Luxury & Fashion Innovator | Founder & Chief Metaverse Officer at Journey | NEW BOOK out on 01/17: Into The Metaverse | Speaker |Ex: AWS, Magic Leap, HTC | Virtual Fashion & Couture, Gaming, AR, Connected Fashion

Cathy Hackl is a globally recognized tech & gaming executive, futurist, and speaker focused on AI (including multimodal & on-device AI), spatial computing, virtual worlds, next-gen consumer experiences, new commerce models, strategic foresight, and gaming platform strategy. As one of the top tech voices on LinkedIn, she serves as an External Advisor to BCG’s Frontier Tech practice (AI, Quantum, XR, IoT, Web3), and is founder & CEO of Future Dynamics, overseeing her professional speaking, thought leadership, and publishing. She has worked at Amazon Web Services (AI & Simulation Services), Magic Leap, and HTC VIVE, advising Fortune 100 brands like Nike, Walmart, Louis Vuitton, and Estee Lauder on emerging tech and gaming journeys. She’s built large-scale virtual experiences in Roblox and Fortnite, produced virtual concerts, and is an Apple Vision Pro developer.
Named by Newsweek as a Top 25 AI Visionary of 2024 and a Top Latina Women in AI, her accolades also include recognition as one of Ad Age’s Leading Women of 2023, a cover feature for Forbes Latam’s 100 Most Powerful Women 2023, and a spot on the Vogue Business 100 Innovators list—underscoring her profound influence in the tech world.
As a sought-after keynote speaker, she hosted this year’s inaugural AI House at CES, and has spoken at Harvard Business School, MIT, SXSW, Comic-Con, the WEF Annual Meeting in Davos 2023, CES, and more. She hosts Adweek’s TechMagic podcast and is known in tech circles as the Godmother of the Metaverse. Her media appearances span CNBC’s Squawk Box, 60 Minutes, CNN, Good Morning America, GQ, Time, The Economist, Bloomberg, and Vogue Singapore. In 2022, she became the first human to ring NASDAQ’s opening bell physically and in avatar form, doing so live on television.
Hackl has taught at IE Business School and SDA Bocconi, and authored 5 books, including Into the Metaverse: The Essential Guide to the Business Opportunities of the Web3 Era and The Augmented Workforce: How AI, AR, and 5G Will Impact Every Dollar You Make, and Spatial Computing: An AI-Driven Business Revolution. 
Her personal research explores the future of dating & relationships, Gen Alpha & Beta, neural interfaces, BCI, space marketing, and the post-smartphone era. With a deep passion for frontier technology, she continuously evolves, helping Fortune 100 companies strategize and implement AI and emerging tech solutions—solidifying her place as one of the world’s leading tech trailblazers.

Cathy Hackl

What if gaming isn’t just about fun, but the foundation of our digital future?

During the Global Blockchain Show in Abu Dhabi I shared my perspective on how I view gaming as infrastructure. The virtual worlds built through engines like Unity and Unreal are not just experiences. They are the base layer of a new digital economy.

As we move beyond smartphones into wearables and smart glasses, the virtual layer will expand into our physical world. That shift could unlock an entirely new virtual GDP, and Web3 and blockchain may play a critical role in enabling trust and financing this next evolution.

Gaming is no longer just play. It may be the backbone of what comes next.

I shared the stage with my fellow tech pioneers and friends Yat Siu BORGET Sebastien Wissam Younane at the Global Blockchain Show.


#GlobalBlockchainShow #GBS2026 #Gaming #AI #SpatialAI #smartglasses #wearables #MWC26 #GDC #DCBlockchain

I’m honored to join the inaugural cohort of the Semafor World Economy Principals.

This carefully curated and highly influential community brings together global CEOs, policymakers, builders, and innovators who are actively shaping the next chapter of the world economy. Principals are nominated by peers and institutions and selected for their leadership, ideas, and real-world impact. Semafor World Economy, convening in Washington, DC, is the largest gathering of global chief executives in the United States.

