How Spuerkeess is rethinking the role of HR in banking

Putting people at the center with AI

With a bold, technology-supported approach to internal mobility and people development, the bank Spuerkeess is setting new standards in employee retention. At the heart of this is an HR initiative that has not only changed processes, but also created a new culture.

“Our vision was clear: internal mobility should not just be an administrative act, but a living part of our corporate culture,” says Sandra Schengen, Head of HR & People Management at Spuerkeess, describing the motivation behind the project. The aim was not only to give employees transparency about open roles. But also to show them real development opportunities regardless of their current position.

A first milestone on this path was the bank’s internal job fair launched in 2024; over 250 employees, 25 participating departments and more than 30 workshops turned the event into a lively marketplace for exchange, inspiration and perspectives.

Linking existing potential and roles with the help of AI

A central element of the project: employees were able to use AI-supported personality diagnostics to gain new insights into their individual personality traits and corresponding skills. Characteristics such as resilience, agility, self-efficacy and entrepreneurial thinking were made visible, not as an assessment but as an invitation to reflect. Many participants took the opportunity to compare the results specifically with career paths within the bank. Employees found the combination of technological precision and an open and engaging exchange to be particularly valuable.

The new strong role of HR

However, the initiative not only had an impact on employees. It also strengthened the HR department itself. It is now more visible, strategic and modern than ever before. The systematic integration of AI has enabled HR to position itself as a partner at eye level for managers and employees.

From trade fair to approach

What began as a one-off event has become the starting point for a broader change. Today, Spuerkeess uses AI-based personality diagnostics in key areas: in the selection of new talent, in leadership development and in coaching. What is important here is that the technology is used responsibly and in line with the bank’s values. That is: data protection-compliant, ISO-certified and EU-hosted.

Technology that serves employees

What Spuerkeess is showing with this initiative can also serve as inspiration for others. It’s not about digitalization and AI for its own sake. It’s about using the right tools and the right attitude to create a more human, appreciative working environment in which people can make the most of their personalities and skills. “When we give our employees the right tools, they not only discover new roles, they also discover themselves. And that’s where the real potential of our time lies,” says Sandra Schengen.

Read the full interview with Sandra Schengen here.

What companies would never learn about their employees without AI

73% of all talents are ready to make a move – but only if you do!

The shortage of skilled workers is reaching new record levels: according to a study by ManpowerGroup, 86% of German companies are struggling to find talent. When promising candidates suddenly drop out or are lured away by counter-offers, it’s not only frustrating but also expensive. Unfortunately, this is exactly what often happens

Personality vs. hard skills

Why companies often make the wrong decisions despite knowing better? A new study of 110 HR experts clearly shows that the majority of companies are aware of the importance of personality and soft skills in recruiting. Many HR professionals are also aware of their own shortcomings when it comes to finding the right talent for the right positions.

What really motivates employees? – This question is more relevant today than ever, especially in industries such as consulting and financial services, which rely on trust, expertise and personal relationships and are also under high pressure to innovate. Traditional employee surveys often only provide superficial answers. A study from the manufacturing industry clearly shows how companies can use AI-based Natural Language Processing (NLP) technology to delve deep into the actual experience of their employees – and gain concrete ideas for action.

The study: 40,000 open answers, intelligently analyzed

In a large-scale study, Zortify and Great Place to Work analyzed over 40,000 open-ended text responses from employees at industrial companies using NLP technology. Unlike multiple-choice questions, open answers allow an unbiased view of what is really important to employees. NLP makes these answers measurable, comparable and structurable in terms of content – e.g. via semantic cluster analyses.

The result:

Employees with low loyalty to the company speak significantly more often about poor leadership – even more often than about salary. Highly committed employees, on the other hand, mainly talk about team culture, appreciation and meaning.

The real game changer: experience as a management parameter

The key finding from the study:

“The employee experience must become the starting point and benchmark for all transformation activities.”

Marcus Heidbrink, Co-Founder and CEO of Zortify

With the help of AI, this experience can be systematically recorded and incorporated into decision-making processes for the first time. Companies can use an NLP tool to analyze tens of thousands of responses on the emotional state of employees and extract the most important topics, problems and moods from them. In terms of the diversity of opinions, this corresponds to the input from a large number of focus groups, the implementation of which would entail enormous costs.

Active listening with AI offers three key advantages, particularly in industries such as finance and services, which are experiencing major upheavals and a growing shortage of skilled workers:

1. Understanding instead of assuming

NLP tools not only recognize whether someone is dissatisfied, but why – in the employees’ own words. This enables differentiated, target group-oriented measures.

2. Culture as a lever for loyalty

The perception of values such as appreciation, innovation or tradition differs significantly between loyal employees and those who are willing to change jobs. Targeted action here strengthens emotional loyalty.

3. Shaping transformation effectively

The study highlights cultural factors such as participation, autonomy and communication quality as key retention factors. NLP technology helps to identify these in employees and turn them into strategic control variables – especially in hybrid, dynamic working environments.

Employee satisfaction in the financial sector: no reason to be complacent

At first glance, the financial sector performs well in recent studies when it comes to employee satisfaction – top 10 at kununu and at the top of the Pens Study 2024. The sector scored particularly well for corporate culture (4.26/5), working environment (4.22/5) and diversity (4.40/5). However, as is so often the case, first impressions can be deceptive. This is because the scores say nothing about increasing polarization within the sector:

Job security in private banks is only 49% (vs. 70% in public sector institutions).
Management deficits and work intensification are increasing despite rising salaries.
Over 80 % of institutions report a shortage of skilled talent.

Conclusion

At a time when talent is more selective than ever and work pressure is increasing in many areas, it is no longer enough to conduct a survey once a year. If you want to retain your employees, you have to listen continuously. NLP technology makes this listening efficient, scalable and intelligent.

Employee retention starts with genuine participation – and AI provides the key.

You can download a detailed summary of the study from Zortify and Great Place to Work here.

73% of all talents are ready to make a move – but only if you do!

Personality vs. hard skills

Recruiting in transition: Why “Hire & Pray” is no longer enough

It is said that diamonds are only created under pressure. We wouldn’t agree with this saying when it comes to recruiting. Under pressure, our judgment suffers. Under pressure, suitable candidates are more easily overlooked or applicants are hired overhastily who later turn out not to be suitable. The cost of bad hires runs into the hundreds of thousands.

