Who Should We Hire? That’s No Longer the First Question.

AI suddenly takes over a large proportion of the tasks previously handled by an assistant.

What does this mean for workforce planning? Fewer employees? A reduced role? Or an opportunity to fundamentally rethink how work is organized?

As artificial intelligence becomes more widely adopted, companies are increasingly questioning which positions they will actually need to fill in the future. But perhaps the discussion is starting in the wrong place.

Before deciding whom to hire, organizations should first understand which tasks will need to be performed in the future – and which skills will actually be required to accomplish them.

This is precisely the shift in perspective that Linh Grethe describes in her conversation with Laura Saloßnick and Benjamin Thomsen from Signature. She leads a fully remote team of around twelve employees and has been exploring how human and technological capabilities can work together effectively.

Her conviction: The future of workforce planning will no longer be defined solely by positions and full-time equivalents. It will begin with tasks, outcomes, and competencies.

An example from Grethe’s own working life illustrates just how tangible this transformation has already become.

Previously, her virtual assistant was responsible for calendar management, preparing information, and various administrative tasks. Today, Grethe estimates that AI agents handle approximately 70 percent of those responsibilities.

However, this does not automatically mean that the human role becomes redundant.

Instead, the nature of the work changes. Her assistant now focuses on tasks that require independent thinking, relationship-building, and initiative rather than the routine processing of information.

This fundamentally changes how organizations should approach their workforce requirements.

“In the future, we should plan around capacity rather than hours or headcount.”

What initially sounds like an organizational adjustment raises a strategic question: Why do companies continue to plan primarily around existing job profiles when the tasks associated with those roles are constantly evolving?

After all, automating a task does not automatically answer the question of what should happen to the role itself.

Linh Grethe describes a pragmatic approach to distributing work between employees, external specialists, and AI agents.

Recurring tasks that can be clearly defined and evaluated may be well suited to AI. When creativity, sensitivity, or independent judgment are required, however, she believes humans still have the advantage.

External specialists, meanwhile, can provide valuable expertise in areas where an organization requires specific knowledge but does not necessarily want to build that capability internally on a permanent basis.

In her own organization, Grethe therefore works not only with permanent employees but also with freelancers who are integrated into the team on a long-term basis. What matters to her is not simply how many hours someone works, but the results that collaboration delivers.

For CEOs and HR leaders, this opens up a new approach to workforce planning.

Not every task needs to be permanently assigned to a fixed position. And not every additional requirement automatically calls for a new hire.

The key question is no longer simply how many people an organization needs, but which skills and capacities are required to achieve its business objectives.

As tasks evolve more rapidly, the demands placed on employees inevitably change as well.

For Linh Grethe, the ability to learn is therefore one of the most important competencies for the future.

Professional expertise remains relevant. But those who rely exclusively on their existing knowledge may quickly reach their limits in an environment shaped by technological change.

What increasingly matters is whether people are willing to acquire new knowledge, challenge established ways of working, and develop solutions independently.

Grethe illustrates how she incorporates this into recruitment through a recently filled sales position on her team. During the selection process, she presented a candidate with the company’s existing sales reporting and asked them to consider how it could be improved.

Her focus was less on finding the perfect solution and more on understanding the candidate’s approach: Can they identify opportunities for improvement? Do they develop their own ideas? How do they approach an unfamiliar challenge?

Practical exercises like these can provide valuable insights into learning behavior and problem-solving abilities.

For evidence-based personnel assessment, this means that competencies must first be clearly defined and then evaluated using appropriate methods. A strong CV or a convincing interview alone is not sufficient.

Particularly when filling key positions, organizations should therefore increasingly ask themselves whether they are paying enough attention to the capabilities that enable people to navigate future change.

As the organization of work changes, so do the demands placed on leaders.

Linh Grethe experiences this every day. Her team operates entirely remotely. Face-to-face meetings are rare, and spontaneous conversations in the hallway are no longer part of everyday working life.

This changes how leaders recognize whether employees need support, feel overwhelmed, or are becoming disengaged.

Her response, however, is not greater control.

“For me, trust is the starting point, not the reward.”

Employees are given clear objectives and the freedom to decide how to achieve them. Regular conversations provide transparency around results, challenges, and support needs.

For Grethe, what matters is not whether someone is constantly online. What matters is what the team achieves together.

At the same time, she has had to learn to communicate expectations more clearly and to recognize that constructive criticism is not incompatible with appreciation.

One of her most important personal insights is therefore:

“Good leadership doesn't mean everyone is always happy with you.”

This is a particularly relevant perspective in a working world where leaders are expected to be empathetic, performance-oriented, flexible, and, ideally, avoid conflict altogether.

Good leadership does not mean meeting every expectation. It means providing direction, enabling accountability, and having the courage to address difficult issues.

While people need trust, feedback, and interpersonal guidance, working with AI agents presents a different set of requirements.

Linh Grethe observes that leaders increasingly need to learn how to define tasks for technological systems just as precisely as they define objectives for their teams.

AI agents do not need emotional recognition. They need clear instructions, appropriate information, and reliable mechanisms for reviewing their outputs.

This creates a new leadership competency: the ability to distinguish between different forms of collaboration and manage them accordingly.

At the same time, responsibility for outcomes remains with people.

Grethe openly discusses her own mistakes when working with AI. When the results are not satisfactory, she reviews her instructions and introduces additional quality-control steps. In some cases, she even configures her agents to ask specific clarifying questions before carrying out a task.

This illustrates a fundamental principle: Automation can reduce the workload, but it cannot replace human accountability for quality.

That makes an organizational culture in which employees can voice concerns, acknowledge mistakes, and ask for support all the more important.

Especially when introducing new technologies, this is not a minor consideration. It is a prerequisite for organizational learning.

Another aspect of Linh Grethe’s experience deserves attention: economic efficiency.

She observes that companies are increasingly purchasing AI applications and software licenses without sufficiently questioning their actual value.

The desire to keep pace with technological developments does not necessarily lead to better results.

Grethe herself has had to learn that seemingly inexpensive AI applications can quickly become costly due to usage-based pricing.

At the same time, she deliberately continues to rely on human expertise, particularly for creative design tasks. In these cases, she values an individual, tailored result more than the fastest technological solution.

For organizations, the implication is clear: Progress is not determined by the number of AI tools being used, but by how effectively they are applied.

Linh Grethe does not recommend launching a comprehensive strategic transformation process as the first step.

Her advice is much more pragmatic: Identify one recurring, time-consuming task and experiment with how AI could provide support.

Then evaluate whether the experiment has actually saved time, improved quality, or created additional capacity.

Only then should the next decision follow: Which tasks should remain with people? Where are new competencies needed? And where will roles or future workforce requirements change?

This creates a shared responsibility for executive management and HR.

Workforce planning can no longer begin only when a position becomes vacant. It must increasingly consider how work is created, how it evolves, and how it can be allocated effectively.

Above all, the conversation with Linh Grethe highlights one thing: The future of work will not be determined by new technologies alone. It will be shaped by leaders who understand their potential while recognizing where human capabilities remain indispensable.

Perhaps the most important question in future workforce planning is therefore no longer: Who do we need to hire?

But rather: What work will still require human expertise in the future – and what kind?