At a moment of extraordinary global change, the conversations around technology, AI, and the future of markets matter more than ever. I’m looking forward to joining this exceptional group in Washington, DC this Spring to engage in high-trust discussions about the forces reshaping our economies, industries, and societies.

Grateful to contribute my perspective on AI, spatial computing, physical AI, world models, XR, gaming and the convergence of technologies that are redefining how we live, work, and connect. 

#SemaforWorldEconomy #SWE #AI #SpatialComputing #SpatialAI #TechConvergence #WorldModels #Gaming #XR #keynotespeakers

Helping SMEs boost profits 10x faster with my AI & Automation-as-a-Service agency—turn your business processes into saved time, empowered teams, & increased profits, all without the extra overhead. Link in Bio ↓

There are two ways to be a business leader in 2025:

1. Struggle with inefficient processes. Stagnate.
2. Leverage AI Agents (aiGENTS). Scale 10x faster. 

Most are stuck in the first.

As a leader, you have ambitious goals. But they're out of reach, aren't they? 

The bigger problem?

You're missing out on game-changing opportunities. 

Opportunities to streamline operations, outpace competitors, and attract top talent to fuel your growth.

Yet, when it comes to:

↗ Automating repetitive tasks
↗ Breaking down departmental silos
↗ Achieving rapid, sustainable growth
↗ Reducing reliance on costly vendors

You find:

↗ Your workflows are still painfully manual
↗ Your teams are disconnected and inefficient
↗ Your operational costs are spiraling out of control

The solution? 

Transform your business with AI Agents and workflow optimization.

That's our expertise. 

Our services encompass:

↗ Crafting tailored AI strategies aligned with your business goals
↗ Implementing AI Agents for immediate impact
↗ Streamlining cross-departmental collaboration
↗ Providing ongoing optimization and support

Are you serious about revolutionizing how your business operates? 

Are you ready to scale 10x faster with AI Agents? 

Reach out now to start your journey towards operational excellence and exponential growth. 

→ GO HERE: www.hiteshmahajan.com 

Email: hello@aidapt.co
X: @hitesh_ai​

Hitesh Mahajan

every CEO in the Gulf wants AI.

almost none of them want
to change how they work.

that's the entire problem
in one sentence.

AI won’t transform your business. I will | From AI-Ambition to AI-Native, sprint by sprint.

most companies in MEA aren’t behind on AI because of budget.

they’re behind because they’re waiting for certainty that will never come.

the playbook is the same everywhere: “let’s wait until it’s proven, then we’ll move fast.”

but by the time it’s proven, the window is gone.

the businesses I see winning right now didn’t wait for a perfect business case.

they ran a small deployment, learned something real, and compounded from there.

3 months of cautious observation costs more than 3 weeks of messy experimentation.

the risk isn’t moving too fast. the risk is confusing “careful” with “safe.”

👋🏼 I’m Hitesh. I help MEA businesses go from AI-Ambition to AI-Native at Aidapt. 50+ transformations and counting. Follow for the signal, not the hype.​​​​​​​​​​​​​​​​

Hitesh Mahajan 🚀

CEO @ Aidapt | I design your AI strategy and orchestrate the data foundations, platforms and intelligent systems you need, then build and run them for you in a single AI-first operating model with clear, measurable value

BCG just surveyed 2,360 executives across 16 markets.

The headline: companies plan to double AI spending
in 2026 to 1.7% of revenues.

But here's the number nobody's talking about.

CEOs in the Middle East and Africa are more
confident AI will deliver ROI than CEOs in the US
or UK.

41% of Middle East companies plan to invest
more than $50M in AI this year.
The UK? 24%.

Let that sink in.

Here's my take on why this matters for MEA:

1) The "wait and see" era is dead. 72% of CEOs
globally now say they're the main AI decision maker.
Twice the share from last year. If your CEO isn't
leading AI in your org, you're already behind.

