10 June 2026

Sport Already Drowns in Data. It Does Not Yet Own the System That Reads It.

Sport runs on data more than almost any industry on earth, and the numbers are staggering.
Each SailGP F50 catamaran carries around 125 sensors generating tens of billions of data
points across a single sailing day, streamed to the cloud and back to the crews in roughly 150
milliseconds, faster than a blink. A Formula 1 car runs 300 or more sensors and produces close
to a terabyte of data over a race weekend, fed live to engineers who can spot a component
beginning to fail before the driver feels anything wrong. Baseball's Statcast system tracks 18
points on a player's body 30 times a second and now classifies every pitch thrown with a neural
network. The NBA captures the same kind of 3D pose data 60 times a second. In cricket,
Hawk-Eye records the three-dimensional path of every delivery, and a single IPL match
generates well over 100,000 data points.

This is how a broadcaster can tell you a car is about to catch another before it happens, or break
down exactly how a tack or gybe was executed. It is also how the smartest teams now win. The
Mumbai Indians improved their death-over wicket yield by close to a third in a recent IPL season
by feeding years of ball-tracking data through a model that found which batters are vulnerable to
which deliveries under pressure. The data was always there. What changed was a system that
read it and turned it into a decision.

That is the gap in most sports. The data arrives, much of it instantly, and then it mostly sits there.
Interrogating all of it, in the moment, still depends on a team of analysts pulling it apart by hand.

That is what agentic AI offers. Not another dashboard, but a system that manages the data,
answers the questions put to it, and acts on what it finds. Build it for one team, and it watches
continuously: flagging when a player or a component is drifting towards a danger zone, surfacing
patterns a human would miss, and answering a coach's question in seconds rather than after the
next training block. The information was always there. The system is what makes it usable.
This is the shift worth understanding, and it extends far beyond sport. The team does not buy
that capability off a shelf. It builds it, and it owns it.

Why Sport Is The Clearest Case

Money in sport behaves in a specific way. Clubs and teams will spend on athletes and on
machinery. They will not spend on the back office. They want to give fans the best possible
experience without sacrificing the revenue that funds it. That tension is exactly where this
technology earns its place, because it attacks the unglamorous, expensive operational layer
rather than the visible one.

Performance is only the start. The same logic runs through the broadcast and commercial
operation that sits behind every team and competition: scheduling, research, rights and copyright clearance, shooting schedules, production management, and accounting. These are the functions that consume hours and budget, and they are exactly the kind of structured, repetitive, rule-bound work an agentic system runs well. A copyright check that took an assistant an afternoon, a shooting schedule reconciled by hand, a production-management process held together by spreadsheets and chasing: all of it can be built into systems a business owns rather than bought as another subscription.
To see why owning matters, it helps to know what just happened to the model most businesses have relied on for a decade.

Benioff Calls Time on Traditional SaaS

The phrase doing the rounds is that Marc Benioff has declared SaaS dead. What he actually
said, on a recent earnings call, is sharper than the headline. It is “the end of software that makes
humans do all the work.” The man who built the largest software-as-a-service company in the
world, and arguably invented the category, is not burying software. He is burying the version that
needs an army of people to operate.

That should stop any business owner in their tracks. Five years ago, in sports media, we were
selling software-as-a-service as the future. Cloud production, subscription tools, everything
rented and remote. It was the trend. Now the person with the most to lose from saying so is the
one calling time on it.

He has a reason. The thing replacing it is already working, and it changes what a business can
own.

For thirty years, the deal has been the same. You pay a monthly fee, you log into someone
else's system, and your data lives on their servers, shaped to their product. You never own the
tool. You rent access to it, and when you stop paying, you have nothing.

Agentic AI breaks that arrangement. Instead of buying a finished product and bending your
business to fit it, you build the system you actually need, and you keep it. The workflows, the
proprietary logic, the data, the way your particular operation runs: all of it sits inside something
you own rather than something you lease. When a process changes, you change the system.
When the market moves, it moves with you. This is the work AgenticScale does: building
bespoke agentic systems for a business and leaving that business owning them, rather than
selling another subscription. They have been at it for eleven years, well before the current noise,
which is worth knowing in a field crowded with firms that arrived last year.

The Part You See, and The Part That Pays

There is a real difference between generative and agentic AI, but the industry keeps blurring the
line.

Generative AI produces an output. You ask, it makes: a clip, a summary, a line of text. The
visible layer, the part that demos well. Agentic AI runs a process. It holds a goal, keeps context,
and takes the sequence of actions needed to reach it, calling on tools and systems along the
way, with a person supervising rather than operating. One writes the quote. The other reads the enquiry, prepares the quote, checks it against your pricing, sends a holding note if information is missing, and files the result. One makes the thing. The other runs the function. The cost of a business is not in producing the odd document. It sits in that surrounding work, and that is the layer that this changes.

