Introduction

So I work for Kickstart Innovation as well as Swiss AI Weeks and I see some familiar faces here like raise your hand if you were part of the hackathon in Zurich last year.

There you go.

Yes, few people here.

And Aniko works with us and Aniko, thank you so much for like putting in a lot of work to make this meetups happen.

So I think this is the second one and it proves to be very interesting.

thing.

Davos in Two Moods: Geopolitics vs. AI Optimism

This is going to be slightly different talk in the sense that what I would like to do,

I would like to share a little bit of what happened in Davos last week, which was crazy

and packed and overwhelming.

And one thing like that I have experienced is there were two sides

of Davos, right?

There was one which was quite depressing, if you would listen to all the

the geopolitical conversations and where we are headed as humanity you know you would think that

in this age we will not have these conversations and how everything that we worked for for the last

like you know almost 100 years to be more united to be more globalized is going completely like

opposite ways and there was the other doubles where it was a lot of excitement it was a lot of

like hype it was a lot of a lot of talks around innovation and what AI can do and it was interesting

thing to like see and in one of the panels they said you know it would be so great if we could

merge this to two tracks to take a little bit of too much of an excitement oh I have to keep an eye

on this to take a little bit of too much of an excitement to the the dark side and the other way

around now so we started the new year right like I wanted just to like ask a couple a couple of

of questions.

A Quick Thought Experiment: If Generative AI Disappeared Tomorrow

So imagine you wake up tomorrow and ChatGPT does not exist.

Perplexity does not

exist.

Clot does not exist.

Feels a little bit surreal, right?

And if we think about it,

it has been only a few years.

And if we think about it that in the first year, people were

quite reluctant and scared to touch the technology.

Just think about it, how fast that exists.

now if two years ago somebody would tell you that your half of your team can be

virtual agents what would be your reaction actually that was one of the

questions that I would ask in my workshops a couple of years ago like

imagine in some point in the future your team is half human and half agents and

people would have this big eyes and now you're all looking at me like well yeah

Yeah, of course, Tata just showed a lot of agents.

Marco was just showing what you can do with the agents.

And just to put in perspective how quick things change

and how we take it as normal.

What Davos Highlighted About AI Right Now

So a few things that were happening in Davos.

Record Investment—But Elusive ROI

Let's start with the fact of how much money still goes into AI.

who can tell me how many zeros is in a trillion 12 yes correct so by 2025 the

whole investment into AI reached 1 .5 trillion I just let's think about it now

okay fantastic wonderful and but let's look at it what have we achieved over 60

160 % companies are failing to show the tangible ROI.

Of course, we have seen great demos right here.

And they were showing all these automations

and wonderful things.

However, the large companies are still

failing to deliver the ROI.

This was one of the big topics that has been discussed.

Last year, there was a big MIT report

that came out that also cited some numbers that 95 %

of the companies are failing to show the ROI

and what should be done about it.

A lot of large companies in the U .S.

and in many other places

actually scrapped their AI initiatives

because after a while they saw that this was a destruction,

that they invested a lot of money and then they scrapped it.

So this was a big topic.

From “AI Tourists” to “AI Leaders”

The other topic, I liked it.

Have you heard about this definition,

AI tourists versus AI leaders?

So this was something that has been brought by the CEO of the Accenture,

where she started explaining that,

okay, there are two groups of companies.

There are some which are AI tourists.

You know, they love inside the company.

You see so many tools.

You try it out.

You come to work every week and you say,

oh my God, have you heard about this?

Let's try this out.

The next week, something else comes out.

Have you heard about this?

Let's try this out.

You have plenty of pilots are running

and none of them leave sandbox.

Does this sound familiar?

Like raise your hand if this sounds familiar,

If you've experienced it, yes, quite a lot.

And then AI leaders, where they call them the AI natives.

And these are the companies that, so to say,

they migrated, they immigrated to AI.

So they have passed the pilots, they

have put them into the production,

and they actually can see already some tangible results.

The AI Tsunami and the Impact on Jobs

So AI tsunami is coming.