2) 90% of CEOs believe AI agents will deliver
measurable returns this year. They're putting
30%+ of their AI budgets into agentic AI.
This isn't hype anymore. It's line items
on a balance sheet.

3) 60% of CEOs admit they've slowed
implementation because they're scared of
errors and malfunctions. This is the gap
we see every week in MEA. The budget is there.
The conviction is there. The execution capacity
is not.

4) 94% of companies will keep investing even if
AI doesn't pay off this year. That's not optimism.
That's survival instinct. They know the cost of
not doing this is higher than the cost of doing it
imperfectly.

5) Half of all CEOs believe their job is on the
line if AI doesn't work. Half.

The MEA confidence is real. But confidence without
execution is just vibes.

The companies that will win aren't the ones
spending the most on AI.

They're the ones actually turning it on.

P.S. If your CEO is still delegating AI to IT,
send them the BCG AI Radar 2026 report.
Then send them my way.

AI won’t transform your business. I will | Taking your business from AI-Ambition to AI-Native, sprint by sprint.

BCG AI Radar 2026 report

I stole this idea and now use it with every hire.

Best illustration of high agency I've ever seen.

There are 5 levels of work:

1.	"There is a problem."
2.	"There is a problem. Here are some causes."
3.	"Here's the problem. Here are possible solutions."
4.	"Here's the problem, the cause, the options, and the one I'd pick."
5.	"I found it. I fixed it. Just keeping you in the loop."

Here's what I tell every new hire on Day 1:

You start at Level 4. You earn Level 5. Anything below is a conversation we need to have.

High agency isn't just how you tackle problems. It's your entire orientation to work.

(AI is a multiplier for Level 4+ people. An expensive babysitter for everyone else.)

P.S. What level are you operating at right now?

A founder’s appetite for;

eating shit, 
embracing unsexy work, 
using their ears more than their mouth, 
cutting losses quickly, 
and maintaining a tight emotional range…

Will always be the algorithm for success.

AI changes the tools.

It doesn’t change this.

On horseback. Giraffes 20 feet away. 
Ayaan in front not even flinching.

Mt. Kenya does something to you.

No screens. No notifications. Just open sky, green as far as you can see, and two people who remind you what actually matters.

Komal Dawani been on horses before. Ayaan? First time. The kid rode into the wild like he’d done it a hundred times.

(4 years old and already more fearless than most adults I know)

Kenya isn’t just a place. It’s a feeling. The air is thick with something you can’t bottle and can’t explain until you’ve been here.

Grateful doesn’t cover it.

P.S. If you’ve never ridden a horse next to a giraffe in the African bush, put it on the list. Non-negotiable.

No alternative text description for this image

Snowflake just launched Project SnowWork.

The pitch: tell it "build me a board-ready
forecast deck" and it does it. Autonomously.
Multi-step. Grounded in your governed data.

9,100 accounts are already using Snowflake's
AI products. This is the next layer: from
insight to execution. No analyst queue. No
3-week reporting cycle. Just ask and receive.

Here's the thing nobody's talking about.

Most MEA businesses can't use SnowWork yet.
Not because the tech isn't ready.
Because their data isn't.

You can't run autonomous AI workflows on a
warehouse full of broken pipelines, no
semantic layer, and zero governance.

So here's the 3-step path to actually being
ready when SnowWork goes GA:

1) Fix the pipeline. Ingest, transform, model.
If your data is still landing in 14 different
spreadsheets before it hits Snowflake, you
have a plumbing problem, not an AI problem.

2) Turn on Cortex Analyst. Get your team
asking natural language questions against
governed metrics. This is the muscle memory
SnowWork will build on.

3) Build governance now. RBAC, masking
policies, shared business definitions. SnowWork
enforces whatever rules you set. If you set
none, you get autonomous chaos.

The companies that nail these 3 steps in Q2
will be first in line when SnowWork opens up.
Everyone else will watch the demo and wonder
why it doesn't work on their data.

