Practical AI for Everyone

AI is everywhere these days… Headlines hype exciting new tools – but under the surface, there are simmering worries. The good news? Although jobs do evolve – so can you and your work profile.

Since tools like ChatGPT became mainstream, AI stopped being just a pipe dream for techies. It feels real now – for blue- and white-collar workers. For example, nearly two-thirds of workers expect AI to reduce job opportunities. We heard headlines like IBM pausing hiring thousands of back-office roles or Klarna slashing marketing agency spend by 25% “thanks” to AI. So it’s only natural to ask (even if we take the hype with a grain of salt): “Is my job safe?”

I felt it, too. Early on, I anticipated ChatGPT-like tech could handle some aspects of my job – desk research for scouting innovative startups – more efficiently than me. My first reaction could have been fear, maybe trying to ignore it. But I decided to take a “leap of faith” and to double down instead. I convinced the team we needed an AI agent for scouting. We went for it, and honestly? We love it now. It helps us focus more on the aspects where we excel – the human factor.

So, while “Is my job safe?” is a valid starting point, I believe a more powerful question is: “How can I actively use this AI shift to design the right career for me?” That’s what this article is about – intentional career design. It takes a conscious effort: understanding what AI can do, aligning that with your human strengths and interests. To me, this is the most practical article I’ve written so far.

The tools and principles here – incl. a hands-on 4-step self-assessment / “reskilling sprint” – helped me a lot and I hope they’ll help you, too.

Table of Contents

AI at Work: What It Can (and Can’t) Do

Let’s start with a clear picture of what today’s AI – incl. its “generative” (GenAI) and “agentic flavors” – is actually good at in work – and where it still falls short. You’ll see this is less about “Will AI take my job?” and more about “Which tasks can it support – and which are on us?“.

What AI does well (in a nutshell):

• Streamlining repetitive tasks: AI handles structured, repeatable work at scale – e.g. form-filling, writing boilerplate reports etc.
• Processing and summarizing huge amounts of data: It spots patterns we might miss and delivers fast insights – helpful in research, analysis or sifting through documents.
• Supporting decisions with predictions: From churn risks to sales forecasts – AI can provide decent directional input (if trained right), esp. in “narrower” use cases.
• Staying on 24/7 without burnout: It doesn’t tire, doesn’t forget and doesn’t need a coffee break. Good for monitoring or consistency in outputs…

Think of it as a powerful “streamlining engine” for clearly defined tasks where analyzing known factors works well. This explains how models like ChatGPT score in the 90th percentile on the bar exam (law being a structured domain).

Let’s contrast that with AI’s current limits:

• Understand context the way humans do: It doesn’t “get” nuance – it guesses patterns based on training data, which often leads to “hallucinations” or inconsistencies.
• Feel emotions or build trust: It can simulate empathy, but it can’t care. Real human connection, emotional sensing and trust-building? On us.
• Adapt to complex, messy environments: When expectations are vague or conditions shift, AI falters. Human adaptability and critical thinking are hard to imitate.
• Make ethical calls: AI follows rules – it doesn’t grapple with what’s “right” in ambiguous situations. It also can’t take any responsibility. You do.

While AI is vaguely modeled on our “firing neurons”, it completely misses the biochemical and physiological side of human intelligence. These include emotions, intuition, motivation, the complex brain-body connection etc. These factors (or lack thereof) explain the persistent limitations above.

Thus, AI is a potent assistant for specific, narrow tasks, but humans are essential for complex situations requiring real judgment, creativity, empathy and adaptability. These are areas where our value increases, not just “AI gaps”. And recognizing that helps us shift focus: Instead of clinging to tasks AI might do better, we can lean into the strengths only we bring. AI can take care of much of the structured how and what – so we can focus more on the why and what if.

Note that this chapter doesn’t aim to cover every potential or limitation of AI. Check out my pieces on how AI is changing job opportunities or technology deep dives (LLMs, AI agents etc.). That context will also help you use the tool in the next chapter better. Also, AI’s capabilities are a “moving target” and change over time but I help you stay on top of that easily, too.