I think I'm not telling anything new,

but the numbers are already quite big so 40 % of the global jobs and 60 % in the

advanced economies and this is mostly concerning the junior roles that junior

roles are being eliminated being transformed and entry -level in eventually

well and I don't know are we talking months are we talking years but the

entry -level work is is going away something that this was Jensen has come

Sovereign AI and the Geopolitics of Tech Supply

come up with this definition of six layer.

So in conjunction with all of the talks around sovereignty.

And obviously, that ties to all the geopolitical situations.

If we look into the tech stock now,

where is the most AI tech stock is coming from?

The US and China, right?

Okay, there is Mistral in France,

which is like, you know, like, okay,

there were initiatives in the Middle East

that didn't quite take off,

but there's going to be a lot of investment

into the sovereign AI,

where countries like India, Singapore, and so on

will be investing a lot in AI.

Well, you know that Switzerland has its own Apertus,

which was the core of the Swiss AI Weeks,

and the hackathon,

those of you who were at our hackathon last year,

you know that a lot of the solutions

we were testing for the developers

to build on Apertus.

So something definitely to pay attention to.

to.

The Energy Cost: Data Centers and Electricity Demand

The other thing is the huge amount of the electricity.

So right now, the data centers are

going to use 1 ,200 terawatt by 2035.

And just to sort of put this into perspective of like

to say, what is this?

So the whole country of Japan, which includes everything,

which includes its infrastructure, its people,

and so on and it's a country of like over 100 million people 125 million

people they are using between 900 and thousand so again right like that was a

big topic of what is the future of the data centers can we redesign the data

center so they are green so they are different but a huge topic and then the

From Human-in-the-Loop to Human-in-the-Lead

last one IP I picked I picked six here the last one is this human in the loop

versus human in the lead so up until now a lot of AI conversations is happening

okay I am human in the loop in other words AI does something and the human is

still there who is reviewing who is approving who is doing that that is at

least the reality in in my world and we have not yet moved into the human in the

loop but the idea is when you are human in the loop you become a bottleneck for

for the AI, because AI moves much faster than we humans.

So then the future is going to be the human in the lead

where the human essentially says,

this is my business trajectory, this is my roadmap,

this is my decision, and then the AI goes and builds it.

So in other words, you have a lot more

value creation mindset.

Okay, still with me?

How Organizations Are Restructuring for AI

The Shift from a Pyramid to a “Diamond” Org Structure

so then this is something that already came out last year on how organizations are changing this

is the traditional org structure that we are all used to where at the bottom you have the junior

staff in the middle you have USB have team leads you have management and on the top you have the

executives and this is the diamond structure which is the new setup that is coming about and I just

talked about it where at the bottom you barely have any juniors and interestingly and at the

top you almost don't have like a lot of like leadership but in the middle these are AI enabled

managers these are AI enabled employees which are managing who are managing the agents who are

setting the direction and in other words who are the human in the lead and then I wanted to share

some of the concrete examples because sometimes it just stays very theoretical

and these are some things that have already happened last year.

Concrete Examples: Nike, Moderna, and Cisco

So around November and

Tata you've worked for you being coming from Nike maybe even have some more insights into this that

in November Nike did complete restructuring and they eliminate CTO and chief commercial

commercial office roles, and they're moving them under the operations.

Now you would ask me why,

and the logic being here, and I would like to focus on the CTO role in particular, where

historically the IT departments are always sitting separate, right?

These are the departments which

is, okay, you have operations, you have growth, and then you have IT.

And now not anymore, because

Because data, digital, digital transformation, and AI is becoming the core of the organizational value.

And they have merged this.

So it's not anymore a back office function.

Then I have another example which is different, and this is Moderna.

Also happened at the beginning of the last year, where Moderna actually hired a chief people officer.

but that person is chief people officer

and chief digital officer.

Now, okay, again, we think about it, why?

And the thought here is that technology moves

a lot faster than HR teams.

And you may have already your technology a lot faster,

but you are lagging behind by educating

and upskilling your employees.

And by merging these two departments,

they want to make sure that this stays

like Align.

So in other words, you have your employees being upskilled to the technology

that you are using.

And some interesting things that Moderna did is that, so this was at the

beginning of last year, and I'm sure now they've gone quite a lot further.

