Artificial intelligence is transforming the world of recruitment. Candidates are optimising their profiles using AI, while companies are increasingly relying on automated search and selection processes. But does this development actually lead to better hiring decisions – or does it simply make the processes faster?

In an interview with Rüdiger Schmidt-Sodingen from Opinomic, a Swiss media and communications company, Dr. Lang discusses the opportunities and challenges of artificial intelligence in recruitment.

The discussion goes beyond the increasing use of new technologies and addresses fundamental questions about the future of recruitment consultancy: What role do personal experience and industry knowledge play when algorithms are taking over more and more tasks? How can companies develop the skilled professionals of tomorrow? And why is it becoming increasingly difficult to attract suitable leaders?

Drawing on her many years of experience in life sciences recruitment, Dr. Lang explores these developments and explains why in-depth expertise, personal conversations and human judgement remain indispensable in an increasingly digitalised working world.

The Interview

Dr. Lang, you have been working in recruitment for over 20 years. What has changed?

Above all, the speed and access to candidates. In the past, networks and industry knowledge were essential for identifying skilled professionals. Today, profiles are visible, searches are digitalised, and candidate outreach is increasingly automated.

AI is accelerating this development enormously. What used to take days can now sometimes be done in minutes. Active sourcing has long been standard practice among recruitment agencies. However, finding a profile is far from the same as attracting the right person for a particular role.

You describe an algorithmic arms race in recruitment. What do you mean by that?

We are witnessing AI competing against AI. Candidates use AI to optimise their CVs and cover letters and can submit applications automatically. Companies, in turn, are under pressure to manage the flood of applications through automated screening and matching.

Both sides are stepping up their use of technology. Individual processes are becoming more efficient, but the overall system is not necessarily improving. AI was supposed to make recruitment easier. Instead, it sometimes creates problems that we then try to solve with even more AI.

The number of applications is increasing, but their quality is not necessarily improving. At the same time, the candidate experience is suffering: standardised rejections and, in some cases, no response at all. Companies are struggling with profiles whose reliability has become more difficult to assess due to AI optimisation.

For years, we have promoted the importance of the candidate experience – and now we are partly undermining it ourselves through automation.

If companies can find candidates themselves using LinkedIn and AI, why do they still need headhunters?

A fair question! LinkedIn has made the candidate market more transparent. Companies can find specialists and executives without relying on huge recruitment agency databases. AI makes the search even easier. Active sourcing is no longer a specialised skill known only to recruitment professionals.

However, candidates are also optimising their profiles using AI. Skills are presented strategically, and CVs are tailored to job requirements. Everything looks more professional. But how do you separate the wheat from the chaff?

For me, this is where recruitment consultancy begins: assessing actual skills, experience and motivations for changing jobs rather than simply finding profiles.

Particularly in the life sciences industry, small differences can be decisive. A high matching score reveals very little about whether someone is genuinely qualified for a demanding position.

Suitable candidates also need to be convinced to consider a career move. This requires trust and persuasion.

Candidate searching is increasingly becoming a standardised technical service. The real value of professional recruitment consultancy lies in thorough assessment, market knowledge and the ability to attract the right people for a particular role.

AI promises productivity gains. What does this mean for the next generation of skilled professionals?

Many entry-level tasks are being supported or taken over by AI: research, documentation, data preparation and initial analyses. From a business perspective, this sounds attractive: less effort and faster results. But how will today's entry-level employees become tomorrow's experienced specialists?

Experience is gained through practical work, making mistakes and gradually taking on responsibility – not through education alone. The pharmaceutical and biotechnology industries will continue to need highly qualified scientists. AI can analyse data, but professional judgement and accountability in a regulated environment require expertise and experience.

Companies must therefore ask themselves not only what they can automate today, but also how they will develop the skilled professionals of tomorrow. Otherwise, we risk making savings in the wrong areas.

Many companies complain that they struggle to fill leadership positions. Where does the problem lie?

Leadership is becoming increasingly demanding, while the scope for decision-making is shrinking. Managers are expected to reduce costs, implement changes, motivate employees and achieve ever-higher targets.

International companies, in particular, are experiencing continuous restructuring and shifting priorities. Leaders must stand behind decisions over which they often have very little influence.

As a result, qualified specialists are asking themselves why they should take on such responsibilities. Greater responsibility does not automatically mean greater influence or job satisfaction.

Companies should ask themselves what they genuinely enable their leaders to achieve. An attractive job title and a higher salary are not enough. Those expected to take responsibility need the freedom to act and the trust to make decisions.

What should company management teams do differently when using AI in recruitment?

First, they should clarify which problem they actually want to solve: processing as many applications as possible in the shortest time – or finding and retaining the right employees?

AI can reduce administrative work. That is a major step forward. But efficiency alone is not a measure of quality.

An unfilled key position, a poor hiring decision or the loss of an important specialist can be extremely costly for a company. An automated recruitment process does not change that.

I would like to see a more balanced approach. Not everything needs to be automated to the maximum extent simply because it is technically possible. Instead, we should use the time gained for thorough assessments, personal conversations and sound decisions.

Ultimately, it is not the recruitment process that needs to be convincing, but the hiring decision.