From Curiosity to Capability: Learning with AI, not just using it with calm music and truffle eggs at OTAKU in Al Gurm
We’ve hit a turning point.
Today I discovered a lovely little gem in the Al Gurm area of Abu Dhabi – a place I first noticed on Google Maps because each house sits on its own island. Welcome to Otaku: Japanese restaurant by night, international with a Japanese twist at breakfast, and, crucially, open from 7am.
Today’s choice is the waitress’s recommendation: truffle eggs on sourdough with truffle sauce. And if you’re thinking that sounds like too much truffle, you’d be wrong, it was amazing. Only down side for this place with this japanese decor and calm music is no hot chocolate at all, so had to go with the black tea that was ok 7/10.
Anyway back to the AI.
“The future of work won’t be defined by who uses AI fastest - but by who learns with it most effectively.”
For a while, AI felt like a playground, a space for wild experiments, clever prompts, and productivity hacks. But lately, something has shifted. The novelty has worn off, and now the question is no longer “What can AI do?” but “How do we actually work with it?”
We are moving from exploration to integration, and that requires a whole new mindset.
The Wall Everyone Hits
If you have played with AI tools for any length of time, you know the moment I am talking about. You are deep in a creative flow, experimenting with prompts, maybe even getting AI to write some light code, and then suddenly you hit that wall.
The task gets too technical. The experiment feels too complex. And the instinct is to hand it off to a developer or just stop altogether and revert back to your old ways.
But here is the twist: AI is not asking us to code more. It is asking us to learn differently.
Instead of treating AI like a vending machine that spits out answers, what if we saw it as a learning partner, one that explains, questions, and even teaches us as we go?
Ask it to show you the why, not just the what. Let it narrate the process.
That is how you turn curiosity into capability.
A lot of the resistance to AI is not technical. It is emotional. It is the quiet discomfort of feeling like you should already know how this all works.
But AI is not replacing your expertise. It is extending it.
When we shift from “using AI” to “learning with AI,” we move from fear to fluency.
You do not have to be a prompt engineer. You just have to be curious enough to ask, “Can you walk me through that?” or “Explain this like I am new.”
That is the kind of collaboration that builds creative confidence.
AI becomes not just a tool for output, but a partner for growth.
The Middle Management Bottleneck
Interestingly, the biggest obstacle to AI adoption is not the executives or the early adopters. It is the middle layer, the managers.
Leaders see the strategic potential. Individual contributors are eager to experiment. But the middle often lives in a world built on predictability, where change feels risky.
They have built systems that work, and AI feels like a threat to that hard-won stability.
So part of this culture shift is about psychological safety.
We need to create low-risk, high-learning environments for managers, places where they can explore AI use cases without fear of breaking something or looking unprepared.
Once they experience small wins, the mindset flips from “AI might disrupt my team” to “AI might help my team grow.”
That is when change starts to cascade naturally.
If there is one lesson from organisations that are doing this well, it is this:
You do not build an “AI culture” with a memo. You build it through shared discovery.
Start small with one team, one workflow, one experiment.
Celebrate the moments when AI solves a problem, not just the polished outcomes. Share stories. Talk about the process.
Culture does not shift because of one big announcement. It shifts because the small wins start to outnumber the old habits.
The Spectrum of Transformation
Every company needs a full reboot in how it thinks and works with AI. The reality is that most cannot do it all at once, so the path forward has to be iterative adoption that builds towards that transformation over time.
There is a spectrum, and every organisation sits somewhere along it. The goal is to keep moving forward while embedding an AI-first mindset from the start.
Incremental adoption: Use AI to improve existing workflows such as reports, planning, and research. Keep it visible and practical, and anchor every change in faster learning and better decisions.
Hybrid collaboration: Create small AI-focused teams within current structures to explore use cases and share findings. Treat them as internal accelerators that make experimentation normal.
Ground-up innovation: For the bold, launch an AI-first division of an existing department or team that builds from AI-first thinking and brings lessons back to the core business. If structural change is not yet possible, start by rebooting the mindset: test, learn, and integrate those lessons into everyday operations.
Transformation is not a binary switch. It is a layered evolution that begins with mindset and matures through consistent action.
Creating a Culture of Safe Reinvention
The most effective teams share one habit: they remove blockers from everyday work.
The goal is no longer play, the goal is dependable improvement of existing processes.
Make change routine and lightweight. Create a clear path that anyone can follow without waiting for approvals that never arrive.
“People need the authority and permission to reinvent completely, constrained only by time to outcome.”
Create a fast lane
If approval is required then set up a twice a week review that lasts fifteen minutes, decisions only, no slides.
If a change meets the guardrails and shows improvement against the outcome, approve it on the spot.
Publish the decision and the template so the next team can reuse it tomorrow.
Small, safe, continuous changes create momentum.
When people know they can improve the work without waiting, reinvention becomes normal.
Integration, Not Automation
The goal is not to automate humans out of the loop.
It is to create a partnership where AI brings speed and scale, and humans bring empathy and judgment.
When that synergy clicks, something shifts. People stop asking, “What will AI replace?” and start wondering, “What can AI help me build?”
That is when AI stops being a tool and starts being a teammate.
Final Sip ☕️
The real challenge ahead is not technical. It is cultural.
It is about teaching people to see AI not as an endpoint, but as a companion in the creative process.
The organisations that thrive in the next decade will not be the ones who deployed AI fastest.
They will be the ones who learned with it the most deeply.
AI is not here to take your job.
It is here to take your curiosity seriously.