The Paradox of Exposure: How AI and Your Smartphone Are Decimating Traditional Soccer Scouting and Unearthing Global Talent
We discusses AiScout, an artificial intelligence and mobile technology application created by Ai.io to revolutionize soccer player discovery. This platform democratizes the scouting process by enabling aspiring athletes globally to record themselves performing 75 standardized drills, which are then analyzed and scored using AI technology. Professional soccer clubs and leagues, including those in the English Premier League (EPL) and Major League Soccer (MLS), utilize these data-driven scores to efficiently identify talent from a wide user base of over 100,000 players. AiScout has successfully facilitated professional trials or national team selections for 147 players, effectively removing geographic and economic barriers to professional soccer opportunities.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
You know, it's kind of strange, isn't it?
We live in this world where, well, everyone's got a camera,
right? A supercomputer in their pocket.
Absolutely high definition video, instant sharing.
It's everywhere. So you'd think getting noticed
as a young athlete, say a reallytalented soccer player, would be
easier than ever. Just film yourself, send it off
Simple. That's the logical assumption,
(00:21):
yeah. But actually, it feels like the
opposite sometimes. Like getting truly discovered,
you know, having a professional club seriously look at you
standing out from all that digital noise.
It feels maybe harder. It's a real paradox.
That's exactly it, yeah. Visibility, Sure.
It's everywhere. Anyone can post a video clip.
It's cheap. It's universal, Right?
But getting someone professionalto actually vet that talent, to
(00:46):
figure out if that highlight reel translates to actual pro
potential, that's where the old system kicks in.
And it's, well, it's incredibly expensive.
Expensive and complex. In logistically a nightmare
often. Plus, historically it's been
pretty subjective. Think about traditional soccer
scouting. It's always been limited by,
well, geography mostly. And money.
(01:07):
Yeah, if you weren't lucky enough to be near a big club or
Academy. Exactly, if you didn't have the
funds to join an established visible Academy system.
Or maybe you live somewhere remote outside the usual
scouting circuits. Could be a village in Africa,
small town in South America, even parts of developed
countries. Your talent, no matter how
amazing, could just vanish invisible to the top.
(01:30):
Level pretty much just unseen. And that's the core issue we're
looking at today, this massive pool of untapped, unseen
potential simply because of location or economics.
It's a huge inefficiency in a global sport.
OK, so that's the problem, this paradox of exposure.
But today we're going to really dive deep into how technology
isn't just tweaking that old model, it's fundamentally
(01:53):
breaking it down. That's right.
We're exploring a system that's using, well, artificial
intelligence, AI combined with something almost everyone has a
mobile phone, to just leapfrog those old barriers, the
geographic ones, the economic ones.
So the mission for us today, foryou listening is to really get
under the hood of this, understand how this tech
breakthrough is building a new kind of pipeline, a verifiable
(02:15):
data-driven path to professionalopportunities in soccer.
Yeah, we're. Focusing on one specific
platform that basically turns any standard smartphone into a
pretty sophisticated, objective scouting tool.
It's about democratizing that search for the next generation
of stars, making it fairer, moreaccessible.
All right. Let's unpack that, starting with
the old way, the traditional scouting.
(02:37):
You mentioned the limitations, geography, cost.
Can you paint a picture of just how fragile that boots on the
ground system really is? Oh, it's incredibly resource
intensive, Yeah. Think about a scout from, say, a
top European club. What do they actually do?
Travel right, Lots of travel. Tons of it.
Flights, hotels, navigating unfamiliar places, maybe needing
translators, spending weeks or months away from the club's
(02:59):
training ground. And the cost must be huge.
Thousands easily for just one trip, and that immediately
limits where they can go, how many players they can
realistically see. You can't send scouts
everywhere. No.
Way. And then there's the human
element. The scout might be having an off
day. Maybe they're tired from jet
lag. Or the one day they watch a kid,
it's pouring rain, the pitch is a mud bath, and the player has a
(03:21):
terrible game. Or maybe.
The scout just has unconscious biases like they favor a certain
type of player because that worked for them years ago.
Exactly. Subjectivity creeps in.
Fatigue. Maybe they miss someone who
doesn't fit the physical mold they expect.
It's inefficient with money, andit's inherently biased, even
unintentionally. So OK, let's put ourselves in
(03:41):
the shoes of that talented 16 year old kid.
Maybe they're in rural Colombia,maybe a less scouted part of
Eastern Europe, maybe somewhere in Asia.
How does a scout from ManchesterUnited or Bayern Munich
realistically find them? The honest answer?
Mostly they don't. They just won't.
That's the massive blind spot ofthe traditional system.
Talent gets filtered out not necessarily by lack of ability,
(04:04):
but just by bad luck of locationor circumstance.
Can't afford the fees for the well known local Academy maybe.
That's a huge factor. Those established academies, the
ones scaled to do visit, often have significant costs
associated with them, so if you don't have the money, you're
already potentially excluded. So this new tech approach, the
one led by this company AI dot IO, its goal is to just smash
(04:27):
that barrier down. That's the core vision, to
eliminate that requirement for physical proximity, for money,
for access to the established network.
It's about providing a fair shotbased purely on ability.
So it's not just about making scouting a bit better, a bit
cheaper for the clubs, It's aiming for something bigger,
real democratization of opportunity.
(04:48):
Exactly. Leveling the playing field for
the player who just needs to be seen objectively.
And crucially, it also gives theclubs a massive advantage.
They get access to a vastly wider talent pool assessed using
data. It's a win win then.
Player gets seen, club finds talent they'd otherwise miss.
That's the idea, yeah. And it's all enabled by making
the tech accessible. The key piece is this app, a
(05:10):
scout. That's the disruptive element.
It takes everyday consumer tech.The phone in your pocket.
Right, the standard smartphone almost everyone has now and
turns it into professional gradeevaluation equipment.
No need for fancy sensors. Expensive of labs motion capture
suits. None of that.
Just your phone, the player, andpresumably some specific
(05:30):
instructions. Exactly.
A phone, the athlete, and a standardized set of criteria.
That's the fundamental shift. OK, that claim still feels
pretty big. A smartphone as a pro scouting
tool? How does that practically lower
the barrier? What happens on the app?
Well. Think about the cost structure.
Traditionally the initial vetting, just figuring out if a
player is even worth a closer look.