According to Greenhouse’s Candidate Experience Report, the majority of candidates find the recruitment process frustrating, unfair and inefficient – despite the high demand for labor. Other studies show a similar picture: according to “JobTeaser”, 41% of applicants cite excessively long decision-making processes as the main reason for abandoning an application process. Negative reviews or a poor company reputation can also act as a deterrent and lead to dropouts.

The hidden costs of a lost candidate

Candidates dropping out has far-ranging consequences:

Time and money invested in the recruitment process is lost.
Teams have to make do without the necessary support for longer, which can affect productivity.
Frequent dropouts in application processes damage the company’s reputation and discourage further applicants.

The reason why this keeps happening: Many companies are too passive throughout the entire process. Publish a job advertisement, then wait and see? That’s no longer enough. Successful recruiting requires proactive strategies in order to attract top talent and not have to rely on less qualified applicants.

The active, strategic search for the best candidates should begin long before the actual application process. Thanks to new AI-based technologies, there are now innovative ways to target potential talent. According to the LinkedIn Talent Trends Report 2024, 73% of the global workforce is made up of passive candidates – people who are not actively looking but would still be willing to change jobs. A huge pool from which recruiters can draw.

Active sourcing reduces costs and increases retention

Companies that actively approach talent benefit from lower time-to-hire and cost-per-hire values. At the same time, candidate satisfaction increases, provided they are approached individually and not flooded with generic recruitment emails.

The key word is personalization. And no, a personal address in an email that is otherwise designed for mass mailing is not enough. Companies that show genuine interest in the skills and experience of applicants have a better chance of receiving a positive response. The second contact should therefore be personal and conversational. AI tools help to initiate a mutually beneficial exchange and combine data-based analysis with human relationship management.

How exactly do they do this?

The AI boost for active recruiting

This is where our AI-based personality analysis from Zortify comes into play: Desired candidates first answer a set of open questions, the answers to which are analyzed by the AI. Key personality traits such as the Big Five, entrepreneurial thinking or self-efficacy are assessed.

The analysis, including the respective answers, provides a wonderful basis for an in-depth discussion with the candidates and a structured interview: To what extent are individual answers particularly reflected in the results of the analysis? Which results on self-perception and assessment by the AI surprise them and why? In which areas of the company can they be most effective due to certain characteristics? And where do they see potential for development? At the same time, the analysis is a filter for companies to decide whether the candidates who appear promising at first glance really fit the role and the company.

The de-briefing can take place in three ways:

The recruiting team discusses the results directly with the candidates.
The recruiting team evaluates the results together with Zortify and receives recommendations for action.
Zortify takes over the de-briefing.

The aim is not only to make interview processes more efficient, but also to improve their quality – through clear criteria and individual questions. If the profile is not ideal, the analysis report enables an appreciative, data-based refusal. This not only saves our clients 1-2 rounds of interviews, but also the candidates. The latter still take away a positive experience because they gain new insights about themselves and possible professional futures. The importance of this aspect is underlined by the figures from the Greenhouse study: for a good 68% of applicants, constructive feedback increases their motivation to contact the company again at a later date, even in the event of rejection.

Conclusion: Rethinking recruiting

So what does HR need in order to shape the application process in such a way that it not only results in short-term placements with outstanding candidates, but also in sustainable relationships with people in a growing talent pool?

Rethinking: Less passive recruiting, more active sourcing.
Personalization: Proactive and personal approach to candidates throughout the entire process.
Skills development: HR teams need to familiarize themselves with active recruitment strategies and AI tools.
Gradual technology integration: Use browser-based solutions as a starting point to keep costs low.
Suitable providers: Choose providers that not only deliver tools, but also offer coaching and ethical advice.
Focus on people: For both recruiters and candidates, people are the deciding factor.

Companies that base their recruiting strategy on a proactive, people-centered foundation will attract the best talent in the long term. The figures show: Now is the right time to take action.

Schedule a demo with Zortify

Finding the right talent does not allow for compromises!

Applicants want a fast, appreciative application process – companies, on the other hand, need a lot of information to prevent wrong hires, as well as efficient and structured processes to keep costs low and not make themselves liable to legal action. How does HR find the balance – and the best talent at the same time?

New Leadership: Nice is the little brother of toxic.

We think it is right and important that we as a society discuss topics such as “toxic masculinity” and clearly name corresponding misconduct as such. Language shapes our being and our consciousness; We can only describe problems and thus make them discussable if we have words for them. Toxic is such an important word.

Recruiting in transition: Why “Hire & Pray” is no longer enough

Recruiters are under pressure from many sides. They have to find the best candidates in a competitive market. The willingness of young people in particular to change jobs is higher than ever, as are their demands on employers. These demands are not only directed at the job itself, but also at the application process. Companies that fail in the candidate experience lose the best talent during the selection phase. Decision-makers, on the other hand, expect their recruiting teams to fill positions as seamlessly as possible with talented individuals who are both professionally and personally convincing.

In a survey conducted by the Society for Human Resource Management, 53 percent of recruiters surveyed stated that the stress level in their job has increased compared to the previous year. And it continues to rise with every unfilled or incorrectly filled position.

We should be talking about resilience now at the latest.

And in its actual meaning. Because contrary to what is often assumed, resilience does not mean being particularly resistant. Instead, it is the ability to pick yourself up again after setbacks and look ahead with optimism. “Ability to recover” is an excellent translation.

Resilience is a psychological resource that people can ideally activate reliably. At the same time, it is by no means only natural or fixed. We can learn and train resilience. It plays a key role in enabling us to do a good job in challenging environments, in contact with different personalities and in the face of increasingly rapid change. This is another reason why resilience is a sought-after quality that can determine whether we are the perfect fit for a position or not. But also whether we would have been the perfect fit for a position, were rejected and still go into the next job interview with confidence. And whether, when we are on the other side and have to make hiring decisions ourselves, we allow ourselves to be paralyzed by bad hires from the past or consciously remind ourselves of them in order to learn and grow from them.

And whether we do not allow ourselves to be carried away even after overwhelmingly positive experiences. But remain vigilant, focused and self-critical. We conducted a study on this in a call center, the results of which can certainly be applied to recruiting (as a special type of sales). In the study, the top performers showed significantly higher scores for resilience and self-efficacy than those employees who were not convincing on the phone.

