Discover how HR translates fear of the future into future skills, human abilities that AI cannot replace, plus effective learning formats for transfer.
In this article, we focus on how organizations can enable genuine knowledge transfer and ensure that employees are future-proofed for the long term through targeted learning formats and effective AI training.
AI is a hot topic among many organizations, yet people are still feeling a bit torn about it: somewhere between curiosity and uncertainty, between “We gotta get started now” and “What does this mean for me?”
That's exactly what we talked about in our February webinar with L&D expert Ruben Leites, asking: How can we shift our perspective from fear of the future to future skills? And what can HR and L&D do in concrete terms to not only inform people, but truly empower them?
One of the strongest takeaways was that, when it comes to AI, companies are less afraid of AI as a tool and more afraid of uncertainty. This uncertainty is particularly prevalent where communication and guidance are lacking. When change is not clearly defined, speculation arises, and uncertainty can quickly turn into resistance. The bottom line is that discussions about AI revolve primarily around identity, security, and future viability, as opposed to the features themselves.
AI's Strengths
Artificial intelligence really shines when it comes to structure, repetition, and data volumes. One of its biggest strengths is speed. Processes that take people hours or days can be done in seconds: structuring texts, summarizing info, developing variants, analyzing data, or automating routine tasks. This is a huge help, especially for administrative or repetitive tasks.
Added to this is the scalability of AI. While human capacities are naturally limited, AIcan generate almost unlimited output in different variants, languages, orlevels of detail. AI makes it possible to achieve a breadth and depth ofcontent in a short time that would be virtually impossible to achieve manually. This creates new scope for creative and strategic tasks.
A third keyperk is in analysis and pattern recognition. AI is awesome at digging throughbig data, showing correlations, and spotting recurring patterns. It spotstrends, anomalies, and connections that would be easy to miss in everyday life. This is a huge plus when making decisions, especially in complex, data-drivensituations.
AI's Limitations
As powerful as AI is in processing information, its limitations are clear when it comes to meaning and responsibility. AI can generate results, but it cannot take responsibility for those results. It does not evaluate the consequences of its suggestions, it does not bear any liability, and it does not vouch for the impact of its output. This responsibility always remains with humans.
AI also lacks the ability to truly understand context and relevance. It can calculate probabilities and combine patterns, but it does not know why something is significant for a particular organization, team, or specific situation. The question “What does this mean for us?” requires experiential knowledge, values, strategic classification, and situational awareness. Context does not arise from data alone, but from interpretation.
Finally, AI can suggest options, but it cannot make real judgments or responsible decisions. It provides a basis for decision-making, not decisions themselves. Whether a suggestion is sensible, ethically acceptable, strategically wise, or culturally appropriate must still be evaluated by humans. Critical thinking, weighing options, and prioritizing remain deeply human activities.
Therefore, AI provides the material, accelerates and structures it. However, only humans can create meaning through their ability to establish significance, take responsibility, and make conscious decisions. It is precisely this interaction that determines the future viability of organizations.
The Most Important Future Skills
When AI takes over routine tasks, human skills become more important, not less. Our webinar highlighted key soft skills that are becoming increasingly important in the age of AI:
- Contextualization: Classifying output and translating it into meaning
- Critical thinking: Reviewing, questioning, and verifying results
- Judgment and decision-making: Responsibility remains with humans
- Communication: Formulating goals, engaging in dialogue, creating clarity
- Empathy and social skills: Leading teams through change
- Creativity: Combining new ideas, designing, creating meaning
- Ability to learn (learn – unlearn – relearn): Perhaps the most important meta-skill
One particularly exciting aspect is that AI compels us to both name and redefine these competencies. Ruben therefore refers to soft skills as the “hard currency of the future.”
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HR's Key Role
AI-related uncertainty is not purely an IT issue. It is a people, culture, and leadership matter. HR and People & Culture can have a decisive influence in three areas:
1. Realistic assessment instead of extreme views
Neither a cure-all nor evil, AI is a tool that changes the way we work. A clear, realistic picture reduces uncertainty.
2. Transparency and communication
HR does not have to have a perfect answer to every question right away. But HR departments should show that they take the issue seriously, are engaged with it, and are actively shaping the framework.
3. Create learning spaces
People need to try out AI in teams, in everyday life, and with mistakes. It is precisely the joint reflection and questioning of output that builds competence. Teaching soft skills is extremely helpful here, especially for team development.
Why AI Can Actually Promote More Exchange
A common narrative is that “with AI, everyone works on their own and there is less collaboration.” The webinar experience shows the opposite. Where companies create learning spaces, AI often leads to more dialogue.
One example is AI-based travel planning, which suddenly delivered extremely expensive hotel suggestions, not because the AI was “bad,” but because important framework conditions had not been clarified together. It was only through discussion that it became clear which parameters were really relevant.
Key here is that AI only works well in a corporate context if teams explicitly define their goals, standards, and expectations together.
What Really Works in AI Training
Many companies are currently investing heavily in AI training. Basically, this is a good thing, but budget alone doesn't make a difference. It only makes a difference when learning happens in a real work setting, connects to real use cases, and lets people actually apply what they've learned, not just learn it.
Read how TÜV NORD Akademie Inspired 9,000 Participants with Real-World AI Training
Pure tool training tends to be too vague if there's no transfer.
During the webinar, three success factors became particularly clear:
And this is exactly where we step in at 3spin Learning: with soft skills training that doesn't just provide information, but also enables focused repetition, flexible learning whenever and wherever learners want to practice, supported by AI coaches and AI feedback.
Certificates Only if They Reflect Skills
Certifications can be helpful because they provide guidance, demonstrate progress, and promote motivation and commitment. But they lose their value if they only confirm that someone has watched a video. A certificate should show that you can actually apply what you have learned.
At the same time, the webinar emphasized that, especially with soft skills, effectiveness is often better demonstrated through transfer, observation, and feedback than through mere “badges on the wall.”
Read here to find out how our customers and partners TÜV NORD and Zurich Insurance view us:
- How TÜV NORD Akademie Successfully Deploys Immersive Training with VR
- More Realistic than Role-Playing Games: Zurich Uses AI for Leadership and Customer Service Training
Three Specific Recommendations for HR
In conclusion, Ruben set out three very clear priorities that HR managers should address over the next six to twelve months:
- Realistically classify AI and communicate clearly.
- Set up skill mapping: What skills do we have and what skills do we need?
- Strengthen multipliers: Empower managers to create learning spaces and provide guidance.
Especially in times of crisis, companies often cut back on L&D. The reasoning behind this is often simple: if employees are not developed further, a company will lose everything in the long term because its most important asset, its people, will not remain fit for the future..
The Future of Work Is Human
Perhaps the greatest closing statement to emerge from the webinar is:
„The future of work is human, not artificial, but definitely involves AI.“
AI accelerates, analyzes, and scales. But future security comes from both the use of tools and from people who can learn, reflect, communicate, make decisions, and deal with uncertainty. When companies shift their focus from fear to skills, AI becomes not a risk but an enabler for better collaboration, more creativity, and more space for what really matters.