(05:51):
That's where a lot of the scouting cost and travel
happens. Makes sense, sending someone out
is expensive. Right with the app, that whole
initial phase shifts. The player downloads the app,
follows the instructions, performs the drills, films
themselves, and does it whereverthey are.
Their own local park, a school field, anywhere.
So the first trial happens remotely at 0 cost to the club.
(06:12):
Essentially, yes. The platform, the AI behind it,
provides that first layer of objective assessment.
It's like having a data scientist analyze the players
raw abilities before the club commits any resources.
No flights, no hotels, no scout time.
OK, so it drastically lowers theclub's risk for that initial
(06:33):
look. They're not spending thousands
just to see if someone might be good.
Exactly. And because it's so accessible
to the player, it just blows thetalent funnel wide open.
Yeah, suddenly the potential pool isn't just kids in known
academies, it's potentially anyone, anywhere, with a phone
and the talent. That initial assessment stage,
the most expensive and geographically locked part,
(06:53):
becomes virtually free to execute globally.
OK, logistically that's a game changer.
But, and this is a big but, right, this only works if the
data you get from a smartphone video is actually reliable.
It can't just be kids sending inflashy highlight reels.
The clubs need objective, trustworthy info.
Absolutely critical. And that's where the mechanics
of the deed identification come in.
This is the engine engineering behind the objectivity.
(07:15):
So how do they ensure it's not just, you know, edited videos or
performances that aren't comparable?
Standardization. That is the absolute key, the
linchpin of the whole system, tomake sure you can compare a
player doing drills in a park inBrazil with someone in the
state-of-the-art facility in Germany.
They have to be doing the exact same things, measured the same
way. Precisely, the platform requires
(07:38):
athletes to perform a set of 75 standardized drills 75.
Wow, OK, that sounds like a lot.75 drills.
It is. It's a significant undertaking
for the player, definitely. But that number isn't just
plucked out of thin air. It's designed as a comprehensive
battery. It's not just testing one thing
like shooting. It aims to assess the full
spectrum of of athletic performance, technical ability,
(08:02):
and functional movement patternsrelevant to soccer. 75 drills.
Can you give us a feel for what sort of things they cover?
We need to get specific here. What's a player actually doing
when they use this app? Yeah, good question.
It breaks down into roughly 4 key dimensions that are vital
for elite soccer. You've got technical skill,
functional movement speed and agility, and then some biometric
(08:23):
output measures. OK, let's take technical skill.
What does that look like in a drill?
So imagine drills that measure, say, the consistency of your
first touch, or how accurately you can pass a ball against a
wall from a set distance 10 times in a row.
Or maybe shooting accuracy, launching a ball from a specific
spot towards marked zones in a goal.
(08:43):
So quantifiable stuff, not just can you kick it hard, but can
you place it accurately, consistently under these
specific conditions. Exactly.
Repeatability and precision under standardized parameters,
yeah. Then for functional movement and
agility, think about shuttle runs, but very specific ones
like a 10 cone lateral shuffle, measuring how quickly and
efficiently you can change direction.
(09:04):
Stuff that tests coordination and balance at speed.
Right, Or drills designed to isolate how well you decelerate,
stop, and then accelerate again.Crucial movements in soccer.
And every single drill has strict rules.
The exact distance between cones, The specific movement
path required. Why so rigid?
To ensure the data is truly comparable.
(09:25):
That's the whole point. Whether you're using your phone
in Manchester or Mumbai, the AI is analyzing the same inputs
against the same defined requirements.
It removes the environmental variables as much as possible.
OK, that makes sense. Standardization is key for
comparison, but who or what is doing the analyzing?
You mentioned 100,000 users. Later on, no human can watch and
(09:47):
score what, 7.5 million individual drill videos?
Accurately, no chance. That's where the artificial
intelligence comes in. This is the the magic happening
behind the scenes. So how does AI turn a simple
smartphone video into sophisticated pro level
performance metrics? It's primarily using advanced
computer vision techniques coupled with biomechanical
modeling. When you upload the video of
yourself doing a drill, let's say it's a Sprint test, the AI
(10:09):
system processes that video data.
It's not just watching it like ahuman, it's running algorithms
that perform skeletal tracking and object recognition in real
time, essentially. Skeletal tracking.
What does that mean? The computer vision algorithms
identify key joint markers on the athlete's body.
Think hips, knees, ankles, shoulders, elbows.
(10:32):
It calculates their position in 3D space frame by frame,
millisecond by millisecond, justfrom the 2D video feed.
Wow. From a standard phone camera.
Yeah, it's computationally intensive, but the algorithms
are sophisticated enough now. And once it has that skeletal
data, you can calculate metrics that are basically invisible to
the human eye watching normally.Like what?
Things like angular velocity, how SAS specific joints are
(10:54):
rotating, stride length and frequency during a Sprint, foot
to ground contact time, even theconsistency of your running form
compared against a database of elite professional athletes
form. So the phone video isn't just a
video anymore, it becomes raw data for like a physics engine
analyzing the players movement. That's a great way to put it,
yeah. The AI automatically generates
(11:15):
this detailed objective report, biometric data, athletic
performance scores, all derived from those 75 standardized
movements. And crucially, because it's AI,
it removes that initial human bias, right?
The AI doesn't care what the player looks like, what kit
they're wearing, whether they look like a footballer.
Completely agnostic. It only cares about the data
points derived from the measuredmovements.
(11:36):
Did they meet the speed threshold?
How consistent was their touch? How efficient was their change
of direction measured in milliseconds and degrees?
That. Feels like a fundamental shift
moving from a scouts subjective eye test, or gut feeling it at
least for the first look, to purely quantitative measurement.
It is. It provides that crucial first
(11:56):
snapshot based purely on performance data, and that
objectivity is key to reducing the risk of overlooking someone
who doesn't fit a preconceived mold or just happen to have a
bad day when a scout watched. OK, but hang on, soccer isn't
just about running fast or kicking accurately in drills, is
it? What about the intangibles?
Tactical awareness, Reading the game?
Vision, decision making under pressure?
(12:19):
The things that really separate good athletes from great
players. How does AI measure that from
standardized drills? That's a really important
question, and the answer is it doesn't, not directly.
The AI assessment based on thesedrills is designed to be the
ultimate filter for the objective, measurable physical
and technical foundations. So it's screens for the basic
(12:41):
tools needed. Exactly.
It's screens for the capacity topotentially become elite.
It tells the club OK based purely on measurable data.
This player scores in the 95th percentile globally for agility,
techno consistency and ball striking power, according to our
standardized tests. It identifies the raw material.