Resilience as a top skill

The latest Future of Jobs Report from the World Economic Forum names resilience as the second most important core skill (after analytical thinking) for work in 2025. Companies need resilient people more urgently than ever before – both in recruiting and on the applicant side. The key question is: How can organizations shape the conditions for recruiting teams in such a way that they do not burn out under the increasing pressure, do not become discouraged by failures in a highly competitive and complex environment, in other words become and remain resilient? How do decision-makers, HR management, recruiters and hiring managers find a common understanding to identify the best candidates? And how do resilient recruiters find resilient employees for all roles that need to be filled?

We clearly see companies as being responsible for creating an environment in which employees can use their resources and activate them again and again. The following approaches can be particularly useful with regard to the demands placed on the recruiting team:

Reduce workload with AI

Routine tasks, such as scanning CVs or scheduling interviews, can and should be automated so that recruiters and hiring managers can focus on what comes after the first impression.

Streamline the application process

With the help of AI-based personality diagnostics, key characteristics that go beyond the CV can be identified even before the actual job interview. The Big 5, as well as optimism and resilience, are some of these characteristics. The analysis reports provide recruiters with an excellent basis for deciding who is worth inviting to an interview. Which candidates are worth investing more time in and which are simply not a good fit. This approach benefits both sides. As applicants don’t want to spend an unnecessarily long time in a selection process where their chances of success are close to zero.

Recruiters can also use the reports from the AI analysis to make the following interviews more efficient. The reports we generate with Zortify are based on open text answers from applicants. And therefore provide wonderful starting points for an in-depth dialog. Instead of working through generic questionnaires, recruiters can use the evaluations to ask specific questions about the applicant’s personality, team dynamics and working style.

Backing up decisions with data

The personality data analyzed with the help of AI helps the recruiting team to implement two key aspects of good talent selection. Even under pressure: a consistent focus on the individual and an objective comparison with other candidates. The data enables everyone involved in recruiting to develop a common understanding. And agree on what is important in the further selection process.

For example, a candidate may be perfectly qualified, but not particularly resilient according to the analysis. This is where recruiters need to assess the options: Do we give top priority to skills and prefer to invest in developing the person’s resilience on the job, or do we opt for an applicant with the second-best CV but who has a distinctly resilient personality? – By making these factors discussable and developing a shared understanding of desired qualifications, organizations reduce the pressure on recruiters, decrease bias on all sides and increase the accuracy of hiring predictions.

Creating psychological safety

An environment in which mistakes are named as such, but are also seen as a learning opportunity, reduces the pressure on recruiters and promotes their resilience. Regular feedback loops between hiring managers and executives also help to understand each other’s work and challenges and improve collaboration.

KPIs instead of “hire & pray”

It is clear that the pressure on companies will not decrease in the years to come. On the contrary: Germany will lose seven million skilled workers by 2035 as the baby boomers retire and low birth rates follow. Competition for talent is likely to intensify further. At the same time, technological development is making huge progress. Which on the one hand increases the need for new skills, but can also massively relieve the burden on companies in general and recruiting teams in particular.

AI-based analysis tools can make the recruitment process faster, more targeted and more objective. As a result, recruiters have free resources to take on a proactive role. Instead of constantly reacting to urgent staff shortages, they can focus on the question of which skills and personalities the organization really needs to grow and thrive in the long term. The aim is to move away from a reactive “hire and pray” approach towards proactive, data-driven recruiting that ensures the company’s long-term talent supply. This kind of anticipatory, strategic workforce planning goes far beyond short-term recruitment. And ensures that the right employees with the right skills are in the right place at the right time.

From panic to precision: how data-driven recruiting brings long-term success

A key lever here is the use of data and KPIs. While Sales tracks in detail how effective measures are, this systematic approach is often lacking in Recruiting. However, in order to grow with their tasks instead of cracking, recruiters need to specifically analyze which factors have led to a successful hire or a bad hire. They can significantly increase their success rate by analyzing past wrong decisions, recognizing their own bias and learning from it.

At the same time, they need to develop a deep understanding of the company’s future requirements. This includes not only assessing skills and experience, but also taking into account personality traits, development potential and career paths. In order to anticipate market trends and build talent pools at an early stage. It is more important than ever for recruiters to work closely with managers and colleagues in business development and marketing (employer branding). At first, this may sound like even more work. In fact, this kind of rethinking takes a huge amount of pressure off recruiting teams because it replaces short-term panic with long-term, sound planning. And at best, this leads to smart and sustainable recruiting strategies.

That is, strategies that produce plenty of diamonds even without excessive pressure.

Finding the right talent does not allow for compromises!

New Leadership: Nice is the little brother of toxic.

Expensive, unloved employees: How to avoid bad hires

The start of the year traditionally brings movement into the company. Employees leave, others have to fill the gap, and new employees have to be found and trained at the same time. And the question always arises: How do we ensure that the next person really fits in with us? That they won’t leave for new shores at the next full moon or turn of the year?

Applicants want a fast, appreciative application process. Companies, on the other hand, need a lot of information to prevent wrong hires, as well as efficient and structured processes to keep costs low and not make themselves liable to legal action. How does HR find the balance – and the best talent at the same time?

One thing is clear: a poor application process can be expensive. Specifically, when companies:

hire candidates even though they don’t suit them,
reject candidates who would actually be a good fit,
lose candidates in the process because they are frustrated,
risk their reputation due to recurring negative candidate experiences, resulting in bad reviews on Kununu or Glassdoor.

Where false judgements are made

Misjudgements happen, for example, when recruiters are overly impressed by features such as prestigious universities or large companies on a CV and then neglect to track down the really relevant qualifications. In interview situations, eloquence and self-confidence can mask a lack of skills.

Qualified candidates, on the other hand, run the risk of being weeded out early if their CV does not meet the formal requirements. Or if they sell themselves poorly in their cover letter. In stressful interview situations, introverted or less eloquent applicants sometimes perform worse. Even though they would be an excellent fit professionally.

Is AI the solution? – A clear “yes and no”.

The risk of bad hires does not automatically decrease with the use of AI. Sometimes the same effects described above are at work. AI systems can scan CVs and cover letters for certain keywords or qualifications in order to save time. However, this can lead to the exclusion of suitable applicants if unconventional but qualified candidates are overlooked due to missing keywords. At the same time, there is a risk of mis-hiring if applicants appear to be suitable due to the clever placement of keywords, even though they are not.

