The Great Unbundling of Work

Your Job Isn't Disappearing, It's Dissolving.

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Friends,

I had a bit of a rant this week. Too many half truths. And I realised I needed to decipher some of the inertia I see. In and amongst that, my message to you is this: your job isn't disappearing. It's dissolving.

Last week, Deep Research completed in 37 minutes what used to take me three days. Research, synthesis, framing. All there, all accurate. It was better than I could have managed in a week two years ago. Five years ago, I wouldn't have known where to start.

When ChatGPT summarises one of those long research reports more clearly than a senior analyst, I no longer feel unsettled. I barely notice. It's become routine.

That unease I used to have wasn't irrational. It was a warning.

AI will not take your job, and no, someone using AI will not take your job either.

That phrase sounds catchy on panels. It flatters executives. It's not true. Please stop saying it. It's becoming embarrassing. What's actually happening is harder to articulate and more damaging to your sense of professional identity.

AI isn't taking jobs. It's unbundling them.

Every role, from lawyer, teacher, consultant to product manager is being quietly shredded into tasks. Some tasks are being swallowed by machines overnight. Others are being stretched, reimagined, and recombined. The rest? Still deeply, fully human. But now under pressure to justify their existence.

This isn't the robot apocalypse. This isn't a collapse. It's erosion.

And that queasy feeling in your stomach? It's warranted.

McKinsey estimates a third of all workplace tasks may be automated by 2030. But that statistic misses the deeper truth: it's not just tasks disappearing, it's roles being hollowed out from within. And tasks being rebundled together into new roles.

I’m recently being asked to speak to leaders about what this unbundling means for leadership, skills, and capability. Here’s how I explain it:

The Hollow Expert Syndrome

Three months ago, a creative director told me: "I spent twenty years mastering my craft, learning all the skills, all the software, all the layers." Then he watched a 22-year-old intern with Midjourney outproduce his entire team in a single afternoon.

A corporate lawyer using Kira Systems saw her contract review time drop by 60 percent. A copywriter sees headlines she'd labour over for days generated in seconds. The title of this email? Claude helped me. A financial analyst watches modelling tasks that defined his value become one-click operations.

This is the “hollowing out” - when chunks of your expertise suddenly become commodities.

Let's take your job. Break it into components:

• Reading and summarising documents? AI does that better.

• Writing proposals? AI drafts them in seconds.

• Making slides? AI builds the deck.

• Spotting patterns in spreadsheets? AI is your analyst now.

• Thinking clearly about what matters? Still you.

• Knowing what to ask? Still you.

• Convincing others, navigating politics, sensing context? Still you.

AI has cracked the outer shell of most knowledge work. What remains is the messy, judgment-heavy, human-centre and is harder. It's also more valuable - and even more so as we step forward in this age.

But the crisis that no one discusses is that your identity was wrapped up in those tasks. The ones now being automated. The ones that made you feel like an expert.

The jobs aren't disappearing. They're being hollowed out. And the question becomes: what are you filling that space with?

Organisational Paralysis

I've sat in multiple senior team meetings over the last year watching the same scene play out: Executives nodding enthusiastically at AI demos and strategies. Middle managers exchanging panicked glances. Teams clapping politely while mentally updating their resumes.

Everyone feels the pressure to transform. No one knows how to begin.

They install some form of AI. They train the model. Then they stare at it, waiting for productivity to magically appear.

But you can't bolt a Ferrari engine onto a horse cart and call it progress.

Meanwhile, the dissonance grows:

• Execs demanding AI transformation without changing how work happens

• Middle managers caught between pressure from above and resistance from below

• Teams using shadow AI tools (sometimes on their phones or second laptops!) while official initiatives stall

• Vast spending on platforms with minimal change in outcomes

I was told [hearsay!] that a well-known global company spent $12M on AI tools that 87% of their employees never opened. Not once. They didn’t know how or why.

The organisational pain is real, and it results from a fundamental disconnect between technology capabilities and human readiness.

A New Process for Staying Relevant

This is the part most companies get catastrophically wrong.

You need a new process. One that starts with humans, not algorithms. This is where I recommend you start. You yourself, or with your teams. You don’t need a template. You can just write it down, old school style on your Pukka pad with a Bic Biro.

1. Monday: Deconstruct the job into tasks

   • List every activity in your current role

   • Estimate hours spent on each weekly

   • Identify which ones create genuine value versus busywork

2. Tuesday: Classify each task

   • AI can do it entirely (delegate immediately)

   • AI can help significantly (augment now)

   • Only humans can do it (double down here)

3. Wednesday: Rebuild the role

   • Cut what machines do better without apology

   • Redirect those hours to high-judgment work

   • Measure new allocation against business outcomes

4. Thursday: Design new workflows

   • Document exactly how work will flow

   • Create clear handoffs between human and AI

   • Build feedback loops to improve both sides

5. Friday: Address resistance points

   • Identify emotional barriers to adoption

   • Create psychological safety for experimentation

   • Set concrete metrics for the new approach

This isn't a theoretical exercise. It's Monday-Friday practical work that prevents obsolescence. And it must be repeated quarterly as both AI capabilities and human skills evolve. 20 minutes a day for one week to try and stay relevant.