It finds the athletes who can physically and technically do
(13:01):
the job. Precisely, It removes the need
for expensive human scouts to waste time evaluating thousands
of players who objectively just don't have the fundamental
athletic or technical baseline required for the professional
level. So the AI does the massive
initial sift. Right.
It finds those top few percent based on data to the outliers
like the 147 players we'll talk about who got trials.
(13:23):
Then the human element comes back in, but in much more
focused way. The club takes that data, sees
the high scores and then invest the resources.
They bring those statistically validated players in for a
proper in person trial. That's where the human coaches
assess the intangibles, the character, the coach ability,
how they perform in actual game situations, the tactical
(13:46):
understanding. So the AI isn't replacing the
human scout entirely. Not at all.
It's making the scout infinitelymore effective.
It turbocharges their efforts byensuring they only spend their
valuable time in the club's money on players who have
already cleared a very high objective bar based on data.
It validates where they should focus their attention.
Got it. So the data acts as this bridge.
It connects the player who performs well objectively
(14:08):
wherever they are, to the possibility of that professional
trial. Instead of Scout maybe stumbling
upon them, the club is actively searching a global database for
specific data profiles. Yeah, it completely changes the
strategy. Clubs can filter this huge
database for very specific needs.
Maybe they need a left back withexceptional acceleration scores
and high endurance metrics. They can query the data for
(14:30):
players who fit that exact profile.
Before ever seeing them play live.
Before spending a penny on travel, it allows for incredibly
targeted talent identification based on specific, measurable
attributes that align with theirtactical needs.
OK, the mechanics sound impressive.
The theory is compelling. But you know the proof is in the
pudding, right? Let's talk real world impact.
(14:52):
Is this actually working? Are these pipelines getting
players noticed? Yeah, let's look at the numbers,
because they are pretty remarkable, especially
considering how relatively new this approach is in widespread
application. Since it really launched
properly in 2023, the platform ascout has signed up over 100,000
users. 100,000 players worldwide.
(15:13):
Over that, Yeah. Now think about the scale of
data that represents 100,000 players each performing those 75
standardized drills. That's 7.5 million data points
or more, because each drill probably generates multiple
metrics. Exactly.
It's a massive, constantly growing data set of highly
granular performance informationbeing analyzed, scored
(15:34):
objectively, and benchmarked against global standards.
Incredible volume. But the key question, the one
everyone listening wants to know, does it lead anywhere?
Are these data profiles actuallytranslating into real
professional outcomes for players, Contracts.
Trials. Absolutely, and this is the
bottom line, the most crucial metric.
(15:54):
To date, the platform has directly helped 147 players
secure professional trials or selections for national teams.
147 layers getting a shot at thepro level directly because of
their performance data on this a.
That's correct. And these aren't just random
occurrences, these are tangible,life changing opportunities
generated because the data objectively highlighted their
(16:15):
potential, allowing them to bypass those traditional
geographic or ganomic roadblocks.
That number, 147, feels significant, especially from a
pool identified purely remotely and validated by AI.
That efficiency seems high compared to traditional methods.
It's an efficiency rate that traditional scouting, with its
massive costs and limitations, would likely struggle to match,
(16:37):
certainly not from such a diverse, previously invisible
pool. It shows the system works in
identifying genuine prospects. OK, this is where it gets really
interesting for me and I think for you.
Listening to numbers are one thing, but stories make it real.
You mentioned quantifiable success.
Let's talk specifics. The Ben Greenwood story is often
cited. Tell us about that.
(16:57):
How did he go from using an app to signing for a professional
club? Right.
The Ben Greenwood case is almostthe perfect illustration of how
this pipeline functions. He used the app, performed the
75 drills. His performance data, when
analyzed by the AI, flagged him as a serious outlier, just
exceptionally high scores in keyareas.
So the data screamed potential. Exactly.
(17:18):
The objective scores were so compelling that they earned him
an immediate trial invitation from Chelsea FC.
Wow, Chelsea, one of the biggestclubs in the world based purely
on smartphone data. Based purely on the objective
data generated through the app, That alone is a massive
statement about trust clubs are beginning to place in this
technology, in these algorithms.OK, so he gets a trial at
(17:40):
Chelsea. What happened next?
Now ultimately he didn't end up signing a contract with Chelsea
after the trial, but that's not the end of the story and
actually highlights another key benefit.
How so the? Visibility he gained and
crucially, the validation that came from being identified by
the subjective system and getting that trial in elite club
like Chelsea, that was huge. It proved his potential wasn't
(18:02):
just a fluke. It gave him credibility.
Absolutely. That objective validation, the
proof that his data profile was good enough to interest his top
Premier League club directly ledto him securing a professional
contract shortly after with AFC Bournemouth, another significant
English club. I see, so the AI data open the
very first door got him noticed at the highest level, and even
(18:25):
though that specific door didn'tlead to a contract, the
validation it provided open the next door for him.
Precisely the platform acted as that initial risk free entry
point for the club and a validation tool for the player.
It proved his fundamental abilities were at a professional
level. The AIS Objective Score report
essentially acted as a verified reference that other clubs could
(18:46):
trust. That's a powerful pathway.
Are there other examples like that?
Yeah, another clear one is Jez Davies.
He was signed by Burnley, another club playing at the
highest levels in England, againafter being initially identified
and assessed entirely through the apps objective evaluation
process. So multiple cases of players
getting actual pro contracts in top leagues starting from just
(19:08):
using their phone. Correct.
These aren't just anecdotes, they are verifiable examples
showing the system is functioning as intended.
It's creating a modern, efficient pipeline that directly
connects talent that might have been previously overlooked for
whatever reason straight to top tier professional clubs.
And what this really demonstrates, I think, is that
clubs are now trusting this AI generated data enough to make
(19:31):
significant decisions based on it.
Decisions like flying a player in investing time and resources
in a physical trial. That's a big commitment.
It absolutely is, and it signalsA fundamental shift in their
risk assessment and resource allocation.
Why? Because it optimizes their
efficiency dramatically. How so?
Instead of the old way is sending a scout halfway around
(19:53):
the world on a hunch, hoping to maybe see one player who might
be good enough, they can now sitdown, review the objectively
scored performance data from literally thousands of players
globally. They can filter that data,
identify maybe the top 2 or 3% who meet their specific
criteria, say exceptional speed and dribbling scores.
Then they invest the money to fly only those few highly
(20:16):
validated candidates in for the in person assessment.
