AI Adoption Specialist | Fast results, human-centered, no fluff | Keynotes & Advisory

I am a Futurist Rebel at the intersection of technology and humanity, dedicated to guiding business through the transformative power of AI and innovative leadership. With broad expertise in AI, leadership and company organization, I thrive on turning visionary ideas into reality, fostering environments where technology amplifies our human potential.

My journey is fueled by a relentless curiosity and a rebel heart that challenges the status quo, always in pursuit of creating more humane, efficient, and fulfilling workplaces. I believe in a future where business optimization through AI not only enhances performance but also brings us closer to a utopian harmony between machines and humans. This belief is grounded in my deep understanding of the delicate balance between operational efficiency and strategic foresight, paired with a holistic approach to leadership that nurtures both business growth and personal well-being.

Let's embark on this journey to reshape the future of work, making it a wellspring of fulfillment and progress. If you're ready to explore the vast potentials of AI and transformative leadership in creating a culture that champions innovation, integrity, and joy, I invite you to connect with me. Together, we can forge a path towards a future where work enriches our human experience, making every moment count for something greater.

Everything you learned about product development is backwards for AI.

Find a problem. Build a solution. Every business school teaches this. Every startup accelerator preaches it.

It makes perfect sense. Except with AI, it doesn't work.

When OpenAI released ChatGPT, they didn't solve a clear problem. They released fascinating technology and said: "Here. Play with it."

And we did. We chained tools together. We created things we never planned to build. We discovered problems we didn't know existed.

This is what I call Solution-First Innovation. Instead of problem-first, solution-second, AI flips it:

Solution first. Problems emerge through play.

The companies winning at AI aren't the ones with the best strategy documents. They're the ones where people have permission to experiment without needing a business case first.

And every month, the experimentation gap widens.

Traditional product development: find a problem, build a solution.

AI adoption: find some curiosity, let the problems find you. And yes, in the very beginning of AI adoption we might start with the use cases first. But the gold lies within flipping this approach afterwards.

Sure, to get things going, let's tackle your obvious Use Cases and prove value. But long-term this is what keeps your innovation in a small cage.

I explore this deeper on Substack. Just hit the button on my profile.

Follow me for regular guidance through the jungle of AI. Simple. Clear. Applicable.

Damian Nomura

Solution-First Innovation

Your AI champions are building use cases. The
 executive team is bought in. Everyone at the top
 knows the value.

 So why isn't anything landing?

 There are two kinds of stuck in AI adoption. Most
 people confuse them.

 Phase 1: The Easy Kind

 Daily business gets in the way. AI gets
 deprioritized. Everything slows down.

 This is still the easy part. One motivated AI
 champion can build ten use cases a week here. It's
 mostly about commitment and structure.

 Phase 2: The Real Wall

 Your use cases exist but don't touch the ground.

 Executive team believes. AI champions are building.
 But the layers beneath stall.

 Middle management feels squeezed. Pressure from
 above. Resistance from below. The people who actually
  need to use these tools? They're not moving.

 If you're stuck in Phase 1, the solutions are
 tactical.

 If you're stuck in Phase 2, you have a communication
 challenge.

 The technology isn't the bottleneck. The message is.

 This is exactly what I work on in my Executive
 Sparring program. Not AI strategy. The communication
 that creates buy-in.

 8 spots for Q1 2025. Book by December 18th.

Why isn't anything landing?

The technical part of AI adoption has become shockingly simple. I've taken companies from zero to a working pilot in five days.

The tools are ready. The capabilities are there.

So why are most companies still stuck?

Because the hard part isn't technology. It's culture.

It's getting leaders comfortable with "try things and see what happens" as a legitimate strategy. It's creating space for experimentation without requiring justification upfront.

The best AI use cases in your company probably haven't been discovered yet. And they won't be discovered by consultants running workshops. They'll be found by employees playing around who think, "I wonder if..."

That "I wonder if..." is worth more than a hundred use case workshops.

This is the short version. The full breakdown is on my Substack. Link in comments.

And if you're leading AI adoption and feeling stuck, my DMs are open.

Why companies get stuck at AI adoption

Most AI rollouts fail at communication, not technology.

The question that's missing is simple: "What's in it for me?"

 Not what's in it for the company.
 Not what's in it for productivity.

 What's in it for the person who has to change how they work?

 Here's the framework:
 → Less tedious work
 → Fewer interruptions
 → More time for good work
 → Personal upside they can take home

That last one matters more than you think.

When someone takes a skill home and applies it to their own life - that's where real identification with the company happens. You're giving them honest value for their life outside work. Not just extracting productivity.

That's priceless company culture work.

Will everybody pay that back? Maybe not. But the ones that do? They'll make a real difference.

If you want to make AI actually stick in your company, follow me. Your feed will thank you.

Rolling out AI to your organization is like
 telling someone about your vacation.

 You were there. You felt the sun. You tasted the
 food. You remember every moment.

 They're looking at photos on a screen.

 This is the echo chamber problem in AI adoption.

 You believe in this. Your AI champions believe in
 this. You've been building together. You've seen
 what's possible.

 Then you try to roll out to the broader
 organization.

 That's when you hit the outside world.

 The people on the receiving end haven't been on
 the journey with you. They haven't felt the wins.
 They've been doing their jobs the way they've
 always done them.

 And now someone is asking them to change. Again.

 No wonder rollouts stall.

 What's worked for you in bridging this gap?

At some point, looking for an AI use case is like looking for love. The harder you search, the less you find.

 Here's a story that captures this.

 A woman was preparing for a language exam. She ran out of practice tests. So she asked an LLM to generate new ones based on the format.

 Simple problem. Simple solution.

 But then she started using the AI to grade her answers too. She compared its ratings to official guidelines. Same accuracy as a human examiner.

 She set out to generate practice tests. What she accidentally built was two things:
- a personal language tutor
- a test grading system, that could also process hand-writing (she wrote the tests by hand). 

The ladder could potentially lead to a replacement of exam-centers.

 She found a bigger problem through experimentation, not market research. And she could productize this right now.

As a matter of fact, you could steal this idea right now and productize it.

The best AI use cases aren't discovered in workshops. They're stumbled upon by someone curious enough to play.

 What have you discovered by playing that you never intended to build? 

Let me know in the comments.

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