The Middle Manager's Dilemma

If you're a manager right now, you're feeling this acutely. Don’t tell me I’m wrong.

You're being asked to implement AI transformation. Your teams are resistant, confused, or secretly ahead of you. Your own role is being hollowed out from both directions. What nobody tells you is this: middle management is ground zero for AI disruption.

You've built a career on:

• Information gatekeeping (now automated)

• Process management (now streamlined)

• Report creation (now generated)

• Team coordination (still human, but changing)

For example, a retail manager in the UK that I spoke with saw scheduling and reporting automated in 2 months, leaving them questioning their entire value proposition. They had been promoted to do that very job!

Your options?

1. Desperately protect the status quo (and become obsolete)

2. Become a pure executioner of AI strategy (and limit your growth)

3. Reimagine your role as a capability builder (and thrive)

The third path is hardest. It's also the only sustainable one.

When you get back to the office this week, take your calendar from last week. Highlight everything you did that AI could now do. That's your vulnerability map.

SuperSkills: The Human Advantage

AI isn't your enemy. Your real risk is irrelevance.

The antidote isn't more software. It's more capability.

As you know I’m calling them SuperSkills. And they're not soft. They're the new survival skills.

These uniquely human capabilities will define the next decade of work, the abilities that machines can't replicate because they require complex judgment, ethical reasoning, creative intuition, and social intelligence.

I'll be sharing the complete SuperSkills framework soon, but it centres on one core truth: in a world where information processing is cheap, human wisdom becomes invaluable, especially where knowledge is no longer power.

These are not optional add-ons to technical expertise. They are the new foundations of professional relevance. In a world of infinite tools, your human edge is what can't be replicated.

The Resistance Patterns (And How to Break Them)

I won’t be surprised to see people mourning their professional identities. Twenty years of expertise are suddenly rendered partially obsolete, which is why people are lost.

Most tech discussions miss this emotional dimension of transformation. Transformation is not just about tasks. It's about who we thought we were.

I see five distinct patterns of resistance, each requiring a different approach:

The Denier: "This won't affect my industry." Real Example: A senior accountant insisted AI couldn't touch tax work until he was shown how ChatGPT had reduced a 4-hour tax assessment to 20 minutes. Create a side-by-side comparison of their current work process versus an AI-augmented version. The gap must be visceral, not theoretical.

The Perfectionist: "AI makes mistakes, so it's useless." Real Example: A legal team rejected an AI contract review because it missed a clause, ignoring that humans miss clauses 4x more frequently. Run parallel processes (human-only vs. human+AI) for two weeks with error tracking. Let data challenge the perfectionist narrative.

The Identity Defender: "Real professionals don't use shortcuts." Real Example: A creative director refused AI tools, calling them "cheat codes" until his team was consistently outbid by agencies using generative design. Connect them with respected peers in their field who are using AI. External validation from those they admire breaks the identity lock.

The Overwhelmed: "I'll learn it later when things settle down." Real Example: A marketing VP kept delaying AI training until "after the big campaign", campaign after campaign. Create a 15-minute daily "AI dojo" focused on one narrow use case. Make it absurdly small to overcome the overwhelm.

The Tool Collector: "I watch all the TikTok videos about AI and I've installed and tried 17 AI apps!" Real Example: A product team bought seven AI platforms but couldn't show a single shipping feature that benefited from them. Institute a simple "show your work" ritual where teams must demonstrate measurable improvements, not just tool adoption.

Each pattern feels like protection, but each actually accelerates irrelevance. The most dangerous response isn't resistance. It's performative adoption. Installing tools without changing how you think, talking about AI while working exactly as before, nodding along in meetings while privately hoping it all goes away.

What Progress Actually Looks Like

The uncomfortable truth is that most companies don't want transformation. They want the feeling of transformation.

So they buy the platform. They make a steering group. They clap for the keynote.

But when you peek inside? Same workflows. Same habits. Same fears.

Meanwhile, someone in your company, maybe a new hire or a junior employee, has quietly built a faster, better version of the process using AI. In Notion. In Airtable. On her own, thinking it’s normal. The best way, not just a new way.

And that's where the real transformation starts. This is the new normal. You need the new mavens. It doesn’t matter what age they are. You need the ones who can think strategically, have a mindset that is open to change and can execute - and make people uncomfortable at their ability. These are the leaders of the future.

I’ve seen someone half my age rebuild an entire financial modelling system using AI and Zapier in Google Sheets. The old process took 10+ people and three weeks. His takes one person and four hours.

That's not incremental change. That's reinvention.

The question for leaders: are you spotting these pockets of innovation, or suffocating them? Agency and ownership need to sit with teams, not just transformation teams. Everyone's job is different, and everyone's job will be different. HR and transformation teams can provide the guard rails, but ultimately, everyone needs to own their future.