The same applies to AI-supported systems that analyze video interviews to evaluate non-verbal clues such as body language and facial expressions. Such systems would rate candidates positively simply because they show good non-verbal skills. At the same time, qualified people can fall through the cracks if they are assessed negatively due to nervousness or cultural differences in their non-verbal communication.

Taking the candidate’s perspective

So what to do? – One thing is clear: the best formal recruitment process is useless if it ignores the needs of the applicants. There are studies on what candidates want in the application process. First and foremost: objectivity, transparency, speed and personal interaction. Whether AI systems can have a positive impact on these factors is assessed differently by potential applicants, according to a survey of 1,005 participants conducted by the International University of Applied Sciences Erfurt. The majority of participants stated that the use of AI could lead to an increasingly impersonal process. More than half feared being disadvantaged by programming errors. And over 40 percent believe that transparency and data protection are at risk.

It is interesting to see that the majority of respondents have not knowingly had any experience with AI in the application process. The proportion of supporters also varies greatly depending on their level of education and migration background. For example, people with a high level of education or migration backgrounds are more likely to see advantages in AI, especially with regard to non-discriminatory assessment. In addition, some of the statements in the study clash with the desire for objectivity formulated in other studies. For example, 59% stated that they feared that factors such as “likeability” would be pushed into the background. At the same time, likeability is anything but objective and says little about the expected professional performance.

What can recruiters conclude from these contradictions?

Here comes the ultimate recruiting recipe!

No, of course not. At least we haven’t found it yet. (But we’re working on it with Zortify.) 🤓

Our findings from seven years of working at the interface of HR and AI:

Walk the Talk: We can recommend to anyone and everyone to put themselves in the target group’s shoes and go through their own processes from an applicant perspective. Ask yourselves: How do I feel at the various stages of the process? Do I know what is happening and with what goal? Am I interacting with an AI or a human being? Would I still want to do the job after this experience?
Transparency requires clarification: Where AI is used, it is all the more important that HR experts make personal contact with applicants at critical points. For example, to explain where AI technology is used, what kind of evaluation it provides and what happens next. De-briefings and a personal meeting in the event of a rejection are also important to maintain the bond between the company and candidate.
Focus on individualization: Not every applicant has the same needs. While some applicants prefer a quick process, others want deeper insights into the company. Flexible application options, e.g. video interviews or trial days, can cater to both sides. The same applies to vacancies and roles: Not every job requires the same depth of information. For example, the application process for a management position can be designed differently than for an employee in production.
Data-based evaluation: In order to improve the candidate experience based on data, companies should regularly gather feedback from applicants (including rejected applicants) to identify bottlenecks or points of frustration. Think: candidate experience surveys. Other KPIs can also provide valuable insights, such as those that measure the performance of newly hired employees or figures on how long new employees stay with the company.
Reflect on your own thought and behavior patterns: Narratives such as the “talent vs. employer market” consciously or unconsciously shape the work of recruiters. Ask yourself self-critically: Do I always make quick decisions because I’m afraid of losing the applicant? Do I make compromises because I assume I won’t find a better candidate? – Becoming aware of your inner drivers helps to sharpen your focus on what the company really needs.

Conclusion: Hire slow, fire fast.

Candidate experience and business needs don’t have to be opposites – at best, they complement each other. Every recruiter has a responsibility for the company.

Even if the application process takes longer as a result, it is worth weighing up all the options carefully. AI systems can provide valuable insights, but the final decision should always be made by a person – or rather a group of people – with expertise.

In the short term, it may be tempting to hire a candidate, even if he or she is not an ideal fit – but in the long term, such a compromise will harm the company.

If a suitable candidate cannot be found immediately, freelancers, external experts or consultants can be a valuable alternative. Platforms such as ExpertPowerHouse, Upwork or Empion offer access to an expanded talent pool and make it possible to flexibly bridge short-term bottlenecks.

And last but not least: Fire fast. What may sound harsh is actually a deeply human move. After all, it serves no one’s interests to keep employees and give them the same negative feedback over a long period of time. What’s more, a bad hire puts a strain on the entire team. And: the world does not need more dysfunctional companies. But vibrant and innovative organizations that develop great solutions in a changing world. And that is much more likely with the right people in the right positions.

We look forward to your thoughts on this: Which levers are you already using successfully to ensure a good candidate experience and sound talent selection? – Join the discussion on LinkedIn.

New Leadership: Nice is the little brother of toxic.

Expensive, unloved employees: How to avoid bad hires

More Evolution, Less Disruption: 5 tangible HR trends

For companies, 2025 means less disruptive change and more evolutionary growth. In view of the overall social situation, especially with the rise of populism, the pressure is increasing not only economically, but also in interpersonal relationships. This is where companies need to take a closer look. It is more important than ever to fill key positions with people who …

More Evolution, Less Disruption:

Five Tangible HR Trends to Get Started Right Away

1. Building Resilient Mid-Level Leaders

Many people are starting the new year potentially overwhelmed. According to a Gartner survey, three-quarters of HR managers feel overburdened by the expanding range of their responsibilities. The development of middle management often gets neglected, yet mid-level leaders are crucial in initiating, communicating, and supporting necessary innovations.

Therefore, in 2025 companies should focus more on developing leadership skills. AI technologies can support this by analyzing specific traits such as entrepreneurial thinking, resilience, or optimism in employees, and deriving targeted learning and development programs.

2. Investing in Long-Term HR Tech

More than half of HR leaders report that current technologies do not meet today’s or future requirements. The focus should not just be on efficiency but on supporting HR staff in their development.

A shift in thinking is needed: investments in smart technologies should aim to strengthen the transformative role of HR. The Gartner Hype Cycle shows that technologies go through various phases before they can be productively utilized.

Realistic management of these phases helps in setting expectations and developing sustainable solutions.

Gartner Hype Cycle

Currently, many companies are still between phases 2 and 3. Expectations for AI-powered tools are both highly positive and negative. At the same time, it is becoming increasingly apparent that AI alone does not offer a comprehensive solution. While this may disappoint some, it presents an opportunity for HR professionals whose task is to identify and foster human potential. They can skip the “trough of disillusionment” and proceed directly to the “slope of enlightenment.”

However, support from number-driven stakeholders is crucial. Investors and decision-makers must be willing to invest not only in time and cost savings but also in transformative technologies and learning and development programs for HR staff.