So they maximize their chances of finding the right player
while minimizing the cost and wasted effort.
Exactly. They're using data to make much
smarter bets on where to deploy their expensive human resources.
OK, Speaking of maximizing advantage and making smart bets,
let's talk about adoption by thebig players.
(20:37):
For this AI scouting system to really be revolutionary, it
needs buy in from the elite clubs, right?
The ones who theoretically already have the biggest budgets
and the most extensive traditional scouting networks.
That's a crucial point and we are seeing exactly that.
Who's using it? Well, among the prominent early
adopters are giants in the English Premier League, Chelsea,
(20:58):
who we mentioned, and Burnley. OK, so top flight English clubs,
their involvement sends a prettystrong signal, doesn't it?
This isn't just some gimmick, it's being seen as a serious
tool at the highest level. Absolutely.
It's signals that they view thisas a strategic necessity.
It's about staying competitive in the relentless global arms
race for talent. But why?
(21:19):
Why would a club like Chelsea, with seemingly unlimited
resources and scouts all over the world, already need this?
What's the incentive for them? 2 main drivers I think
efficiency and crucially expansion of reach.
Even for a club like Chelsea, scouting is expensive and
imperfect. Missing out on the next big
thing because they were playing in an unscouted region is a
(21:41):
potentially massive multi £1,000,000 mistake down the
line. In terms of lost transfer value
or just not having that player on their team.
Both. By integrating AI driven
scouting, they expand their initial funnel exponentially.
Almost infinitely. They are effectively turning
millions of smartphones worldwide into potential first
(22:01):
stage scouts working for them 2 / 7, objectively flagging
potential talent they would never have found otherwise.
It's like getting a pre filteredlist of the most promising
needles from the entire global haystack without having to sift
through the hay themselves. That's a perfect analogy.
It gives them a massive competitive advantage in
Discovery, one they really can'tafford to ignore if the rivals
are using it. Makes sense.
(22:22):
Is it just EPL clubs or is it catching on elsewhere?
No, it's broader than that. Clubs in Major League Soccer MLS
in the United States are also adopting the technology, which
shows it has appeal across different major leagues, all
facing similar challenges and efficient global talent
identification. OK. the US market is
interesting. MLS is growing fast, lots of
(22:44):
investment. You mentioned a specific
strategic move regarding access for US players.
Yes, that's quite significant. In 2024, the platform a scout,
was made completely free for allplayers based in the United
States. Free, so no cost at all for the
player to download, use it and potentially get seen. 0 cost
barrier for the player. And that move really underscores
(23:05):
the commitment to the democratization idea.
It's about maximizing accessibility, ensuring the
widest possible pool of talent can get into the system.
Especially in a huge developing soccer market like the US,
removing any friction for playeruptake seems key to getting the
most comprehensive data. Exactly.
It ensures they capture as much data from that important market
(23:25):
as possible, which benefits boththe players seeking
opportunities and the clubs searching for talent within that
specific pool. It reinforces that core goal,
mass accessibility, global reach.
So let's bring it all together then.
We've talked about the tech, thedata, the success stories, the
elite adoption. What's the ultimate?
(23:45):
So what? What does this democratization
really mean for soccer? For the players, For the clubs?
Well, let's look at the two sides.
For the athlete, the impact is potentially profound.
It fundamentally removes those traditional barriers where you
live, how much money your familyhas.
Your post code doesn't determineyour visibility anymore.
Not for that initial assessment,no.
You don't need to be near a major city or afford expensive
(24:08):
Academy fees to get onto the radar of the world's biggest
clubs. Your raw ability, measured
objectively by AI against standardized benchmarks, becomes
the primary currency. It creates a more level playing
field, a genuine meritocracy, atleast at that first hurdle.
That's the goal, where the data speaks first, regardless of
background or connections. It offers hope and a tangible
(24:29):
pathway for talented kids everywhere.
And then for the clubs, what's the big win for them wrapping it
up? For the clubs, it's about
efficiency, objectivity and finding hidden gems.
It gives them a data-driven strategy to discover those
future stars they might otherwise miss, and to do it far
more cost effectively than was ever possible before.
So it's transforming Scouting from the sort of subjective,
(24:52):
geographically limited art. Form into more of a
standardized, globally accessible science, ensuring
talent isn't overlooked just because of bad luck or lack of
resources. Which ultimately should lead to
a deeper, more diverse, more globally representative pool of
talent reaching the professionallevel.
Absolutely. It enriches the game overall.
The data acts as a guarantee if you have the required ability
(25:14):
demonstrated objectively. The pipeline to potentially get
noticed is now open to you no matter where you start.
OK, so just to synthesize this deep dive for everyone
listening, we started with that strange situation.
More ways to be visible than ever, yet harder to get truly
discovered. The paradox of exposure.
Right. And we saw how AI, combined with
(25:36):
the smartphone everyone carries completely flips, that it uses
those 75 standardized drills notjust as exercises but as data
collection points. Turning that simple phone video
into a really sophisticated athletic profile using computer
vision and bio mechanics. Objective comparable data.
And that shift from subjective eye test to objective data
(25:57):
scoring is the absolute core transformation.
It's not just theory. We have the numbers over 100,000
users feeding data into the system and.
Critically, 147 players who've already secured professional
trials or national team looks directly because of that data.
Plus the buy in from top clubs like Chelsea and Burnley proves
it's stories like Ben Greenwood going from the app to a Chelsea
(26:17):
trial and then signing for Bournemouth or Jez Davies
signing for Burnley. They show the pipeline is real
and it works. It really feels like.
Technology genuinely leveling the playing field here, making
that dream of professional sportpotentially accessible based on
merit, on measured ability, regardless of where you start.
It validates the talent that wasalways there, just hidden.
(26:39):
Exactly. It removes the.
Obscurity caused by simple logistics or economics.
And you know the implications here?
They ripple out far beyond just soccer or even sports.
How do you mean? Well, think about it, if
artificial intelligence can use a standard smartphone and some
standardized tasks to objectively and efficiently
identify world class athletic talent, something previously
(27:00):
reliant on years of expensive travel, human intuition and
subjective networks, then what other fields are next?
Think about other highly specialized areas, maybe certain
types of creative talent, technical skills, problem
solving abilities, Fields currently dominated by
traditional networks. Interviews, subjective
assessments, geographical hubs, you're saying could AI?