A Hypothesis for the Next Decade

The future belongs to organisations that treat human capability like infrastructure.

Not perks. Not workshops. Core systems of learning, resilience, adaptation.

Because here's my bet:

• The companies that invest in making humans more human will move faster

• Their people will solve more interesting problems

• Their customers will feel the difference in every interaction

• And their cultures won't collapse from change fatigue

Everyone else will still be clapping while their relevance slowly dissolves.

If you are in transition

If your role feels unsteady, start here:

• Stop asking what tool to learn. Start asking what part of your work no longer adds value.

• Break your role into tasks. See what can go. Focus on what must grow.

• Invest in what machines cannot do: curiosity, context, clarity, and judgement.

• Adjust regularly.

• If your workflow has not changed in six months, neither have you.

• Stay close to people who are moving forward. Share.

• Momentum spreads.

• Start small. But start.

This is your moment.

Not to compete with AI, but to complement it. Not to copy what's being done, but to invent what's next. Let's not waste this time in history pretending the old ways still work. Let's build something more human. And more powerful.

Try my weekly reset this Monday. Then reply to me and share what you're dropping and what you're building instead. I’d love to hear some examples that perhaps I could use in my book.

Stay Curious - and don’t forget to be amazing,

Rahim

PS. I’m now accepting keynotes on SuperSkills for Q3/Q4. Email me if you are serious about hiring me to deliver a 60-minute session.

Here are my recommendations for this week:

One of the best tools to provide excellent reading and articles for your week is Refind. It’s a great tool for keeping ahead with “brain food” relevant to you and providing serendipity for some excellent articles that you may have missed. You can dip in and sign up for weekly, daily or something in between - what’s guaranteed is that the algorithm sends you only the best articles in your chosen area. It’s also free. Highly recommended. Sign up.

Now

1. Something is broken in how we think about how we are facing this AI world - While we drown in AI buzzwords and corporate theatre, real transformation stalls. Companies form committees and schedule "vision sessions" instead of building. Meanwhile, quiet innovators ship actual products without fanfare. We've seen this pattern before with social, mobile, and the internet. Soon, the delayers will wonder how they fell behind.

2. I’m a LinkedIn Executive. I See the Bottom Rung of the Career Ladder Breaking. AI threatens entry-level jobs as automation takes over traditional starting roles in tech, law, and customer service. College graduate unemployment is rising faster than average. Companies must redesign junior positions with higher-level tasks AI can't handle, ensuring young workers gain valuable experience despite technological disruption.

3. Extending Minds with Generative AI - As human-AI collaborations become the norm, we should remind ourselves that it is our basic nature to build hybrid thinking systems – ones that fluidly incorporate non-biological resources. Recognizing this invites us to change the way we think about both the threats and promises of the coming age. In this Nature paper, Andy Clark reframes anxiety about AI by challenging the idea that cognition is confined to the brain. He argues humans are "cognitive hybrids" who naturally integrate external tools into thinking processes. From ancient writing to modern AI, technology doesn't replace human abilities but redistributes cognitive labour across biological and technological networks.

4. I went to a ‘longevity doctor’ to find out how to biohack my health and live forever - This journalist visited "The Longevity Doctor" clinic in London to experience the £6,000 "longevity medicine" trend. Tests included 150+ biomarkers, biological age assessment, glucose monitoring, body composition, bone density scans, and fitness tests. Despite initial health anxiety over test results, she discovered her biological age was 30.46, 7.58 years younger than her chronological age of 38, outperforming 79% of peers. The biggest revelation was her poor upper body strength, requiring twice-weekly strength training to prevent muscle mass decline (3-8% per decade after age 30). Research shows loneliness has mortality risks equivalent to smoking 15 cigarettes daily.

5. The Case for the Scandinavian Sleep Method - If sharing a bed (and a blanket) with your partner is becoming untenable, consider a duvet divorce. I’m trying this. Mrs H likes it a whole 2 degrees warmer in our room.

Next

1. Official Lean AI Company Playbook - Step-by-step guide and everything you need to scale using AI while staying lean

2. Is Mubi Really Worth $1 Billion? Inside Efe Cakarel’s Plan to Make the Global Streamer Cooler Than A24

3. What Sam Altman Told OpenAI About the Secret Device He’s Making With Jony Ive - The idea is a ‘chance to do the biggest thing we’ve ever done as a company here,’ Altman told OpenAI employees. Basically an iPod Shuffle around your neck that records you and you can call upon.

4. Anthropic’s new Claude 4 AI models can reason over many steps - Claude Opus 4 and Claude Sonnet 4, part of Anthropic’s new Claude 4 family of models, can analyze large datasets, execute long-horizon tasks, and take complex actions, according to the company. Both models were tuned to perform well on programming tasks, Anthropic says, making them well-suited for writing and editing code.

5. Why Apple Still Hasn’t Cracked AI - Insiders say continued failure to get artificial intelligence right threatens everything from the iPhone’s dominance to plans for robots and other futuristic products.

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