3. Cultural Change Bottom-up – With Change Influencers

Top-down mandated innovations often face resistance and contribute to “change fatigue.” After disruptive changes, it is essential to allow time for evolutionary stabilization. New things must “restabilize, lose their surprise effect, and normalize,” as sociologist Armin Nassehi puts it regarding successful societal change processes.

In a corporate context, “change influencers” can help foster changes. These employees with strong peer networks drive innovations forward. AI-powered tools can help identify them.

In this context, we highly recommend the Ada Fellowship Program.

Small, easily implementable technologies (“tech nuggets“) can also facilitate change and establish new work practices.

4. AI Competencies Become Mandatory – And Soft Skills Are Not Just Optional

Starting in 2025, the EU AI Act will require companies to ensure that employees using AI systems possess the necessary competencies. As technology becomes more embedded in HR work, HR departments will increasingly depend on other disciplines within the company, such as data protection, IT, legal, work councils, or procurement. The first three will become even more involved in assessing the potential risks of AI. Companies must therefore rethink their processes and consider how to implement AI tools to take on truly business-critical tasks. Ideally, they will have a provider that supports them and ensures that the systems are used in compliance with EU regulations.

Alongside technical knowledge, fostering soft skills remains crucial. As technology increasingly shapes our daily lives, reflecting on our interactions with it becomes more important. What behaviors do we want to maintain? What should we let go of? What new ones should we establish?

5. Addressing the Skilled Worker Shortage: Strengthening Employees Instead of a Four-Day Work Week

The shortage of skilled workers is real. The craft sector alone currently lacks 113,000 skilled workers. However, companies are not merely wish-fulfillers. A four-day work week will not be feasible for most companies in 2025. Instead, they need to focus on how to achieve significant results with the existing workforce without burning them out. Here, psychology is also important, especially traits like resilience, optimism, and self-efficacy, which can be measured using AI.

Moreover, we need a shared understanding that work does not always mean joy but also involves growth and overcoming challenges. Conflicts are inevitable. What matters is how they are handled – whether people engage with each other respectfully and constructively even in difficult phases. There is no such thing as a “perfect organization” or a “perfect employee.” The acknowledgement of contradictions and simultaneity within an organization is crucial.

Ideally, the tools used should also consider this complexity. Instead of quickly categorizing people, they should aim to view all aspects of a personality in a differentiated manner and derive suitable roles and development opportunities for employees.

Conclusion

It will be a challenging year, but we remain optimistic. Despite external pressures, companies have many areas within their control, such as whom they hire and promote, how they collaborate, how they support their employees, and how they use the scarce “resource” of human potential effectively. Integrating AI technology offers enormous opportunities but requires a shift in thinking and learning at all levels – from leadership development to fostering soft skills to creating a supportive, encouraging, and demanding corporate culture. It is crucial for companies to focus not only on efficiency but on sustainable development and transformation skills, enabling people to adapt to new, challenging situations and use technology meaningfully.

13 + 1 Bias in Recruiting: How to Recognize and Overcome Them to Find Truly Suitable Candidates

Bias – unconscious thought patterns – can influence our perceptions and decisions. In the context of recruitment, bias can result in unfair evaluations of candidates, leaving potential untapped. This guide outlines common bias, their impact, and strategies to avoid them.

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Between Trump, zero-motivation-days and the “Robin Hood of talent”

Donald Trump will be the next US president. And in social networks, the concept of paid “zero-motivation-days” is being discussed, that is days off for employees without them having to call in sick or take vacation days. Two topics, although of different dimensions, which for us lead to one conclusion: Companies must start to face their responsibility!

Hierarchy with AI rather than everyone at eye level?

Companies promote flat hierarchies and a culture at eye level in order to attract skilled workers. That sounds very progressive and good for employees at first glance. But why do so many people still leave the company after a short time? Why is retention, i.e. retaining talent in the organization, still one of the major challenges?

Year 2 Post-GPT: How My Year Was Shaped and Why Work Must Remain Human

Florian’s 2024 Review

December 2024 – or, in the new chronology, Year 2 Post-GPT – marking two years since the go-live of the first version of ChatGPT. Requests like “Write a rhyming speech for my aunt Hannelore’s 60th birthday” or “Draft an outline for a whitepaper on the impact of generative AI on talent acquisition” – OpenAI’s chatbot has become an indispensable tool for many since November 2022, serving as both collaborator and colleague. Imperfect yet always available, it helps tackle writer’s block or tight deadlines. This past year, we at Zortify leaned on ChatGPT again for tasks like crafting social media posts.

Sometimes, though, it’s not perfect, as we’ve seen. 😉

The best posts? They came from us—straight from the heart, prompted by passion.

Hyperfocus and Hyperteams, Thanks to AI

December 2024 also marks six years of Zortify and two years of unwavering focus on what we believe will have the greatest impact on modern HR practices: AI-driven HR diagnostics. Our goal is clear: achieve an unprecedented level of accuracy in recruiting and development. This means fewer mis-hires, more productive teams, and the right people in leadership positions.

This focus sparked significant internal changes – some positive, some challenging. Team members left, others joined. Leveraging our own technology, which offers personality diagnostics and objective insights, we’ve built a dream team. And we’re growing. If you’re considering a career change in 2025 – especially in Sales – get in touch!

The Bright Side of AI

In December 2024, many businesses are still stuck in the old era – 2022 pre-GPT. While AI adoption has grown this year, it’s mainly large corporations taking advantage of the new tools:

48% of large enterprises use AI, compared to
28% of midsized companies and
17% of small businesses.

For many, the main obstacle remains a lack of knowledge. Clearly, we’re still in the early stages of widespread AI adoption in the economy.

However, in social media, the story is different. Fake news and deepfakes have become so pervasive that they threaten democratic systems. It’s a stark reminder of AI’s power—unfortunately, in its darkest form.

On the bright side, AI is also enabling remarkable things:

People relieved of tedious routine tasks,
Candidates finding jobs that align with both their skills and personalities, and
New, exciting roles emerging at the intersection of human and technological expertise.

Everyone wants these five colleagues* in 2024 (*or: this one AI)

While 2023 (Year 1 Post-GPT) focused on fears about job displacement, 2024 brought the realization that AI won’t replace humans in many areas; instead, it’s making human contributions more crucial than ever. Good work still hinges on collaboration – with other people and within diverse teams. It thrives on inclusion, objective analysis, and respecting individual uniqueness.