Do a similar thing there. Create objective, accessible
(27:22):
pathways based on demonstrated ability, regardless of
background or location. It's the big question, isn't?
It if AI can democratize the search for elite athletes this
effectively, what other domains currently locked behind
subjective gates and traditionalstructures are right for this
kind of technological disruption?
That's something for you to really Mull over.
Where else could AI uncover hidden talent the world is
(27:45):
currently missing?
You know, it's kind of strange, isn't it?
We live in this world where, well, everyone's got a camera,
right? A supercomputer in their pocket.
Absolutely high definition video, instant sharing.
It's everywhere. So you'd think getting noticed
as a young athlete, say a reallytalented soccer player, would be
easier than ever. Just film yourself, send it off
Simple. That's the logical assumption,
(00:21):
yeah. But actually, it feels like the
opposite sometimes. Like getting truly discovered,
you know, having a professional club seriously look at you
standing out from all that digital noise.
It feels maybe harder. It's a real paradox.
That's exactly it, yeah. Visibility, Sure.
It's everywhere. Anyone can post a video clip.
It's cheap. It's universal, Right?
But getting someone professionalto actually vet that talent, to
(00:46):
figure out if that highlight reel translates to actual pro
potential, that's where the old system kicks in.
And it's, well, it's incredibly expensive.
Expensive and complex. In logistically a nightmare
often. Plus, historically it's been
pretty subjective. Think about traditional soccer
scouting. It's always been limited by,
well, geography mostly. And money.
(01:07):
Yeah, if you weren't lucky enough to be near a big club or
Academy. Exactly, if you didn't have the
funds to join an established visible Academy system.
Or maybe you live somewhere remote outside the usual
scouting circuits. Could be a village in Africa,
small town in South America, even parts of developed
countries. Your talent, no matter how
amazing, could just vanish invisible to the top.
(01:30):
Level pretty much just unseen. And that's the core issue we're
looking at today, this massive pool of untapped, unseen
potential simply because of location or economics.
It's a huge inefficiency in a global sport.
OK, so that's the problem, this paradox of exposure.
But today we're going to really dive deep into how technology
isn't just tweaking that old model, it's fundamentally
(01:53):
breaking it down. That's right.
We're exploring a system that's using, well, artificial
intelligence, AI combined with something almost everyone has a
mobile phone, to just leapfrog those old barriers, the
geographic ones, the economic ones.
So the mission for us today, foryou listening is to really get
under the hood of this, understand how this tech
breakthrough is building a new kind of pipeline, a verifiable
(02:15):
data-driven path to professionalopportunities in soccer.
Yeah, we're. Focusing on one specific
platform that basically turns any standard smartphone into a
pretty sophisticated, objective scouting tool.
It's about democratizing that search for the next generation
of stars, making it fairer, moreaccessible.
All right. Let's unpack that, starting with
the old way, the traditional scouting.
(02:37):
You mentioned the limitations, geography, cost.
Can you paint a picture of just how fragile that boots on the
ground system really is? Oh, it's incredibly resource
intensive, Yeah. Think about a scout from, say, a
top European club. What do they actually do?
Travel right, Lots of travel. Tons of it.
Flights, hotels, navigating unfamiliar places, maybe needing
translators, spending weeks or months away from the club's
(02:59):
training ground. And the cost must be huge.
Thousands easily for just one trip, and that immediately
limits where they can go, how many players they can
realistically see. You can't send scouts
everywhere. No.
Way. And then there's the human
element. The scout might be having an off
day. Maybe they're tired from jet
lag. Or the one day they watch a kid,
it's pouring rain, the pitch is a mud bath, and the player has a
(03:21):
terrible game. Or maybe.
The scout just has unconscious biases like they favor a certain
type of player because that worked for them years ago.
Exactly. Subjectivity creeps in.
Fatigue. Maybe they miss someone who
doesn't fit the physical mold they expect.
It's inefficient with money, andit's inherently biased, even
unintentionally. So OK, let's put ourselves in
(03:41):
the shoes of that talented 16 year old kid.
Maybe they're in rural Colombia,maybe a less scouted part of
Eastern Europe, maybe somewhere in Asia.
How does a scout from ManchesterUnited or Bayern Munich
realistically find them? The honest answer?
Mostly they don't. They just won't.
That's the massive blind spot ofthe traditional system.
Talent gets filtered out not necessarily by lack of ability,
(04:04):
but just by bad luck of locationor circumstance.
Can't afford the fees for the well known local Academy maybe.
That's a huge factor. Those established academies, the
ones scaled to do visit, often have significant costs
associated with them, so if you don't have the money, you're
already potentially excluded. So this new tech approach, the
one led by this company AI dot IO, its goal is to just smash
(04:27):
that barrier down. That's the core vision, to
eliminate that requirement for physical proximity, for money,
for access to the established network.
It's about providing a fair shotbased purely on ability.
So it's not just about making scouting a bit better, a bit
cheaper for the clubs, It's aiming for something bigger,
real democratization of opportunity.
(04:48):
Exactly. Leveling the playing field for
the player who just needs to be seen objectively.
And crucially, it also gives theclubs a massive advantage.
They get access to a vastly wider talent pool assessed using
data. It's a win win then.
Player gets seen, club finds talent they'd otherwise miss.
That's the idea, yeah. And it's all enabled by making
the tech accessible. The key piece is this app, a
(05:10):
scout. That's the disruptive element.
It takes everyday consumer tech.The phone in your pocket.
Right, the standard smartphone almost everyone has now and
turns it into professional gradeevaluation equipment.
No need for fancy sensors. Expensive of labs motion capture
suits. None of that.
Just your phone, the player, andpresumably some specific
(05:30):
instructions. Exactly.
A phone, the athlete, and a standardized set of criteria.
That's the fundamental shift. OK, that claim still feels
pretty big. A smartphone as a pro scouting
tool? How does that practically lower
the barrier? What happens on the app?
Well. Think about the cost structure.
Traditionally the initial vetting, just figuring out if a
player is even worth a closer look.
(05:51):
That's where a lot of the scouting cost and travel
happens. Makes sense, sending someone out
is expensive. Right with the app, that whole
initial phase shifts. The player downloads the app,
follows the instructions, performs the drills, films
themselves, and does it whereverthey are.
Their own local park, a school field, anywhere.
So the first trial happens remotely at 0 cost to the club.
(06:12):
Essentially, yes. The platform, the AI behind it,
provides that first layer of objective assessment.
