The Four "New Soft Skills" We Need To Thrive In the Age of AI in Recruiting
In today’s rapidly evolving workplace, AI is no longer a futuristic concept but an integral part of how we work, especially in domains like recruiting and HR. As companies dive deeper into AI transformation, the question isn’t just about adopting new tools but developing the right capabilities to thrive alongside them. Drawing on extensive research and conversations with over a hundred companies, I've identified four essential new soft skills—psychological and psychographic capabilities—that every professional, particularly in recruiting, must cultivate to become successful “Superworkers” and “Supermanagers.”
These skills go beyond technical proficiency; they tap into how we think, create, and lead in an AI-augmented world. This article explores these four new soft skills in depth, illuminating how they can empower individuals and organizations to harness AI effectively, increase productivity, and foster innovation.
1. Becoming a Creator, Not Just a Doer
One of the most profound shifts AI brings is in empowerment. AI systems today are programmable with natural language—you simply tell them what you want in English (or any language), and they perform. This turns every user into a potential creator, able to build AI “robots” or workflows tailored to their unique job functions.
Imagine if you could articulate a command to an AI system and save it, automating repetitive tasks that once consumed hours of your time. You’ve effectively created your own personal assistant or robot. But here lies the catch: how many of us feel prepared or empowered to do this? Many professionals remain intimidated or uncertain about wielding this power.
Historically, tools like spreadsheets were the closest many came to programming—complex models, pivot tables, and financial analyses were built by those who mastered Excel’s language. Now, AI lets you program in your own language, iterating and improving solutions on the fly. This democratization of programming means anyone can become a “super worker” by mastering AI prompting and usage.
However, this also means that those who remain execution-oriented and wait for instructions risk falling behind. If your job consists mainly of routine, repeatable tasks—like budgeting, accounts receivable, or generating standard reports—there’s a real chance it could be automated. To stay relevant, you need to be proactive, collaborating with your team or manager to identify opportunities for automation and innovation.
For example, in recruiting and employee experience, many organizations are experimenting with AI to streamline processes such as performance management feedback, reducing the time employees spend writing reviews. We’re working with companies using platforms like GALILEO to build customized AI solutions that don’t depend on waiting for major software vendors like Workday or SAP to add features. This shift empowers individuals and teams to innovate continuously.
2. Challenging Dogma: Rethink Work from First Principles
AI transformation isn’t just about automating existing tasks—it’s about questioning whether those tasks should exist at all. This is the second crucial capability: challenging the dogma or “falling in love with the problem,” as Elon Musk calls it with his “first principles” approach.
Many business processes continue simply because “that’s how we’ve always done it.” They are often slow, clunky, and inefficient, but deeply embedded in the tools and systems companies rely on. As a CEO and innovator, I constantly ask myself why we do things a certain way and whether there’s a better, faster, or smarter approach.
For instance, consider the publishing, podcasting, or survey processes in a company. The software tools involved might be difficult to use or missing features, forcing manual workarounds. While people can learn new tools quickly, changing fundamental systems is harder. That’s why it’s essential to challenge the very foundations of how work gets done.
This mindset is especially important when adopting AI in recruiting. Simply using AI to speed up sending emails or automating routine steps isn’t enough. Sometimes, the best move is to ask: should we be sending so many emails? Should we rely on email at all? Which steps can be eliminated altogether because they no longer add value?
Take the example of designing a self-driving car: the focus isn’t on automating how a driver moves their hands on the wheel but on automating the vehicle’s movement from point A to point B. Similarly, companies need to identify their “steering wheels”—processes or workflows that are relics of old ways and may no longer be necessary.
To foster this kind of thinking, I recommend dedicating time—half a day or a full day—for creative brainstorming sessions. Bring together creative thinkers to challenge why things are done a certain way and whether they should be done at all. In learning and development (L&D), for example, this approach is revolutionizing how organizations manage roles, shifting people from routine content creation to more strategic, impactful work.