So as soon as they

introduced company -wide GPT, they actually developed 3 ,000 custom agents, and these agents

that deployed immediately into the operations

so that they can facilitate every task.

And this already became the upskilling

like on the hands -on on the job.

And a slightly different example

where some companies don't say we merge the departments,

but they say, okay, well, we need a different approach.

And Cisco is one of them where they created an AI hub.

And this is the unit which is connected

to all the units in the organization,

and they keep a pulse on everything what is happening.

So there's not one right model or one size fits it all.

What Actually Works: Operating Model, Teams, and Workflow Redesign

The message here is that the way organizations

are set up now, it doesn't work anymore,

and it needs to be changed.

And what works and what already comes out

from the experiment is function by function approach

is just not working anymore.

And teams, the smaller teams,

the more cross -functional teams,

the teams which are working on concrete outputs,

this is what is working.

You heard obviously quite a lot about thinking

and redesigning workflows and processes.

So it's not about taking AI and slapping it

on what already exists, but it's rather,

this is an opportunity to rethink each one of the processes

and re -imagine it and then re -revamp them.

And then another interesting thing is,

Why Smaller Companies Can Move Faster

it always used to be that the startups are the ones

who are looking up to the large corporates

and okay, learning from them,

and now it's the other way around.

Because the smaller companies are the ones,

they don't have the legacy systems,

they don't have the constraints,

they don't have the bureaucracy,

and they can move very fast.

They can have ARR of over 100 million

with only 30 30 people teams right and the large companies are starting to look

on the small ones so if you are working for a small company right now take it as

a big advantage and if you are raising money or pitching to like a corporates

use that again to your advantage because that is something that you can position

like hey you can actually learn from us because we can do this much faster let's

see what else we have here okay and a couple of words on the about 60 % of the

The Chief AI Officer: Role, Skills, and Positioning

the companies in uh in europe already have a ai lead or chief ai officer or a role that is working

on the ai and here are a few like snippets right like if you think about it so who is this person

the what is the role of the what is the archetype of a chief ai officer um think of that person as

the as a very strong networker because these are the people who need to manage up and who need to

manage down these are the people who need to understand your business

trajectory that your strategy and your value because they need to be able to

bring this down to the processes they don't necessarily need to be very

technical people however when they are in the room with engineers they need to

speak the lingo of the developers and when they are in the room with that with

with the board, they need to be able to speak the lingo of the board, right?

Very good with understanding the company bureaucracy.

Some people say like, oh yeah, we brought an entrepreneur because it takes an entrepreneur

to know how to fail and running AI experiments is a lot about running an experiment and failing.

So that's something that, you know, also interesting like, you know, that comes up.

and in terms of the you know these are already details but in terms of the who

they should report they should really have a very visible role within the

organization either they need to have a strong sponsor on the sea level or they

need to be reporting to CEO or the CEO so in other words this role is very very

critical but it is by no means a very only a very technical person or only

like when it's is this interesting interesting hybrid and then you know

What to Do Next: Audit, Ownership, and an AI-Embedded Strategy

like okay so you have all this and like what do you do right so how do we like

leave this room and what do you do from there so something that Tata mentioned

about is that understanding where your organization stands and the way like you

know so where are you are you an AI tourist are you AI leader or are you AI

visitor so that first step is incredibly important to have a self -awareness and

that starts with an audit whether it's an audit that you conduct internally

within your organization whether you conduct it with an external partner

that's something that you I would highly recommend to have that and then yeah

have that AI person it doesn't matter what title you give to that person it's

AI officer or AI lead or you name it but this is the person who loves the

the technology, who is not afraid to fail,

who wants to go out there and network

and really can build the relationships with people

and push things forward.

If we had more time, I would have shown you

a couple of very interesting case studies

that, but maybe like for the later time.

Yeah, I mentioned, I understand you're a tourist

or you are a leader, and by all means,

make sure that AI is not leaving,

like this is your strategy, this is your business plan,

and this is your AI roadmap.

no your AI roadmap needs to be part of your business strategy and part of part

of your core core offering and with that I think I am also on time so please

Closing

connect with me I am happy to connect on LinkedIn over the email and very it was

my pleasure to give this talk