CTRL+Think: Reclaiming Critical Thought Before It's Automated Away

Introduction

Artificial Intelligence (AI) is everywhere and for many rising professionals, that’s both exciting and disorienting. In most workplaces over the past year, many are being encouraged, if not outright expected, to embrace the AI revolution: use it to move faster, analyze smarter, and scale our work like never before. At plenty of well-known global consulting firms, there’s significant investment and momentum behind AI adoption. The message is clear: learn it, leverage it, lead with it.

But once the workday ends, I shift into an entirely different mindset. As an MBA student at the Northwestern University - Kellogg School of Management, 6:00 PM CST signals a hard pivot, from delivering faster with AI, to slowing down and thinking more deeply without it; rooted in critical thinking, structured problem-solving, and navigating ambiguity. Here, the focus isn’t on how quickly you can generate a slide deck or automate a summary, but on how well you can challenge assumptions, think from first principles, and navigate ambiguity without shortcuts. Straddling these two worlds: the fast-evolving workplace and the traditional academic training ground, has made it clear that finding balance is one of the most important and difficult challenges for the next generation of business leaders. How do we lean into the power of AI without letting it dull the very skills we’re supposed to be sharpening? How do we remain analytical, thoughtful professionals while taking advantage of tools that promise to “think” for us?

In this op-ed-style piece, I’ll share a personal lens on that tension and explore how younger professionals, especially those early in their management careers, can use AI to enhance their work without sacrificing the development of their own strategic judgment. We’ll break down where AI helps, where it hinders, and how to find balance between speed and substance. The goal isn’t to resist AI, but to use it with intention so we don’t lose the mental edge that sets great thinkers and leaders apart.

And to quote one of my favorite short series, The Vince Staples Show:

"This is a work of fiction. Any similarities to actual events are purely coincidental.

(Except they’re not.)"

The “Promise” of AI: Efficiency, Insight, and Career Growth

We’ve all heard the promises loud and clear: AI will supercharge productivity, eliminate busywork, and unlock unprecedented speed and scale in how we work. And in many workplace settings. including consulting, those promises are already being realized. I’ve seen firsthand how generative AI tools can reduce research time, accelerate document creation, and streamline data analysis. In theory and in practice, this has allowed individuals and teams to shift from doing to thinking, automating the tactical so we can focus on the strategic. Whether it’s writing a proposal draft, synthesizing a dataset, or prepping for a client workshop, AI can act as a time-saving co-pilot. The efficiency is real. But so is the creeping concern: If AI becomes the default starting point, how long until it also becomes the endpoint, replacing not just task execution but the thinking behind it?

That’s where caution [and humility] must come in. AI doesn’t “know” anything; it predicts based on patterns. Numerous studies have documented algorithmic bias, data hallucinations, and factual inaccuracies. While AI can be a great accelerant, it doesn’t yet offer context, discernment, or ethical nuance. If we begin to blindly trust AI outputs without questioning the data behind them or the logic beneath them, we risk weakening the very skills we’re trying to strengthen like judgment, reasoning, and synthesis. And that’s a subtle but slippery slope. It’s easy to accept AI-generated answers at face value, especially when they’re framed well. But easy answers can be shallow ones; and real leadership demands depth.

At the same time, we shouldn’t ignore what AI unlocks, especially for those of us early in our careers. AI tools allow us to step into conversations and roles that previously required deep subject matter expertise. By reducing dependency on niche technical knowledge, they help younger professionals operate with more breadth. I’ve used AI to model market entry scenarios, draft summaries of technical reports, and pressure-test ideas across functional domains I otherwise wouldn’t touch. In short, AI can fill gaps not with perfect knowledge, but with good enough scaffolding to help us contribute, ask better questions, and grow faster. This capability can be career-changing. It levels the playing field and provides a sense of confidence and autonomy. When used intentionally, it enables you to show up to meetings more prepared, make smarter recommendations, and learn through iteration. Instead of waiting for subject matter experts or spending hours on foundational research, AI lets you build from a higher starting point.

Still, the constant push to integrate AI can feel overwhelming. There’s a pressure to always be faster, more optimized, and more plugged in. The hype is everywhere! Executives promoting adoption, companies racing to build AI into workflows, and peers touting how they used AI to 10x their productivity. It’s easy to feel like you’re behind if you’re not fully onboard. But the right mindset is balance. Optimism, tempered by skepticism. Adoption, tempered by reflection. The best way forward is not to resist AI or worship it; it’s to partner with it. Let it handle the mechanical, help with the messy, and challenge you to think differently. But never let it replace your critical thinking. Because in a world where AI can produce answers in seconds, the real value lies in knowing which questions to ask, and why.

The Risks: Outsourcing Our Intuition

Despite AI's substantial benefits, its increased use can unintentionally erode essential critical thinking skills. Recent studies by Microsoft and Carnegie Mellon suggest professionals heavily relying on AI tools may experience diminished independent analytical capabilities. The convenience of AI-driven solutions can lead younger managers to accept generated outcomes without rigorous scrutiny, potentially creating blind spots in decision-making.

This issue becomes even more relevant for those in MBA programs or leadership development tracks. These experiences are designed to help professionals learn how to diagnose complex problems, challenge assumptions, and make tough calls with incomplete information. If AI does the heavy lifting, it’s easy to fall into the habit of verifying output instead of generating it from scratch. And that mental habit of going through the reps, of building your strategic “muscle" isn’t one you want to lose early in your career.

Overreliances on AI can also reinforce existing biases and create informational echo chambers. AI models trained on historical data often reproduce the assumptions and blind spots embedded in that data. As a result, using AI to guide strategy without human oversight could mean replicating outdated thinking, missing edge-case risks, or ignoring emerging trends. For a generation of professionals trying to drive innovation and break new ground, that’s a serious concern.