It's like having a data scientist analyze the players
raw abilities before the club commits any resources.
No flights, no hotels, no scout time.
OK, so it drastically lowers theclub's risk for that initial
(06:33):
look. They're not spending thousands
just to see if someone might be good.
Exactly. And because it's so accessible
to the player, it just blows thetalent funnel wide open.
Yeah, suddenly the potential pool isn't just kids in known
academies, it's potentially anyone, anywhere, with a phone
and the talent. That initial assessment stage,
the most expensive and geographically locked part,
(06:53):
becomes virtually free to execute globally.
OK, logistically that's a game changer.
But, and this is a big but, right, this only works if the
data you get from a smartphone video is actually reliable.
It can't just be kids sending inflashy highlight reels.
The clubs need objective, trustworthy info.
Absolutely critical. And that's where the mechanics
of the deed identification come in.
This is the engine engineering behind the objectivity.
(07:15):
So how do they ensure it's not just, you know, edited videos or
performances that aren't comparable?
Standardization. That is the absolute key, the
linchpin of the whole system, tomake sure you can compare a
player doing drills in a park inBrazil with someone in the
state-of-the-art facility in Germany.
They have to be doing the exact same things, measured the same
way. Precisely, the platform requires
(07:38):
athletes to perform a set of 75 standardized drills 75.
Wow, OK, that sounds like a lot.75 drills.
It is. It's a significant undertaking
for the player, definitely. But that number isn't just
plucked out of thin air. It's designed as a comprehensive
battery. It's not just testing one thing
like shooting. It aims to assess the full
spectrum of of athletic performance, technical ability,
(08:02):
and functional movement patternsrelevant to soccer. 75 drills.
Can you give us a feel for what sort of things they cover?
We need to get specific here. What's a player actually doing
when they use this app? Yeah, good question.
It breaks down into roughly 4 key dimensions that are vital
for elite soccer. You've got technical skill,
functional movement speed and agility, and then some biometric
(08:23):
output measures. OK, let's take technical skill.
What does that look like in a drill?
So imagine drills that measure, say, the consistency of your
first touch, or how accurately you can pass a ball against a
wall from a set distance 10 times in a row.
Or maybe shooting accuracy, launching a ball from a specific
spot towards marked zones in a goal.
(08:43):
So quantifiable stuff, not just can you kick it hard, but can
you place it accurately, consistently under these
specific conditions. Exactly.
Repeatability and precision under standardized parameters,
yeah. Then for functional movement and
agility, think about shuttle runs, but very specific ones
like a 10 cone lateral shuffle, measuring how quickly and
efficiently you can change direction.
(09:04):
Stuff that tests coordination and balance at speed.
Right, Or drills designed to isolate how well you decelerate,
stop, and then accelerate again.Crucial movements in soccer.
And every single drill has strict rules.
The exact distance between cones, The specific movement
path required. Why so rigid?
To ensure the data is truly comparable.
(09:25):
That's the whole point. Whether you're using your phone
in Manchester or Mumbai, the AI is analyzing the same inputs
against the same defined requirements.
It removes the environmental variables as much as possible.
OK, that makes sense. Standardization is key for
comparison, but who or what is doing the analyzing?
You mentioned 100,000 users. Later on, no human can watch and
(09:47):
score what, 7.5 million individual drill videos?
Accurately, no chance. That's where the artificial
intelligence comes in. This is the the magic happening
behind the scenes. So how does AI turn a simple
smartphone video into sophisticated pro level
performance metrics? It's primarily using advanced
computer vision techniques coupled with biomechanical
modeling. When you upload the video of
yourself doing a drill, let's say it's a Sprint test, the AI
(10:09):
system processes that video data.
It's not just watching it like ahuman, it's running algorithms
that perform skeletal tracking and object recognition in real
time, essentially. Skeletal tracking.
What does that mean? The computer vision algorithms
identify key joint markers on the athlete's body.
Think hips, knees, ankles, shoulders, elbows.
(10:32):
It calculates their position in 3D space frame by frame,
millisecond by millisecond, justfrom the 2D video feed.
Wow. From a standard phone camera.
Yeah, it's computationally intensive, but the algorithms
are sophisticated enough now. And once it has that skeletal
data, you can calculate metrics that are basically invisible to
the human eye watching normally.Like what?
Things like angular velocity, how SAS specific joints are
(10:54):
rotating, stride length and frequency during a Sprint, foot
to ground contact time, even theconsistency of your running form
compared against a database of elite professional athletes
form. So the phone video isn't just a
video anymore, it becomes raw data for like a physics engine
analyzing the players movement. That's a great way to put it,
yeah. The AI automatically generates
(11:15):
this detailed objective report, biometric data, athletic
performance scores, all derived from those 75 standardized
movements. And crucially, because it's AI,
it removes that initial human bias, right?
The AI doesn't care what the player looks like, what kit
they're wearing, whether they look like a footballer.
Completely agnostic. It only cares about the data
points derived from the measuredmovements.
(11:36):
Did they meet the speed threshold?
How consistent was their touch? How efficient was their change
of direction measured in milliseconds and degrees?
That. Feels like a fundamental shift
moving from a scouts subjective eye test, or gut feeling it at
least for the first look, to purely quantitative measurement.
It is. It provides that crucial first
(11:56):
snapshot based purely on performance data, and that
objectivity is key to reducing the risk of overlooking someone
who doesn't fit a preconceived mold or just happen to have a
bad day when a scout watched. OK, but hang on, soccer isn't
just about running fast or kicking accurately in drills, is
it? What about the intangibles?
Tactical awareness, Reading the game?
Vision, decision making under pressure?
(12:19):
The things that really separate good athletes from great
players. How does AI measure that from
standardized drills? That's a really important
question, and the answer is it doesn't, not directly.
The AI assessment based on thesedrills is designed to be the
ultimate filter for the objective, measurable physical
and technical foundations. So it's screens for the basic
(12:41):
tools needed. Exactly.
It's screens for the capacity topotentially become elite.
It tells the club OK based purely on measurable data.
This player scores in the 95th percentile globally for agility,
techno consistency and ball striking power, according to our
standardized tests. It identifies the raw material.
It finds the athletes who can physically and technically do
(13:01):
the job. Precisely, It removes the need
for expensive human scouts to waste time evaluating thousands
of players who objectively just don't have the fundamental
athletic or technical baseline required for the professional
level. So the AI does the massive
initial sift. Right.
It finds those top few percent based on data to the outliers
like the 147 players we'll talk about who got trials.