Looking ahead to 2025, the advance of AI will make the human element indispensable.

Why the Human Element Matters

1. AI Makes Human Expertise Absolutely Essential

In an age of ever-shorter innovation cycles, failing forward has become essential. Success lies in learning as we go, guided by those who are already a few steps ahead – those who’ve either learned from their mistakes or designed predictive models to avoid them.

At Zortify, we aim to be these forward-thinkers, guides, and shock absorbers for our clients. We teach the skills needed to use AI technology effectively, enabling businesses to focus on their unique challenges.

Incidentally, this is becoming a legal requirement in 2025. The EU AI Act mandates that employees working with AI possess adequate skills. With our certification program, we’re helping clients easily transition into this new era.

2. Culture Development Remains a Human Task

2024 has proved once more: culture first, AI second. Technology only succeeds within a supportive culture. Toxic work environments or outdated mindsets aren’t fixed by AI alone.

At Zortify, fostering a respectful and inclusive culture remains a core value. For me this includes taking on seemingly trivial tasks when necessary – whether it’s organizing meals for a certification event or stepping in to fill an unexpected gap.

At the same time, in view of our realignment and the associated changes since 2023, it was important to me to highlight and celebrate the achievements of our team. A good example of this and an absolute highlight in 2024 was our Zortify Connect Day, celebrating both our clients and our team. Hearing clients openly share their positive experiences with us was a testament to our team’s efforts and a major motivator.

There will also be a CONNECT Day in 2025. Pre-Registration has already started.

3. Leadership Requires Human Intuition, Clarity – and Free Calendar Time

Good leadership remains inherently human. It’s about knowing when to guide, when to step back, and when to empower team members. AI-based diagnostics can help identify and develop leaders with these qualities but cannot replace the human touch.

Templates - Nikolas Heilmaier - Instagram post

In 2024, I focused intensely on saying “no” to distractions, ensuring alignment with our priorities. This required clear communication – an area I worked to improve by preparing more thoroughly for meetings and fostering dialogue through active listening.

In my view, active listening remains the number one leadership skill. AI can support this, for example by identifying socially desirable behavior as such and providing insights that go beyond first impressions and the obvious. However, it is no substitute for an open door and an open ear policy fostered by leaders. Personally, I have consciously taken more time for feedback and review meetings in the past year and invested in our corporate culture.

An example of that was the implementation of “Open Calendar Time” on office days for spontaneous conversations and personal exchanges. These moments strengthened collaboration and trust within our team.

Conclusion

AI profoundly shaped our lives and work in 2024. In 2025, even more businesses and individuals will harness its potential. Still, collaboration will remain fundamentally human. Successful HR departments will blend deep AI expertise with the empathy and nuance that only humans can provide, using technology to elevate their impact.

At Zortify, we’re proud of our progress in 2024 – thanks to our amazing team. As the year ends, I’m filled with gratitude and excitement for the connections we’ll forge in 2025.

Happy Holidays!

13 + 1 Bias in Recruiting: How to Recognize and Overcome Them to Find Truly Suitable Candidates

links without title are not allowed

Between Trump, zero-motivation-days and the “Robin Hood of talent”

Hierarchy with AI rather than everyone at eye level?

13 Biases in Recruiting

How to Recognize and Overcome Them to Find Truly Suitable Candidates

1. Confirmation Bias

This occurs when we seek information that confirms our initial impressions. For example, during an interview, we might look for signs that affirm our positive or negative first impressions of a candidate.

How to overcome it:

Develop standardized interview questions.
Involve multiple interviewers to balance subjective views.
Use AI tools for an objective initial assessment.

2. Halo Effect

A single positive trait (e.g., confidence) influences our overall impression of a candidate, making other traits seem better than they might actually be.

How to overcome it:

Identify critical traits for the role in advance.
Use AI to conduct personality analyses before interviews.
Evaluate each competency independently.

3. Similarity Bias

We tend to favor people similar to ourselves in terms of background, values, or interests. This is often masked as “cultural fit” but can lead to unconscious discrimination.

How to overcome it:

Focus on objective role requirements rather than similarities.
Ensure a diverse HR team is involved in decision-making.

4. Stereotyping

Stereotyping occurs when we make hiring decisions based on external characteristics such as gender, origin or age. Our judgments are often based on unconscious assumptions (unconscious bias) and not on facts.

How to overcome it:

Conduct anonymized application processes.
Cultivate a culture of ongoing critical reflection on unconscious bias.
Penalize overtly discriminatory behavior.

5. Anchoring Bias

The anchor bias refers to the fact that first impressions or initial responses can have a disproportionately large influence on our overall assessment of a candidate.

How to overcome it:

Use data-driven tools to form a comprehensive view of candidates.
Make decisions only after collecting and reviewing all relevant information as a team.

6. Attribution Error

When we succumb to the attribution error, we immediately attribute certain behaviors to a candidate’s personality instead of to external circumstances. For example: “They are disorganized” instead of “They didn’t have enough time to prepare.”

How to overcome it:

Always consider the context behind behaviors or statements.
Ask candidates about the reasons behind their actions (“Was the preparation time adequate?”).
Use NLP-based tools to create objective personality profiles.

7. Recency Bias

In the case of recency bias, the most recent impressions or answers of the person in front of us have a greater influence on our perception than others. We often ignore what was said earlier.

How to overcome it:

Use standardized digital question tools before interviews.
Leverage NLP technology to analyze open-text responses for personality insights.
Systematically reflect on the overall impression as a team.

8. Overconfidence Bias

Relying too heavily on personal judgment and making quick conclusions (“I can spot a great salesperson instantly”).

How to overcome it:

Have your evaluations reviewed by others, combining human and AI input.

9. Horns Effect

The opposite of the Halo Effect, where a single negative trait taints the overall perception of a candidate.

How to overcome it:

Reflect on whether your negative judgment is based mostly on one trait.
Take time for a comprehensive evaluation.
Support decisions with objective data about the candidate’s personality.

10. Availability Heuristic

The availability heuristic describes how we are sometimes overly influenced by experiences or memories from the recent past. This can be, for example, conversations with other applicants that have just taken place.

