers state that they consider people analytics to be a top priority. For this reason, most large companies have people analytics teams whose team sizes, compositions and organizational structures vary.

2. Challenges and progress

Despite the interest in better data management and HR technologies, there is still a long way to go to fully utilize analytics. Many companies report a challenging initial phase in building their people analytics capabilities - particularly in data cleansing and reporting optimization.

3. Building a strong database

A high-quality data basis is crucial for the success of recruiting measures. However, data must be extracted from transaction systems, cleansed and restructured. Only then can it be used for analyses and consistent data collection and processing be guaranteed. Managing HR data systems requires considerable resources, time and investment.

4. Using and experimenting with data

Once a solid database is in place, teams can experiment with new technologies to help them analyze and disseminate data. This can result in business solutions that are tailored to the individual needs of companies - from automated HR dashboards to customized software solutions for self-service applications, everything is possible.

5. Development of advanced analytical skills

Data scientists use programming languages such as R, Python and Julia. They help them understand complex phenomena and develop actionable recommendations for strategic decisions. Teams that master descriptive and automated reporting are ready to further develop their analytical skills.

6. Scaling and infrastructure challenges

The AI infrastructure poses a scalability challenge and could require the use of cloud services. Many teams are still working with on-premise infrastructures and do not appear to be planning to migrate their data to the cloud any time soon.

7. Application example during the COVID-19 crisis

Measuring the satisfaction of tens of thousands of employees worldwide on a weekly basis: This was achieved by a global organization that created a Pulse survey with the help of People Analytics. The survey results have helped the organization understand how to best support employees in a challenging time and in a fully remote working environment. 

Candidate experience: The importance of a positive applicant experience

The candidate experience is the experience that applicants have during the entire recruitment process. It influences how applicants perceive a company. It can also determine whether candidates accept a job offer or recommend the company to others. In a world where candidate experiences are shared online, a positive candidate experience can also strengthen the employer brand and attract qualified talent. In short, companies that invest in an outstanding candidate experience position themselves as attractive employers.

These are the key elements of a positive candidate experience and their importance:

1. First impression: The first contact, whether in the form of a job advertisement or the career page, shapes the first impression that applicants have of a company. High-quality content that matches the target group arouses interest.
2. Communication: Applicants appreciate prompt updates on their application status and constructive feedback. Transparent, regular and respectful communication throughout the application process is therefore crucial.
3. Application process: A simple, clearly structured application process that takes applicants a minimum of time contributes significantly to a positive experience. Online application platforms should be user-friendly and mobile-optimized.
4. Interview experience: Face-to-face or virtual interviews should be structured and professional. Interviewers should be well prepared and give candidates enough space to ask questions and present their skills.
5. Feedback and follow-up: Constructive feedback after the interview and prompt feedback, regardless of the outcome of the application process, are essential for a positive candidate experience.
6. Onboarding: Effective onboarding for successful candidates continues the positive candidate experience and can help new employees quickly feel at home in the company.

Future-proof skills and lifelong learning

The job market is changing rapidly and constantly. A change that requires skills to be taught and developed in a new way. Various soft skills are becoming increasingly important - and also play a role in the evaluation of potential candidates.

1. Importance of soft skills:

The ability to communicate and work in a team, critical thinking, emotional intelligence and creativity are examples of soft skills that are becoming increasingly important in the modern, constantly changing world of work.

2. Adaptability and flexibility:

Industries and technologies are evolving rapidly. The ability to adapt quickly to new situations is crucial - and flexible applicants and employees who are willing to learn are particularly valuable to companies.

3. Lifelong learning as the norm:

For both employees and employers, lifelong learning is becoming the new norm in order to keep up with the current and future demands of the job market. Training and further education programs help employees and companies to continuously develop.

4. Investment in employee development:

For long-term competitiveness, it is crucial that companies invest in the development of their employees - not only in the form of professional training, but also in soft skills and DEIB training.

5. Future-proof technology knowledge:

In addition to soft skills, technical skills are becoming more important, especially the use of new technologies and digital tools. Companies and employees need to familiarize themselves with the latest technological developments in order to operate efficiently and effectively in a digitalized working environment.

Overall, the future of recruitment and professional development will be heavily influenced by a willingness to engage in lifelong learning and the ability to adapt to new challenges. Companies that recognize and support these trends will create a resilient, innovative and sustainable workforce.

Blue Collar: Winners of the AI revolution

While job profiles of knowledge workers, content creators and the service industry will change fundamentally due to the influence of AI, professions in the skilled trades and jobs where physical and social work is important will benefit: demand in healthcare, the energy sector, high-tech manufacturing and construction will increase, which will mean a significant boost for 'blue collar' jobs. This is confirmed by a report by the World Economic Forum in cooperation with Accenture. It examined 19,000 individual tasks in almost 900 professions to determine the extent to which they could be influenced by AI. The results: Occupations with a high level of personal interaction and non-routine physical tasks are least likely to be affected by AI. "The physical jobs that will be safe in the next five to ten years are characterized by activities in an unpredictable physical environment," Kweilin Ellingrud, director of the McKinsey Global Institute, told Business Insider. "If it's a predictable physical environment that's repetitive, then either a robot - probably before generative AI - or some kind of generative AI can create the automation to do the job well."