P.S. DM me "DataOS" if you want us to run a
quick audit on where your Snowflake  setup
actually stands. No pitch, just a readout.
Or simply book a discovery call here:

Open article: Aidapt by booknow.aidapt.co

Sainsbury’s put Snowflake at the centre

of their data strategy.

Not as a warehouse.

As the engine for every commercial decision.

Supplier negotiations
Demand forecasting
Personalisation at scale
Margin optimisation

They didn’t just buy a licence and hope.

They embedded a team that knew
exactly what to build and in what order.

Here’s what that looks like in practice:

1.	Map every data workflow that touches revenue
2.	Identify which ones are costing you decisions
3.	Build the Snowflake architecture around those first
4.	Train the teams who will live inside that data daily
5.	Measure outcomes, not just uptime

Most retailers skip steps 1 to 4
and wonder why step 5 looks flat.

The software isn’t the hard part.

The implementation is.

P.S. Sainsbury’s isn’t an outlier.

C&A and John Lewis followed the same playbook.

The pattern is clear.

i've spoken to a dozen people this month with
deep anxiety about going AI-native.

They want to get there.
They're expected to get there.

But they feel like it's a full-time job to do
it on top of their already full-time job.

This is the invisible cost nobody is talking about.

Leaders setting AI adoption mandates without
clearing the runway are creating a quiet crisis.

People feel overwhelmed.
They avoid.
Then leadership wonders why nobody is using it.


The technology gap is real.
It's the second problem.

The capacity gap is the first.

If you're one of these people, you're not behind.
You're not broken.
You're just being asked to do two jobs at once
and told it should feel like one.

(That's not a you problem. That's a systems problem.)

P.S. Are you feeling this right now?


Drop a comment. You're not alone.

I’ve spoken to 40+ retail leaders this year.

Most of them have the same Snowflake story.

They bought the licence.

They got an account manager.

They ran their first queries.

Then nothing happened for 6 months.

Not because Snowflake doesn’t work.

Because buying software and turning it on are
two completely different things.

The vendor’s job ends at the contract.

Your job starts there.

Most retail businesses don’t have the in-house team
to map workflows, build the architecture, and drive adoption across every function.

So the data cloud just sits there.

A very expensive database.

The gap isn’t the technology.

The gap is between buying it and actually using it.

P.S. If your Snowflake environment is doing less
than you expected, I’d genuinely like to know why.

Drop a comment or message me.

Every CEO I talk to in MEA says the same thing:

"We can't find AI talent."

But when I ask what they actually need,
it's never a machine learning engineer.

It's someone who understands their business
well enough to know where AI fits.

The talent gap in MEA isn't technical.
It's translational.

P.S. Who's the person in your company
that "gets" both the business and the tech?
That's your AI champion. Invest in them.

Before any AI investment, ask three questions. 

1) Can we document this process end-to-end right now?  If not, AI will automate confusion. 

2) Does our team trust the output enough to act on it without checking? If not, adoption will fail. 

3) Will this create leverage or just speed? 

Speed on the wrong process is still the wrong process. 

Most AI projects fail at question one. 

They never even get to question three.

Jack Dorsey said it out loud this month.

"These roles are redundant.
AI does it cheaper."

Not restructuring.
Not "evolving our business model."

Redundant. Cheaper.

Block cut 4,000 people.
Oracle is cutting up to 30,000.

Both stocks went up on the announcements.

Investors aren't just accepting this.
They're demanding it.

The question for every MEA CEO:

When your board asks what headcount
AI has made redundant in your business,
what will your answer be?

P.S. "None" is not the right answer.
Not anymore.

my dad ran a business for 41 years.

never had a LinkedIn profile.
never wrote a single post.

built something that supported
3 generations of our family.

sometimes I wonder if we've
overcomplicated what it means
to build something meaningful.

weekend thought:

the best AI use case
I've seen in MEA this month
wasn't in a boardroom.

it was a restaurant manager
in Abu Dhabi who uses ChatGPT
to write his weekly staff schedules.

saves him 3 hours every Sunday.

nobody told him to do it.
nobody trained him.
he just figured it out.

that's the real AI adoption curve.

