More AI Training Won't Fix This
What We're Reading
The 6 Essential Skills Your Workforce Needs to Keep Pace with AI by CV Viverito, published October 7, 2026, in Harvard Business Review.
The Quick Summary
AI upskilling often leaves employees overwhelmed and organizations disappointed, because companies keep piling on courses and tools. Drawing on Gartner research, the article narrows the focus to six skills in two areas.
Work orchestration (working with AI to get results):
Problem formulation: defining the right problem to hand to AI
Systems thinking: understanding how the parts connect
Strategic foresight: building on systems thinking to anticipate disruption and plan for change
Oversight and governance (making sure AI results are accurate, safe and trustworthy):
AI judgment and risk mitigation: questioning and checking AI work instead of trusting it by default, to catch errors, bias and compliance issues
Human-AI mediation: handling the gray areas where machine logic and human judgment collide, like an exception the AI can't recognize
Ethical leadership: shaping how AI systems are designed and run so they deliver fair, responsible results
Our Take
We were thrilled to see systems thinking on this list. In Harvard Business Review, no less. The article also names a real problem: AI is a moving target. By the time you've trained people on what it can do today, it's doing something new.
Most AI training so far has been what we call horizontal learning: technical skills like logging in and writing a prompt. That has its place. Keeping pace now takes vertical learning, the kind that changes how people think, what they believe and how they behave around AI.
That's where the article stops short. It describes systems thinking mostly as seeing how the front office and the back office connect. Systems thinking also means understanding time delays and feedback, how things move over time and how they reinforce or balance each other. That's what lets you see the unintended consequences of an AI decision before they show up, for your employees and your customers alike. It touches governance and ethics too. If an AI voice answering customer calls isn't right for one company, it probably isn't right for the next one either.
Which leaves the biggest question: who's teaching any of this? Article after article tells us we need adaptability, judgment and systems thinking. Very few say where people actually learn them. Daniel Kahneman's Thinking, Fast and Slow is a useful lens here. Organizations have adopted AI fast, and the same mistakes keep repeating. The skills this article asks for live in slower thinking: pausing, diagnosing and asking what connects to what before you act.
Your Next Move
Look at the AI training your team has already done. How much of it taught a tool, and how much changed how people make decisions? Then, before your next AI rollout, ask who else it touches and what happens to them six months from now.
Keeping pace with AI starts with slowing down long enough to see the system you're changing.
Ready to Fix the Problem Without Becoming the Problem?
In Fixing the Problem Without Becoming the Problem, we'll help you step back and diagnose what's really driving a problem, understand who's involved and what they stand to lose, and ask questions that bring people in.
Join us October 28 at 11 AM CT for this LIVE course. Can't join live? Don't worry, you'll be able to access the recording and all the resources after the session.
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