3. Cultivating Curiosity and Embracing Iteration
Unlike deterministic software, AI systems do not always respond the same way to identical inputs. They learn, adapt, and sometimes change unexpectedly based on updated data or training. This inherent variability means that what works once might not work the same way the next time.
This is where curiosity becomes a vital soft skill. You need to be inquisitive about why an AI system’s output changes—is it a bug, a data update, or an improvement? Understanding these nuances allows you to troubleshoot, iterate, and refine AI applications continuously.
Curiosity also fosters innovation. The more curious you are, the more likely you are to discover better solutions. I often think of this as the balance between two sides of the brain: the creative, innovative side and the execution-focused, task-oriented side. For me personally, mornings are for creation and exploration, while afternoons are better suited for execution.
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Not everyone is naturally wired for this experimentation. Some people prefer steady, predictable work and may find AI’s evolving nature frustrating. However, in this new world, being willing to experiment, learn from failures, and iterate rapidly is essential.
Historically, many employees waited for others to figure out processes, and they often felt disempowered. Now, with AI tools available at personal and team levels, everyone has the opportunity—and responsibility—to engage in continuous learning and problem-solving.
Eventually, AI tools will become as standard as spreadsheets or email, no longer requiring constant tinkering. But until then, curiosity and iteration are key to mastering AI and driving meaningful change in recruiting and beyond.
4. Becoming a Supermanager: Leading Innovation and Execution
The fourth and perhaps most critical soft skill concerns leadership in the AI era. We’re beginning research on what it means to be a “Supermanager” — someone who can balance encouraging innovation with ensuring execution and results.
Managers today face a new challenge: How much experimentation do you allow your team? Too much, and execution suffers; too little, and innovation stagnates. The best managers find the sweet spot, facilitating creative problem-solving while holding teams accountable for outcomes.
In smaller companies like ours, we encourage people to experiment and bring back ideas. Every incremental innovation is valuable, and the culture supports exploration. But in larger organizations, managers may have less flexibility and more pressure to deliver predictable results.
As a manager, you must decide how to foster creativity: Will you encourage individual experimentation or organize group workshops? Will you sponsor AI learning resources and allocate time for skill development? These decisions are critical for building a workforce capable of thriving with AI.
You don’t need to be the AI guru yourself. Like in software engineering, you can outsource technical tasks but stay involved in design and strategy. The key is to be hands-on in guiding the team’s approach, setting priorities, and fostering a culture of learning and innovation.
This new management capability complements traditional leadership qualities like culture-building, ethics, and customer focus. It adds a “creator” dimension—an essential new skill set for leaders in the AI-driven workplace.
Looking Ahead: Assessing AI Maturity and Collaboration Opportunities
Alongside these soft skills, organizations must also develop frameworks for assessing AI maturity—understanding where they are on the AI adoption curve and how to govern AI initiatives responsibly. Collaborating with partners like Workday, we are working on methodologies, governance models, and surveys to help companies navigate this journey effectively.
If your company is actively implementing AI projects, especially in recruiting or HR, consider engaging with research initiatives or contributing case studies. Sharing experiences and lessons learned accelerates collective understanding and helps build better practices across industries.
Conclusion
The age of AI in recruiting and beyond demands a new set of soft skills—psychological capabilities that empower individuals and leaders to harness AI’s transformative potential. Becoming creators, challenging entrenched work methods, cultivating curiosity, and stepping up as Supermanagers are the keys to thriving in this dynamic environment.
AI is not just about automation or efficiency; it’s about reimagining work itself and enabling people to do more meaningful, innovative, and impactful work. By embracing these four new soft skills, professionals and organizations can unlock unprecedented productivity and creativity, shaping the future of work on their own terms.
Are you ready to become a Superworker or Supermanager in this AI era? The journey begins with mindset and capability—start building yours today.

