System skills that cannot be replaced by AI
In the week of July 9th, US high-tech sector employees lost about 10,000 technical staff. Irony should not be lost to us. Some of the fired items helped build AI that made their work outdated.
Amazon CEO Andrew Jassey confirmed this trend in a statement made in March this year. He said, “As we deploy more generative AI and agents, we should change the way we work. This is expected to reduce the total company's workforce.
The skills that once separated MBAs from the pack (data analysis, process optimization, strategic planning) were performed more efficiently and often effectively by the machine.
This confusion has shattered years of belief. Success comes from models, frameworks, and quantifiable insights. For decades, business schools have taught MBA students to build discounted cash flows, perform regression analyses, and optimize their supply chains. All of these are based on the assumption that smarter analysis equals better decisions.
But as AI takes over the heavyweights of analytics, a new set of business skills is needed. These are skills that cannot be codified by algorithms or outsourced to large-scale language models. Some of them are not even the skills currently taught in most MBA programs.
These are skills required at our hyperconnected, systems-driven age, and are unable to bring “correct” or “best” answers in every technical analysis of the world. They are skills necessary in a world of uncertainty, ambiguity and change, and are not one of the stability. They are skills that help you manage what you can measure, as well as what they can't even see.
Three abilities build this edge: relational, cognitive, and behavior. These abilities are not only resistant, they are uniquely reductively human.
Relational Edge: Listen deeply and build empathy
Executives are advised to speak frequently, accurately and assertively. But this focus overlooks something more transformative by focusing on speaking. It's the power of deep listening. In systems thinking, listening is not passive. Listening is deep and active so listeners can hear not only what is being said, but what is not being said, and build a stronger relationship with them.
Deep listening is the discipline of being completely present with others, the urge to suck judgment, distract, and formulate responses. It means adjusting tone, body language, and emotional undercurrents as much as words, creating space for others to surface thoughts they may not yet fully understand. Deep listeners catch unspoken concerns and subtle clues that others have missed.
Deep Lisning
But deep listening doesn't only apply to social situations. That applies in any situation, whether you're watching your child play alone in nature. The ability to listen – truly listen – requires that you are willing to truly be present in the moment.
In systems thinking, this skill is essential as it helps listeners build empathy and trust with the speaker. It also helps to sense the broader relationship dynamics during play across teams, departments and ecosystems. This is the dynamics of relationships that are not always visible, but shape how people act and respond.
The meta-analysis examined the effects of perceived listening. Researchers found that in the 144 studies they reviewed, speakers they felt asked had stronger workplace relationships and job performance.
Netflix co-founder Reed Hastings practices deep listening with “opposition to agriculture.” By encouraging managers to speak up and listen deeply when they disagree with him, he can avoid mistakes and see new opportunities. He argues that Netflix's 2011 attempt to rebrand the company's DVD-by-mail service through new company Qwickster was because he didn't listen. Despite many people raising serious questions, he succumbed to hell to his new company. As he writes in his book No rules: Netflix and the culture of reinvention “You must be humble, you are interested, and don't forget to listen before you speak and learn before teaching.”
This relational edge extends beyond human dynamics to natural ecosystems. Marine biologist Rachel Carson exemplified the system he thinks through deep listening. She didn't just study chemical data about nature. She listened to the silence. The lack of Birdsong signaled her that fundamentals had shifted in the interconnected web of ecosystems. Her 1962 book Silent SpringCarson weaves different observations of nature and industrial chemicals like DDT into a powerful narrative of environmental collapse. By listening to what the system hadn't told her, the missing sounds — the patterns that traditional analysis had missed. Her insight motivated John F. Kennedy to hit the panel that ultimately led to the formation of the EPA.
Systems thinkers listen more than they hear. They listen in their own body and detect signals from emotions and sensations. This is embodied. Firefighters feel them rather than simply watching or talking about the flames. They are able to detect weak signals in business environments and pay attention to their meaning.
AI can process data, but it cannot sense or sense weak signals.
Cognitive Edge: Think critically and recognize patterns
Executives and MBA students love the framework. They rely on ratios and spreadsheets. Students are flooded with 2×2 matrices and SWOT analysis. These tools simplify complex problems, but we believe they can seduce executives and cleanly analyze and solve complex problems. However, these ratios and spreadsheets mask the assumptions that make up the answer. This is why critical thinking is so important.