(13:23):
Then the human element comes back in, but in much more
focused way. The club takes that data, sees
the high scores and then invest the resources.
They bring those statistically validated players in for a
proper in person trial. That's where the human coaches
assess the intangibles, the character, the coach ability,
how they perform in actual game situations, the tactical
(13:46):
understanding. So the AI isn't replacing the
human scout entirely. Not at all.
It's making the scout infinitelymore effective.
It turbocharges their efforts byensuring they only spend their
valuable time in the club's money on players who have
already cleared a very high objective bar based on data.
It validates where they should focus their attention.
Got it. So the data acts as this bridge.
It connects the player who performs well objectively
(14:08):
wherever they are, to the possibility of that professional
trial. Instead of Scout maybe stumbling
upon them, the club is actively searching a global database for
specific data profiles. Yeah, it completely changes the
strategy. Clubs can filter this huge
database for very specific needs.
Maybe they need a left back withexceptional acceleration scores
and high endurance metrics. They can query the data for
(14:30):
players who fit that exact profile.
Before ever seeing them play live.
Before spending a penny on travel, it allows for incredibly
targeted talent identification based on specific, measurable
attributes that align with theirtactical needs.
OK, the mechanics sound impressive.
The theory is compelling. But you know the proof is in the
pudding, right? Let's talk real world impact.
(14:52):
Is this actually working? Are these pipelines getting
players noticed? Yeah, let's look at the numbers,
because they are pretty remarkable, especially
considering how relatively new this approach is in widespread
application. Since it really launched
properly in 2023, the platform ascout has signed up over 100,000
users. 100,000 players worldwide.
(15:13):
Over that, Yeah. Now think about the scale of
data that represents 100,000 players each performing those 75
standardized drills. That's 7.5 million data points
or more, because each drill probably generates multiple
metrics. Exactly.
It's a massive, constantly growing data set of highly
granular performance informationbeing analyzed, scored
(15:34):
objectively, and benchmarked against global standards.
Incredible volume. But the key question, the one
everyone listening wants to know, does it lead anywhere?
Are these data profiles actuallytranslating into real
professional outcomes for players, Contracts.
Trials. Absolutely, and this is the
bottom line, the most crucial metric.
(15:54):
To date, the platform has directly helped 147 players
secure professional trials or selections for national teams.
147 layers getting a shot at thepro level directly because of
their performance data on this a.
That's correct. And these aren't just random
occurrences, these are tangible,life changing opportunities
generated because the data objectively highlighted their
(16:15):
potential, allowing them to bypass those traditional
geographic or ganomic roadblocks.
That number, 147, feels significant, especially from a
pool identified purely remotely and validated by AI.
That efficiency seems high compared to traditional methods.
It's an efficiency rate that traditional scouting, with its
massive costs and limitations, would likely struggle to match,
(16:37):
certainly not from such a diverse, previously invisible
pool. It shows the system works in
identifying genuine prospects. OK, this is where it gets really
interesting for me and I think for you.
Listening to numbers are one thing, but stories make it real.
You mentioned quantifiable success.
Let's talk specifics. The Ben Greenwood story is often
cited. Tell us about that.
(16:57):
How did he go from using an app to signing for a professional
club? Right.
The Ben Greenwood case is almostthe perfect illustration of how
this pipeline functions. He used the app, performed the
75 drills. His performance data, when
analyzed by the AI, flagged him as a serious outlier, just
exceptionally high scores in keyareas.
So the data screamed potential. Exactly.
(17:18):
The objective scores were so compelling that they earned him
an immediate trial invitation from Chelsea FC.
Wow, Chelsea, one of the biggestclubs in the world based purely
on smartphone data. Based purely on the objective
data generated through the app, That alone is a massive
statement about trust clubs are beginning to place in this
technology, in these algorithms.OK, so he gets a trial at
(17:40):
Chelsea. What happened next?
Now ultimately he didn't end up signing a contract with Chelsea
after the trial, but that's not the end of the story and
actually highlights another key benefit.
How so the? Visibility he gained and
crucially, the validation that came from being identified by
the subjective system and getting that trial in elite club
like Chelsea, that was huge. It proved his potential wasn't
(18:02):
just a fluke. It gave him credibility.
Absolutely. That objective validation, the
proof that his data profile was good enough to interest his top
Premier League club directly ledto him securing a professional
contract shortly after with AFC Bournemouth, another significant
English club. I see, so the AI data open the
very first door got him noticed at the highest level, and even
(18:25):
though that specific door didn'tlead to a contract, the
validation it provided open the next door for him.
Precisely the platform acted as that initial risk free entry
point for the club and a validation tool for the player.
It proved his fundamental abilities were at a professional
level. The AIS Objective Score report
essentially acted as a verified reference that other clubs could
(18:46):
trust. That's a powerful pathway.
Are there other examples like that?
Yeah, another clear one is Jez Davies.
He was signed by Burnley, another club playing at the
highest levels in England, againafter being initially identified
and assessed entirely through the apps objective evaluation
process. So multiple cases of players
getting actual pro contracts in top leagues starting from just
(19:08):
using their phone. Correct.
These aren't just anecdotes, they are verifiable examples
showing the system is functioning as intended.
It's creating a modern, efficient pipeline that directly
connects talent that might have been previously overlooked for
whatever reason straight to top tier professional clubs.
And what this really demonstrates, I think, is that
clubs are now trusting this AI generated data enough to make
(19:31):
significant decisions based on it.
Decisions like flying a player in investing time and resources
in a physical trial. That's a big commitment.
It absolutely is, and it signalsA fundamental shift in their
risk assessment and resource allocation.
Why? Because it optimizes their
efficiency dramatically. How so?
Instead of the old way is sending a scout halfway around
(19:53):
the world on a hunch, hoping to maybe see one player who might
be good enough, they can now sitdown, review the objectively
scored performance data from literally thousands of players
globally. They can filter that data,
identify maybe the top 2 or 3% who meet their specific
criteria, say exceptional speed and dribbling scores.
Then they invest the money to fly only those few highly
(20:16):
validated candidates in for the in person assessment.
So they maximize their chances of finding the right player
while minimizing the cost and wasted effort.
Exactly. They're using data to make much
smarter bets on where to deploy their expensive human resources.
OK, Speaking of maximizing advantage and making smart bets,
let's talk about adoption by thebig players.
(20:37):
For this AI scouting system to really be revolutionary, it
needs buy in from the elite clubs, right?