How to overcome it:

Schedule interviews with breaks in between.
Incorporate data-driven evaluations of candidates’ skills and attributes.
Document impressions from each interview to mitigate post-hoc bias.

11. Status-Quo Bias

With a status quo bias, preference is given to candidates who align with established patterns. New approaches or unconventional profiles are often being overlooked.

How to overcome it:

Assess not just skills but also personality.
Actively seek out candidates with atypical CVs.
Encourage openness and innovation within the team.

12. Survivorship Bias

Survivorship bias occurs when we focus on traits of successful (former) employees while neglecting the potential of other characteristics, not giving unusual or unknown profiles the chance they deserve.

How to overcome it:

Identify which traits are truly critical for success in the role and organization.
Evaluate candidates’ abilities independently of previous benchmarks.

13. Loss Aversion

Preferring the “safe” candidate to avoid risks, even if another might better fit the company culture.

How to overcome it:

Consider the long-term benefits of bold decisions.
Use trial tasks or AI-based assessments to reduce the risk of poor hires.

14. Social Desirability Bias (“Super Bias”)

Candidates may present themselves in ways they believe are socially desirable, masking their true skills or values.

Example: A candidate emphasizes in the interview how important teamwork is for her, although in reality she prefers to work independently. This is solely a statement to meet the interviewer’s expectations.

The social desirability bias is so powerful because it can reinforce other bias. For example, if a candidate behaves in a particularly socially desirable way, the halo effect or the anchoring bias could be amplified. A strongly self-confident candidate could not only be noticed positively, but other skills could also be overestimated – even though they may only be faking them.

How to overcome it:

Use NLP technology for personality tests that analyze free-text responses, bypassing conventional cues.
In interviews, ask about specific past situations (e.g., “Can you give an example of solving a team issue?”).
Avoid giving hints about what you consider the “right” answer.

Conclusion

Biases are a natural part of decision-making but can have negative effects on both organizations and candidates. Through deliberate actions, standardized processes, continuous training, and the use of AI tools, we can counteract these distortions and make better hiring decisions. Recognizing these biases is the first step, followed by developing strategies to mitigate them. When human and artificial intelligence work together, the result is fairer hiring processes and finding the right people for the right roles.

Between Trump, zero-motivation-days and the “Robin Hood of talent”

Hierarchy with AI rather than everyone at eye level?

AI in HR: Overcome the fear, embrace the opportunities!

AI is neither all good nor all bad. Used correctly, it can improve the lives of many people in general and working life in particular. New opportunities are opening up in HR recruitment and development in particular, without people being ” sorted out ” or replaced by technology. Let’s take a look at what is important for a fearless, constructive and responsible approach to AI in HR.

I think organizations need to be aware of three things:

Flat hierarchies don’t eliminate the imbalances of power. Instead, they make them more difficult to grasp. They lead to power no longer unfolding on the basis of a fixed position, but finding its way more subtly. Through certain personality traits, for example, through the appearance, success or knowledge advantage of individuals.
A culture at eye level can be an advantage for some employees and exclude others. The question is: who is on an eye-level with whom? A workforce of people with the same background, the same ethnicity, the same skin color, the same socialization is very likely to hold the same biases – consciously or unconsciously – against people who don’t fit in.
In order to change organizational cultures, the structures must also change, i.e. the organizational framework: Processes, rules, sanctions, communication channels and criteria for selecting people to work in management positions.

How can AI technology make a difference here?

In order to change organizations and make them more attractive to many skilled workers (sidenote: by creating suitable conditions for parents and especially mothers, 840,000 vacancies could be filled immediately), the structure and culture in many companies must change in equally. Eliminating formal hierarchies is not the solution. It is much more important to fill leadership positions with the right people. With personalities who use their power (in the sense of influencing the actions, thoughts and development opportunities of other members of the organization) for the benefit of the people and the organization. Who lead empathetically and provide orientation and security instead of micromanaging and building up pressure.

Structures are designed to be self-perpetuating. Changing them means changing formal and informal rules, processes and communication channels. Therefore, it is not enough to say “We are committed to diversity and equal opportunities in the selection of applicants”. There needs to be an underlying operating system that defines the relevant processes in order to achieve greater diversity and equal opportunities. These could be quota regulations, regulations on leadership positions in part-time, a partially anonymized application process or new procedures for selecting talent.

Transforming the operating system

AI technology can help to change structures. It can change processes in such a way that human socialization and the accompanying biases become visible and have less impact on decision-making processes. It can make the abuse of power through informal or formal hierarchies less likely by backing up decisions with data and making them subject to objective evaluation. AI can help to break down stereotypical job classifications (women work in marketing and HR, men in IT and management). It can break down behavioral expectations (Stefan or Christian become managers and not Claudia) with the help of data. In organizational cultures that consider themselves to be “at eye level”, it can make deep-rooted biases and mechanisms that lead to discrimination or other harmful behaviour discussable and thus changeable.

Conclusion

A workshop on unconscious bias and the rainbow flag on a LinkedIn profile is by no means enough. Organizations that really care about equal opportunities, diversity and thus attracting talent, and that really want to tap into the entire talent pool available, need to look deep inside the organization and critically review their operating system. AI can act as a sensor and make structural shortcomings visible. At the same time, it gives companies the opportunity to design their rules, processes and communication channels fairly, transparently and – this time for real – on an equal footing.

AI in HR: Overcome the fear, embrace the opportunities!

Employee analysis with AI: Make transparent what makes us transparent!

How much transparency is good for people and companies? – In times of Artificial Intelligence, the question of transparency has come back into focus. While we had slowly become accustomed to moving through the analogue and digital world as “transparent people”, the question of how transparent people and processes may, should and must be takes on new relevance due to the increased use of AI.

How to find and promote optimistic and resilient employees

Today’s working world puts the resilience and optimism of many people to the test. Digitalisation and automation require employees to regularly adapt to new technologies and working conditions. This calls not only for flexibility, but also emotional stability. According to the ‘State of the Global Workplace’ report by Gallup (2022), 44% of employees worldwide stated that they are under stress every day.

AI in HR: Overcome the fear, embrace the opportunities!

10 steps to responsible HR work

1. Be aware that AI cannot make decisions.

The question of whether an AI can decide about a person’s professional future becomes obsolete if we realise that the technology cannot make decisions on its own. But it can make us believe that it can. In the end, the AI accesses codified human decisions in order to carry out an action (decision). In other words: What the human doesn’t put in, the machine can’t put out. Or as the authors of ‘Power and Prediction’ put it: ‘Nobody ever lost a job to a robot. They lost a job because of the way someone decided to program a robot.’ If we are aware of this, we can develop a (self-)conscious and responsible approach to AI.