Thinking in Tasks, Not in Titles

Thinking about AI’s impact feels less overwhelming if you stop viewing your job as one single “thing”. A more helpful approach is seeing your work as a collection of different tasks and activities – your personal “role profile”.

Why this shift matters? Because AI rarely automates an entire job. It typically affects specific tasks within it. Research confirms this. Studies suggest that while few jobs are 100% automatable, over 30% of US workers could have at least 50% of their tasks automated or assisted by GenAI.

Brent Dykes shared a useful framework (in Forbes) called the “Human-AI Collaboration Matrix”. You can use it to categorize tasks based on complexity and need for “human touch” (creativity, empathy, judgment etc. – i.e. areas where humans excel). These are the four “quadrants” (with names hinting at the recommended way to use AI for activities from each “bucket”):

• “Automate” (Low Complexity, Low Human Touch): Simple, routine tasks that AI can often handle independently, freeing up your time. Example: Generating a standard weekly sales summary from existing data.
• “Augment” (High Complexity, Low Human Touch): Challenging tasks where AI can significantly boost your speed or analysis, with you directing. Example: Using AI to quickly identify top complaint themes from thousands of customer reviews.
• “Evaluate” (Low Complexity, High Human Touch): Tasks needing human judgment, values or context, even if technically simple. AI can draft ideas, but you make the final call (as you always should). Example: Deciding the best way to deliver constructive feedback to a sensitive team member.
• “Lead” (High Complexity, High Human Touch): Where your unique human strengths (s. above) are the primary value drivers. AI may support a little as a “thought partner”, but you lead task execution. Example: Developing a brand-new, innovative service based on market insights.

This tool helps you see how AI may interact with different parts of your (dream) job, beyond a simple “yes/no” on automation. Next, I’ll show you how to put this into practice to sharpen your profile.

AI-ready Career Audit: Future-Proof Your Role

Let’s get practical. This is a straightforward method to gain clarity and identify steps to make your career more resilient and rewarding. You can use it for your current role or a target job. Think of it as a proactive design tool – helping you focus your energy, develop relevant skills and shape a role that plays to your strengths and values.

Step 1: List Your Key Tasks

Write down your main (current or desired) job activities. Aim for (typically around) 10 core activities. Be specific – go beyond job titles or vague categories. A project manager, for example, may:

• Write regular status reports to their boss
• Moderate daily team check-ins (agile)
• Negotiate with business partners
• Resolve emerging team conflicts
• Present results to stakeholders
• …

Step 2: Map Each Task to the Matrix

Use the “Human-AI Collaboration Matrix” (Automate, Augment, Evaluate, Lead) from the earlier chapter: Which bucket does each task fall into? For example, “write regular status reports” might land in “Augment”; AI could help streamline cluttered thoughts or accelerate drafting. But be honest about each task’s complexity and how much human judgment or creativity it currently requires.

Step 3: Use Your “Levers” to Position Yourself

Once mapped, your task list reveals options to shape your job or role more intentionally. Use these three strategies as inspiration to guide your next steps:

Strategy 1: Become an Adept “AI Collaborator”

Look at the tasks in the Automate and Augment zones. These are where (Gen)AI can do more of the heavy lifting. Your best move? Learn how to work with it – or at least smartly alongside it. Get familiar with accessible tools like ChatGPT & Co. and use cases relevant to your field. Build some basic prompting skills. Use AI to streamline the repeatable so you can free up time for the more “human-factor” work from Strategy 2.

You’ve probably heard it before: “AI won’t replace you, but someone using AI might.” A bit dramatic? Sure. Still has a point? Absolutely. Research show people who collaborate well with AI tend to be more productive and have better job outlooks.

Strategy 2: Double Down on Your “Human Edge”

Prioritize tasks in the Evaluate and Lead zones. These require skills AI can’t replicate well – and where humans shine. Make intentional space for this kind of work and consider AI as a sidekick, not a stand-in. Take on projects that stretch you and strengthen those muscles over time.

And here’s the bigger picture: The world isn’t short on tough nuts to crack – climate change, cancer, misinfo, pandemics… even cosmic wildcards like gamma-ray bursts. The more we automate the repeatable, the more we can stand on AI’s shoulders to face what really matters: the unsolved, the uncertain, the deeply human. That’s where we’re most needed.