The ones who theoretically already have the biggest budgets
and the most extensive traditional scouting networks.
That's a crucial point and we are seeing exactly that.
Who's using it? Well, among the prominent early
adopters are giants in the English Premier League, Chelsea,
(20:58):
who we mentioned, and Burnley. OK, so top flight English clubs,
their involvement sends a prettystrong signal, doesn't it?
This isn't just some gimmick, it's being seen as a serious
tool at the highest level. Absolutely.
It's signals that they view thisas a strategic necessity.
It's about staying competitive in the relentless global arms
race for talent. But why?
(21:19):
Why would a club like Chelsea, with seemingly unlimited
resources and scouts all over the world, already need this?
What's the incentive for them? 2 main drivers I think
efficiency and crucially expansion of reach.
Even for a club like Chelsea, scouting is expensive and
imperfect. Missing out on the next big
thing because they were playing in an unscouted region is a
(21:41):
potentially massive multi £1,000,000 mistake down the
line. In terms of lost transfer value
or just not having that player on their team.
Both. By integrating AI driven
scouting, they expand their initial funnel exponentially.
Almost infinitely. They are effectively turning
millions of smartphones worldwide into potential first
(22:01):
stage scouts working for them 2 / 7, objectively flagging
potential talent they would never have found otherwise.
It's like getting a pre filteredlist of the most promising
needles from the entire global haystack without having to sift
through the hay themselves. That's a perfect analogy.
It gives them a massive competitive advantage in
Discovery, one they really can'tafford to ignore if the rivals
are using it. Makes sense.
(22:22):
Is it just EPL clubs or is it catching on elsewhere?
No, it's broader than that. Clubs in Major League Soccer MLS
in the United States are also adopting the technology, which
shows it has appeal across different major leagues, all
facing similar challenges and efficient global talent
identification. OK. the US market is
interesting. MLS is growing fast, lots of
(22:44):
investment. You mentioned a specific
strategic move regarding access for US players.
Yes, that's quite significant. In 2024, the platform a scout,
was made completely free for allplayers based in the United
States. Free, so no cost at all for the
player to download, use it and potentially get seen. 0 cost
barrier for the player. And that move really underscores
(23:05):
the commitment to the democratization idea.
It's about maximizing accessibility, ensuring the
widest possible pool of talent can get into the system.
Especially in a huge developing soccer market like the US,
removing any friction for playeruptake seems key to getting the
most comprehensive data. Exactly.
It ensures they capture as much data from that important market
(23:25):
as possible, which benefits boththe players seeking
opportunities and the clubs searching for talent within that
specific pool. It reinforces that core goal,
mass accessibility, global reach.
So let's bring it all together then.
We've talked about the tech, thedata, the success stories, the
elite adoption. What's the ultimate?
(23:45):
So what? What does this democratization
really mean for soccer? For the players, For the clubs?
Well, let's look at the two sides.
For the athlete, the impact is potentially profound.
It fundamentally removes those traditional barriers where you
live, how much money your familyhas.
Your post code doesn't determineyour visibility anymore.
Not for that initial assessment,no.
You don't need to be near a major city or afford expensive
(24:08):
Academy fees to get onto the radar of the world's biggest
clubs. Your raw ability, measured
objectively by AI against standardized benchmarks, becomes
the primary currency. It creates a more level playing
field, a genuine meritocracy, atleast at that first hurdle.
That's the goal, where the data speaks first, regardless of
background or connections. It offers hope and a tangible
(24:29):
pathway for talented kids everywhere.
And then for the clubs, what's the big win for them wrapping it
up? For the clubs, it's about
efficiency, objectivity and finding hidden gems.
It gives them a data-driven strategy to discover those
future stars they might otherwise miss, and to do it far
more cost effectively than was ever possible before.
So it's transforming Scouting from the sort of subjective,
(24:52):
geographically limited art. Form into more of a
standardized, globally accessible science, ensuring
talent isn't overlooked just because of bad luck or lack of
resources. Which ultimately should lead to
a deeper, more diverse, more globally representative pool of
talent reaching the professionallevel.
Absolutely. It enriches the game overall.
The data acts as a guarantee if you have the required ability
(25:14):
demonstrated objectively. The pipeline to potentially get
noticed is now open to you no matter where you start.
OK, so just to synthesize this deep dive for everyone
listening, we started with that strange situation.
More ways to be visible than ever, yet harder to get truly
discovered. The paradox of exposure.
Right. And we saw how AI, combined with
(25:36):
the smartphone everyone carries completely flips, that it uses
those 75 standardized drills notjust as exercises but as data
collection points. Turning that simple phone video
into a really sophisticated athletic profile using computer
vision and bio mechanics. Objective comparable data.
And that shift from subjective eye test to objective data
(25:57):
scoring is the absolute core transformation.
It's not just theory. We have the numbers over 100,000
users feeding data into the system and.
Critically, 147 players who've already secured professional
trials or national team looks directly because of that data.
Plus the buy in from top clubs like Chelsea and Burnley proves
it's stories like Ben Greenwood going from the app to a Chelsea
(26:17):
trial and then signing for Bournemouth or Jez Davies
signing for Burnley. They show the pipeline is real
and it works. It really feels like.
Technology genuinely leveling the playing field here, making
that dream of professional sportpotentially accessible based on
merit, on measured ability, regardless of where you start.
It validates the talent that wasalways there, just hidden.
(26:39):
Exactly. It removes the.
Obscurity caused by simple logistics or economics.
And you know the implications here?
They ripple out far beyond just soccer or even sports.
How do you mean? Well, think about it, if
artificial intelligence can use a standard smartphone and some
standardized tasks to objectively and efficiently
identify world class athletic talent, something previously
(27:00):
reliant on years of expensive travel, human intuition and
subjective networks, then what other fields are next?
Think about other highly specialized areas, maybe certain
types of creative talent, technical skills, problem
solving abilities, Fields currently dominated by
traditional networks. Interviews, subjective
assessments, geographical hubs, you're saying could AI?
Do a similar thing there. Create objective, accessible
(27:22):
pathways based on demonstrated ability, regardless of
background or location. It's the big question, isn't?
It if AI can democratize the search for elite athletes this
effectively, what other domains currently locked behind
subjective gates and traditionalstructures are right for this
kind of technological disruption?
That's something for you to really Mull over.
Where else could AI uncover hidden talent the world is
(27:45):
currently missing?
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