Critical thinking is the ability to go outside of habitual models and mental shortcuts. It involves asking basic questions, restructuring the problems, and resisting pressure to reduce complexity early. Thinking critically allows executives to recognize patterns that others may overlook. Detects recurring structures, relationships, or feedback loops across time and domains. Systems thinkers develop this skill by continuously integrating new insights into evolving mental models that scan widely, deeply reflect and evolve.
Systems thinkers resist the rapid simplification caused by questions such as “What is the solution?” Instead, they first ask, “What is the right question?” And by thinking critically, they can see patterns that others have missed.
Think about what happened when traditional analysis failed spectacularly. During the 2008 financial crisis, Wall Street's best analysts missed out on building a systematic risk under their feet. In testimony from a Congressional panel, former Citigroup CEO Charles Prince admitted that he “didn't foresee what would be before us” after the crisis.
Hedge Fund Manager Michael Barry did that. His insights came from not from standard models but from realizing strange patterns. Rising home prices, loose lending practices, and investor satisfaction. He didn't just analyze mortgage bonds. He saw the system – interactions between incentives, behaviors, and structures. That's the cognitive edge. Apply insights across your domain to find out what others are missing.
MIT's Erik Brynjolfsson and Andrew McAfee discuss in their book, The second era of the machine, AI is better within defined tasks, but humans continue to get better with more creative tasks. Analogous reasoning – seeing connections across seemingly unrelated realms – is especially prominent in complex worlds. A machine can sift through a huge amount of data to make connections, but it cannot create meaningful connections that humans can make.
This is the cognitive edge. The ability to identify patterns among weak cues between disciplines, the reasons beyond data, and the ability to question reasons. AI can find patterns in past data, but human thinkers can get a glimpse of possibilities at the edge of what is known.
Behavioral Edge: Accepting uncertainty and adapting to change
Business decisions are made clear through well-defined goals and step-by-step actions that can be taken to them. Executives and business students are encouraged to use the best available data and the most sophisticated data analytics to make decisions about the next step.
This tempts people to fear uncertainty rather than accept it. The pursuit of more data to achieve well-defined goals slows down actions. In a world defined by constant chaos, waiting often means missing the window.
Accepting uncertainty does not mean being paralyzed by a confusing swim or the need for better data. This idea requires executives to build psychological flexibility. This is a trait that requires the ability to focus on the goal while adapting to shift conditions. This is about looking at the short term while focusing on the long term.
The behavioral response to accepting uncertainty is adaptability. When the business environment changes, systems thinkers don't panic. They pause and reflect. These executives are pleased with the change because of their experiments and adjustments. They have no plans.
But these systems thinkers are not skittish. They do not redirect in every part of the new information. Instead, systems thinkers are fixed to a strong sense of purpose and personal values. They maintain a general orientation and still adapt when learning something important and new.
LinkedIn co-founder Reid Hoffman highlights the need for continuous learning and adaptability, especially for founders and entrepreneurs navigating rapidly changing markets. He talks to the learning loop. There, people continue to respond and coordinate to make new information come out. For Hoffman, this ability to adapt in real time is a key marker of success, which he calls “permanent beta.” As he said, “You know things, but you don't know the whole game, so you're paying attention to how the game is changing,” he says, the key is to “never start.”
Systems Thinking Skills
Together, these three edges create a new leadership paradigm. Historically, business skills are based on strong data analytics. Better data meant better answers. Today, AI can analyze data.
Business leaders should focus on the skills they need, especially in a highly confusing environment. Currently, strictness and inference are replaced by sensing, interpretation, and adaptation.
Business leaders need to listen not only to what is being said, but what is not being said. Ask good questions, see connections between seemingly different ideas, and continue to adapt to new and salient information while still being fixed to strong values and sense of purpose.
AI has become a commodity of technical skills. Managing within a messy, nonlinear, often chaotic human system requires a distinctive human edge. These are not just general “soft” leadership skills, but fluid world survival skills.
Major agencies are catching up. Stanford's D.School emphasizes human-centered design. MIT teaches managers to map interdependencies. Companies like Unilever and Google are training leaders in mindfulness and emotional intelligence as well as spreadsheets and strategy decks.
Now, business is running on systems. The skills to navigate complex systems are not only technical, but also unique human beings that AI can perform. To navigate complexity, you need to navigate uncertainty with curiosity rather than fear.
Leaders who flourished in the age of AI do not analyze machines. They surprise them.
More on Systems Thinking: How systems thinkers can avoid bad decisions.