The Agent You Can Message

Here is what it looks like day-to-day, and it is closer than most people think.
Picture a system you reach through WhatsApp, the same way you message a colleague. A chief
executive can ask how the marketing department is performing, what revenue looked like last
month, which clients have gone quiet, and get a straight answer in seconds. No meeting. No
asking someone to pull a report. No waiting until Friday.

That is a different kind of oversight. A leader spends much of the week chasing information that
already exists somewhere in the business but sits trapped in a system, a spreadsheet or
somebody's head. A system with access to those sources collapses the distance between a
question and its answer. The result is a broader command of the business, held by the person
responsible for it, without adding headcount to provide it.

The Value You Can Keep

There is a further consequence that owners and investors should note. When you build
proprietary systems rather than renting generic ones, you create something with its own value.
The methods, the logic, the way you have taught a machine to run a particular process: these
can be protected, and protected assets increase a business's value.

The research here is firmer than the hype around it. A 2026 Federal Reserve Bank of Chicago
study, looking at thirty years of innovation, found that a firm's market valuation rises on average
by $71 million following an AI patent, a larger jump than for any other type of patent, and well
above the $35 million typical of a non-AI patent. Firms that develop AI patents grow faster in
revenue, employment and capital than those innovating in other ways. Harvard Business School
research puts the same effect another way, finding AI patents trade at a premium of around $3
million each over comparable non-AI patents in the same field.

A caution worth stating, because serious readers will check. The same Chicago Fed study is
candid that this effect shows up strongly at the level of individual firms but has not yet appeared
in the economy-wide figures, because too few firms have adopted the technology to move the
aggregate. Read correctly, that is the opportunity, not the catch. The advantage is available now
precisely because most have not taken it.

The Objection, and The Answer

The serious objection comes from businesses with real intellectual property to protect. A chief
executive running a research-heavy firm will say, reasonably, that they will not let an outside
system anywhere near their crown jewels. They would rather buy something off the shelf, plug it
in, and pull it out if it fails.

The honest answer is that owning the system addresses the concern, not creating it. These
models run inside your own environment. Private deployment, on your infrastructure, with your
data never leaving your control. You can run them on hardware that sits under a desk. The
system learns your business because it lives inside it, and nothing goes out to a third party to
make that happen. This is the model AgenticScale builds to: private deployment, on the client's
own infrastructure, with the client owning what gets built. The off-the-shelf product is the one that
sends your data somewhere else. The owned system is the one that keeps it home.

Mistakes, Memory and Legacy

Two things are worth saying plainly to anyone weighing this up. First, expect mistakes. An agentic system will get things wrong, especially early on, just as a new team member will. The difference from a static tool is that it learns, like an employee, and can also rewrite and store code in its memory. An employee can do that, but they take that knowledge with them when they leave. A correction made once is stored and applied thereafter. The system that errs in week one is more reliable by week ten, and the improvement compounds rather than resets.

Second, there is a legacy for owners in this. A business is a collection of processes, and
processes age. Built the usual way, they need a periodic, expensive overhaul. A system tasked
with staying current can track how a function should evolve and rebuild it as standards move, so
the operation does not quietly fall out of date while attention is elsewhere. For an owner thinking
about what the business is worth in five or ten years, that is not a small thing.

Beyond Sport

The same shift is running through mining, power, retail, construction, restructuring, recruitment
and professional services. AgenticScale is already doing significant work in mining and energy,
sectors that look nothing like sport but share the same problem: vast operational data, expensive
manual processes, and systems that do not talk to each other. A restructuring firm facing
distressed assets is exactly the place where a forced rethink of the operating model makes
sense, because the old cost base no longer holds. A recruitment business buried in candidate
data, or a construction firm slow to return quotes, can have a system that reads, answers and
responds the moment it is asked. The sector changes. The principle does not.

The pattern is consistent. The visible layer of AI, the content, gets the attention. The operational
layer, the part that runs the business, is where the cost sits and where the value is won. The
companies that come out ahead will not be the ones with the best demo. They will be the ones
who rewired how they run, on systems they own, before their competitors did.

A team that owns the system and reads its data, rather than renting a dashboard, has built
something it keeps. So has every other business that makes the same choice. Firms like
AgenticScale exist to build exactly that across sport and well beyond. Benioff has read the
direction of travel. The question for everyone else is whether they move while the advantage is
still there to take.

LCA advises businesses across sport, media and beyond on commercial strategy and where to place
capital as the operating model shifts. When there is a fit, we introduce you to the people who build these systems. If that is where your business is heading, let us talk.