What I’ve learned after putting Snowflake at the center of 10+ enterprise data projects:

1.	The warehouse is never the problem. The data culture is.

2.	Clean data in Snowflake still means nothing if nobody trusts it.

3.	Most companies are paying for Snowflake and querying Excel sheets for board decks.

4.	The real ROI unlocks when AI agents can query your data warehouse without a human in the loop.

5.	Governance isn’t a Snowflake feature. It’s a people decision that has to happen before you touch the platform.

6.	The teams who move fastest treat Snowflake as infrastructure, not a project.

7.	If your data team and your business team are in separate meetings, you already have a problem.

The tool is the easy part.

The hard part is deciding what you actually want to know.

👋🏼 I’m Hitesh. I help MEA businesses go from AI-Ambition to AI-Native at Aidapt. 50+ transformations and counting. Follow for the signal, not the hype.​​​​​​​​​​​​​​​​

If your answer to "how do you use AI?"
 is drafting emails, writing reports, and smarter googling...


You are at the tip of a profoundly large iceberg.


Work your way down by:

Questioning everything about how you've worked.

↳ Not some things. Everything.
Assuming AI can handle far more than you think.
↳ Give it credit before you take it away.
Giving the technology time and feedback to earn
your trust.
↳ No different than a new employee.

Most people quit at the surface.

The people building real leverage?

They're at the bottom of the iceberg.

P.S. What's the most surprising thing AI has done
for you that you didn't expect?

What companies call AI-native.
And what AI-native actually looks like.

They are not the same list.


What companies call AI-native:

-We use ChatGPT for emails
-We have a chatbot on our website
-Our engineers use Copilot
-We ran an AI workshop last quarter

What an actual AI-native company looks like:

-AI is embedded in every function's workflow. 
Not just the tools team. Every function.

- Humans review exceptions, not every output
-The org is designed assuming AI from day one
-There is a shared intelligence layer
-Leaders can say: if we removed 20% of headcount today, the business would still run

Most companies live in the gap between
these 2 lists.

The ones that close it in the next 18 months
will have a structural advantage that compounds.

The ones that don't will be explaining it
to their boards.

P.S. Honestly, which list does your company
belong to right now?

We reduced claims processing
from 14 days to 2 days.

Dubai. Financial services.
6-person operations team.

Here's the part most AI consultancies
would have gotten wrong:

They would have started with the data.

"Let's build a data warehouse first.
Then we'll add analytics.
Then we'll automate."

That's backwards.

Here's the order that actually works
for MEA mid-market companies:

1) ProductivityOS first.
Automate the workflow before you touch data.
ClickUp for task management.
Make for process automation.
Get the team using structured systems.

This takes 4-6 weeks.
It costs almost nothing.
And it gives you the foundation
everything else depends on.

2) BusinessOS second.
Now that workflows are automated,
embed AI inside the actual operations.
Claims processing. Customer onboarding.
Reporting. Inventory management.

This is where the 14-to-2-day result
came from. AI running inside the workflow,
not as a side tool.

3) DataOS last.
Snowflake Sigma. Data pipelines.
This is the most expensive layer
and the one with the longest payback.

Only deploy it when you have clean
workflows feeding clean data.
Otherwise you're warehousing garbage.

Most consultancies sell DataOS first
because the contracts are bigger.

We deploy ProductivityOS first
because the results are faster.

P.S. Full breakdown in this week's
Turn AI On newsletter. Link in comments.

built a content system this week that plans, writes, edits, and checks quality across 3 channels automatically. 13 skill files. zero new software. just markdown teaching Claude how my business thinks. this is what AI looks like when you stop buying tools and start building systems.

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The Battle

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