Furthermore, psychological research suggests that frequent reliance on digital tools can lead to “cognitive offloading” where individuals delegate not just tasks but thinking itself to machines. Over time, this can diminish one's ability to synthesize information or draw independent conclusions. For rising professionals in strategic roles, this is particularly risky. Strategic leadership is not about retrieving the right answer, but truly about framing the right question, often in ambiguous contexts with no clear path forward.

There’s also a more subtle risk: loss of ownership. When the tool produces the strategy, the memo, or the analysis, it can be harder to fully own the outcome. You may find yourself defending a position you didn’t fully think through, or implementing a plan you didn’t truly shape. And over time, this passive posture can lead to disengagement or worse, dependency.

The Personal Balancing Act: Using AI Without Losing Yourself

To maximize AI’s benefits without sacrificing critical thinking, rising professionals and managers should treat AI as a partner, not a crutch. That means using it to supplement your thinking, not substitute it. Here are a few guiding principles I’ve picked up as both a consultant and an MBA student:

1. Begin with Curiosity, Not Convenience: Start by developing your own point of view before asking AI for assistance. Sketch a rough hypothesis, outline your assumptions, or build a quick framework. Then use AI to test and refine, not replace, that thinking. When we start with our own ideas, AI becomes a collaborator rather than a shortcut. This habit reinforces independent judgment and helps you build strategic instincts over time. In fast-paced environments, it’s tempting to default to whatever’s easiest, but real growth comes from mental reps, not just mechanical execution.

2. Treat AI Like a Smart but Inexperienced Analyst: AI can deliver fast, well-formatted outputs, but it lacks context, judgment, and often, accuracy. Think of it like a junior team member: helpful, fast, sometimes brilliant, but not infallible. Interrogate its results. Ask: What data is this based on? What’s missing? Would I make this decision without AI’s input? When we challenge AI’s answers the way we would challenge any recommendation, we maintain accountability for the final judgment. This mindset keeps humans in the loop as decision-makers, not just editors.

3. Use Time Saved to Go Deeper, Not Shallower: AI can save hours on execution, but what you do with that time is what matters. Don’t let efficiency become complacency. Reinvest that saved time into more thorough analysis, stakeholder conversations, creative ideation, or simply reflecting more deeply on the strategy. Use AI to accelerate routine work so you can slow down for the things that matter most. Strategic thinking isn’t just about solving problems, it’s about framing them, exploring them, and having the judgment to ask better questions before rushing to answers.

For companies, the takeaway is this: don’t just teach your junior talent to use AI tools - teach them when not to. Build cultures where questioning, skepticism, and deep analysis are rewarded. And for MBA programs, continue emphasizing case studies, Socratic discussion, and real-world ambiguity. That kind of environment is more valuable and critical than ever.

Conclusion: The Thinking That Still Sets Us Apart

In the workplace, AI can feel like a superpower; accelerating analysis, removing roadblocks, and producing polished outputs in record time. In the classroom, we’re reminded of a different truth: that the best decisions start not with answers, but with better questions. Rather than seeing these two worlds as contradictory, we must see them as complementary. The future belongs to professionals who can toggle between both modes: (1) those who can harness technology for speed and scale, but (2) also pause, reflect, and think deeply when it matters most.

AI isn’t going anywhere, and that’s a good thing. It offers immense potential to unlock creativity, democratize access to information, and help us reach new levels of productivity. But it also demands something greater from us: intention. The professionals who will lead the next generation of business aren’t the ones who simply use AI the most. They’re the ones who use it best: with discernment, with discipline, and with a clear understanding of its strengths and its limits.

We are the first generation of professionals with AI in the workplace by our side. That means we carry both opportunity and responsibility. We have the chance to shape how this technology is adopted, how it influences culture, and how it elevates or erodes our thinking. The playbook isn’t written yet. We get to write it. Let’s make it a manual for using AI not to replace human thought, but to sharpen it. Let’s use AI to do more, and think harder. So as you step into your next team meeting, project, or strategic challenge, pause and ask yourself: "Am I using this tool to enhance my judgment, or avoid exercising it?" The answer will define more than just your next task. It may define the kind of leader you become. Because at the end of the day, your most valuable asset isn’t the smartest tool in your tech stack ..... it’s the way you think!

Or, to bring it full circle and with a nod to The Vince Staples Show: "Sometimes it takes a little fiction to get us to confront the truth. What’s exaggerated on screen isn’t far off from what we’re grappling with in real life." A world that’s changing fast, where smart tools are everywhere, but smart thinking still sets you apart.

From a former high school newspaper writer turned consultant + MBA student - This piece was both personal and a blast to write. Thanks for reading!

This article is published for informational purposes and non-commercial use only. The views expressed are solely those of the author and do not represent the opinions of any employer or affiliated organization. Reproduction or redistribution of this content requires express written permission.

References & Data Cited:

• Microsoft, and Carnegie Mellon University. “Generative AI and Human Critical Thinking: A Mixed-Methods Study.” Proceedings of the CHI Conference on Human Factors in Computing Systems, ACM, 2024.

• Schaerer, Matthew, et al. “Algorithm Aversion in Decision-Making: When, Why, and How to Use AI Tools Effectively.” Journal of Behavioral Decision Making, vol. 36, no. 1, 2023

• Zhou, Lili, et al. “AI and the Future of Critical Thinking: Patterns of Use and Overreliance.” ACM Transactions on Computer-Human Interaction, vol. 30, no. 1, Jan. 2024

• Davenport, Thomas H., and Steven Miller. Working with AI: Real Stories of Human-Machine Collaboration. MIT Press, 2022.