2. Make the ‘why and what for’ the starting point for the use of AI.

Before organisations rush into using new technologies, they should ask themselves what specific problems they want to solve with AI. It makes little sense to collect and analyse huge amounts of data if the objectives and benefits are not clear. These considerations should be based primarily on the needs of the people who are connected to the company in some way, while also taking into account the cost-benefit ratio. With regard to AI-supported personality analysis tools, companies can ask themselves:

What does a bad hire cost me with all the resulting consequences (morale throughout the team, offboarding, job advertisement, new candidate search, onboarding, training phase…)?
What does it cost me in return if I invest in technology that makes bad hires unlikely?

3. Keep working on your culture when using AI.

Algorithms are often so complex that even developers cannot always fully understand them. In order to use the technology in a way that benefits both employees and the organisation as a whole, companies need to work more on their culture – more specifically, on a culture that promotes the ethical and responsible use of technology. Guiding questions could be:

How do we want to work together?
What values characterise our work and teamwork?
How do we define success?
How do we make decisions?
How do we solve conflicts?

It should be a key part of the corporate culture to continuously reflect on existing thought patterns, behaviours and unconscious biases. Employees need time and safe spaces to be able to ask themselves and others critical questions. Open formats in which all employees can participate should be regularly offered specifically on the topic of ‘Dealing with AI’. This allows knowledge and experience to be shared and blind spots in working with AI and data to be recognised at an early stage.

4. Learn to distinguish good data from bad data

The type of data we use to train AI systems is crucial. If we use biased or prejudiced data, the machine will deliver results that further amplify stereotypical attributions and discrimination. We therefore need mandatory quality criteria for training data. Answers to the following questions, among others, provide guidance:

Was the AI trained with biased data or with data that represents the overall average of the population?
In the case of questionnaire-based data collection: Were there any possible incentives for participants to provide false information when gathering the training data?
For language models: Does the AI only analyse individual words and pay attention to correct grammar, or does it try to capture the whole context? (Particularly important with regard to the discriminatory feature ‘native speakers’).

There are many more.

5. Be diverse.

Diversity is more important than ever in times of AI. A diverse workforce brings different experiences and perspectives to the discussion about the ethical use of AI systems. This not only helps to improve the quality of decision-making, but also to recognise and reduce unconscious bias.

6. Take a realistic look at the role of AI in the decision-making process.

A fearless and constructive approach to AI technology requires that such analysis tools are only one of several factors in decision-making processes. They serve as a source of additional information that makes it easier for recruiters, for example, to make a final decision in favour of or against an applicant. It should be clear to everyone that AI predictions are never perfect. AI-based analyses are based on empirical data and scientific principles, but nothing more. In AI-supported personality analyses, as we develop them at Zortify, the error rate is realistically between two and five per cent. If we are aware of this, we can deal with it and develop suitable behaviours for the use of AI in organisations together with the employees who use the technology.

7. Make processes transparent (not data sets).

In personality analyses in particular, it is not only HR managers who need to understand how the AI comes to its results, but also the people affected, such as candidates. The keyword here is ‘Explainable AI’. But how can companies explain something so complex that also contains valuable information, for example for competitors? It remains uncertain what benefit applicants could derive from access to raw data or complex equations, as these are often difficult to understand and are not sufficient on their own to recognise bias in the right context.

The U.S. Association of Computing Machinery has developed a pragmatic approach. It requires that institutions using algorithmic decision-making be able to explain the underlying process of the algorithm and the resulting decisions in non-technical language. The aim is therefore not to disclose technical details in detail, but to improve transparency in two areas: the processes and the results. To do this, people need a deep understanding of how AI gets its results (as an example, take a look at our Zortify certification programme).

The ethical design of processes in dealing with AI begins long before the AI is actually used. Think about when and who you need to involve internally in the process – from the data protection officer to the procurement team to the work council. (A corresponding ‘onboarding package’ from Zortify is in the making. If you haven’t subscribed to our newsletter yet, now would be a good time to find out more soon 😉).

8. Create suitable team roles.

AI technology is too important to be left to just a small group of ‘IT nerds’. Instead, an open discussion about the responsible use of algorithms and data should be initiated across the entire workforce. This requires people at the intersection of IT, business departments, HR and corporate culture who actively drive these discussions forward and document progress. Positions such as ‘AI ethicist’ or ‘human-robot relations manager’ are not abstract figures of a distant future, but are already in demand today.

9. Allow yourself to have healthy doubts: about the AI and about yourself.

Just as we shouldn’t blindly trust the machine, we shouldn’t blindly trust ourselves either. Humans make mistakes, carry biases, are sometimes bad-tempered or overconfident and don’t always make wise decisions. Nonetheless, we can allow ourselves to listen to our instincts and intuition.

AI systems can help us not to be blinded by first impressions. They can make established procedures, such as assessment centres, more objective and fair. Above all, they can make them faster and cheaper, thus creating the freedom to constantly reflect on ourselves and engage in deep interaction with others (such as applicants) so that we are ultimately able to make the best decision.

10. Be honest with yourselves: What can AI do better?

In the discussion about Artificial Intelligence, the potential risks are often emphasised. Without ignoring these, companies should consciously shift their focus and ask themselves when they last had an in-depth discussion about human bias and the subjectivity of recruitment decisions.

The fact is: AI systems can perform some tasks better than humans. In the area of recruitment and employee development, technology can analyse decision-relevant information faster than an entire team ever could. It uncovers aspects that escape the human eye even on second glance, thus contributing to better decisions – better for applicants, better for HR professionals, better for the entire organisation. As a result, it can make a valuable contribution to the search for talent and equip companies to meet the complex challenges of our time.

Employee analysis with AI: Make transparent what makes us transparent!

How to find and promote optimistic and resilient employees

Hybrid work personality: The ‘person first’ approach and the role of AI

AI-based personality assessments can make a significant contribution to optimizing hybrid working environments. A recent survey found that 8 out of 10 employers have lost talent due to the obligation to return to the office, underlining the need for a balanced and personalized approach. ‘Person first’ as an extension of “people first”.