Research shows these types of skills – leadership and social influence, analytical thinking, tech literacy, adaptability, curiosity, creativity etc. – are only growing in demand. I explore them a bit deeper in this article, if you’re curious. A friend of mine likes to say “human is the next big thing.” WDYT?

Strategy 3: Embrace Adaptability & Lifelong Learning

We all know that “change is the only constant” and that’s beyond our control. Let’s do the smart thing and accept what we can’t change. So, your task mix will shift. New tools, new expectations, new roles etc. will emerge – again and again. The WEF predicts that nearly half (!) of the skills we rely on today will change and require retraining over the course of 5 years.

Consider taking relevant online courses (like Andrew Ng’s excellent “AI for Everyone“). Also, keep an eye on new jobs AI is creating: Roles like AI & Machine Learning Specialists, AI Ethicists, Prompt Engineers, AI Strategists & Innovators etc. are growing fast. No worries, you don’t need to become a techie if you don’t want but be aware of the changing field.

Step 4: Shape Your Ideal “Task Mix” with Intent

With so many ideas and options on the table, it’s time to narrow down your target “job profile” and plan your next moves:

• What mix of activities suits your profile best? Which activities are your “home turf” as a human – where is AI more efficient?
• Where can you make smart use of (Gen)AI tools? Where can you “just delegate” to it and where will you “cooperate” with it on tasks?
• Does your current job already fit or can it evolve into that optimized “mix of activities”? Or will you need a new job?
• How (dis)similar is your future role from your current one? Are there any “adjacent” jobs that are less “exposed” to AI changes?
• Which “transferable skills” do you have (or can you develop) to make this transition smoother?

But don’t stop there – also ask yourself: What energizes me? What activities are consistent with my values? Where do I create meaningful impact? Frameworks like “Ikigai” can help you put it all together – connecting what you’re good at, what you love, what the world needs and what you can get paid for. It’s a great way to move toward a role that isn’t just “well-adapted to AI” but also reflects who you want to be.

Quick Real-World Example from My Role

In my work leading a corporate AI innovation program, my tasks include scouting startups (“Augment”), spotting business opportunities (“Evaluate”), building internal and external partnerships and drive change (“Lead”) etc. Startup scouting, a repetitive research task, clearly fell into “Augment” – so I introduced the mentioned AI agent to “help”. That freed up time for these – to me much more interesting – “Evaluate” and “Lead” activities.

Mini Excursus: What If We Didn’t Need Jobs at All?

Now, some may wonder whether the real goal shouldn’t be full automation – eliminating jobs, UBI covering everyone’s basic needs and letting people just do what they love. That’s a compelling vision. And maybe one day, society will move in that direction. But for now, most of us still rely on work to pay the bills – and frankly, not everyone hates their job. That’s the reality this article is written for.

To wrap up your “personal audit”, I recommend ending such exercises with a clear, doable next step. That’s how momentum builds: What’s one small step you could take this week to move toward your ideal task mix? If you want to exchange thoughts on how the AI changes are affecting your domain/role, feel free to get in touch.

In Short: Be the Hammer – Not the Nail

It’s easy to get lost in anxious headlines. But history offers perspective: major tech shifts disrupt – yes – but they also always created new kinds of work. Economist David Autor’s research suggests 85% of employment growth over the past 80 years came from new job categories created by innovation.

Stanford’s Erik Brynjolfsson adds AI is more likely to reshape jobs than replace them, which is why smart organizations augment human talent rather than eliminate it. That’s also why employers and leaders need a realistic view of what AI can (and can’t) do – not just fire people based on some hype-fueled napkin calculations. As this article hopefully shows: reality is not that simple.

That process – understanding AI, “auditing” your role and actively shaping your direction by adapting and learning to work with AI – is what “Upward Dynamism” is all about. If you apply the principles and tools shared here, you may even end up creating an entirely new role for yourself (I kinda did that myself).

So, what about you? Have you tried looking at your job as a task portfolio? What’s “that small change” you want to try this week? Share your thoughts below or reach out to me.

Cheers,
John