AI Software That Can Change The Horse Racing Industry

We didn’t believe that there would be a time when we would talk about artificial intelligence technology entering the traditional world of horse racing, yet here we are.

This means that AI is literally everywhere, and there isn’t a single industry that’s left unimpacted by this technology, either directly or indirectly, and for the better or worse. And as it seems, it is already changing the horse racing industry in many different ways. Ways that we didn’t imagine will change for centuries.

But before you get all excited about having an AI superbot that will accurately predict the winner of a race, that’s not the case here. Horse racing is still a very unpredictable sport, and even AI with mountains of data cannot figure out which horse is going to win. So, no, AI didn’t ruin betting.

The thing that AI is changing in the horse racing industry is safety, analytics, data collection, automation, and making everything easier to manage.

Sleip Can Turn an iPhone Into a Gait-Analysis Tool

The best way to explain the AI change in the horse racing industry is to see what’s already happening in the sport. That way we can get a vague idea of what it will look like in the future.
One of the best examples is Sleip, which is a Swedish equine tech company using computer vision to analyze how horses move.

We’re talking about a remarkably simple idea, yet it has the power to change the entire industry.
You basically record your horse trotting with your phone, upload the video, and then the app uses artificial intelligence with more than 100 anatomical points to measure subtle asymmetries in areas including the head, withers, and pelvis.

The tech can spot even the slightest imperfections that are impossible for trainers to see with the naked eye. However, this isn’t a diagnostic tool; let’s get that thing straight. It is a technology that measures movement and provides objective information so professional vets can interpret alongside their normal examination.

For racehorses, longitudinal monitoring may be particularly valuable. Sleip's Trends feature allows users to compare gait measurements over time, creating an individual baseline for each horse rather than judging every recording in isolation.

The company says trainers and regulators, including organizations connected with Hong Kong, Britain, Australia, and New York racing, have increasingly used this type of longitudinal gait information around training and pre-race assessment.

A trainer who sees the same horse every morning already develops an extraordinary eye for tiny changes.
When you think about it, even fans can use this app. Imagine you’re attending the Breeders’ Cup, and you record the horses before they get behind the starting gate, put them through the app, and it will tell you their advantages and disadvantages, or problems they face. Yes, some might say a misuse of the tech’s power, but we don’t do any harm, right?

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StrideSAFE Is Looking for Trouble Before It Becomes Obvious

Another fascinating system is StrideSAFE.

Instead of analyzing smartphone video, StrideSAFE uses a lightweight sensor placed in the saddle cloth while a Thoroughbred races. The system records gait and motion data at high frequency, then uses algorithms developed from a growing database of racing performances to identify horses whose movement patterns may warrant closer veterinary attention.

As of 2026, StrideSAFE says the technology has collected data from more than 75,000 starts and is deployed at tracks across Kentucky as well as Belmont and Saratoga. Its software is designed to identify movement patterns associated with risks such as condylar and sesamoid fractures, providing reports that trainers and veterinarians can review after racing.

That could become one of the most important uses of AI in the entire sport.

Arioneo Wants to Understand the Entire Athlete

Where Sleip concentrates heavily on movement analysis, Arioneo is building something closer to an equine performance ecosystem.

Its EQUIMETRE systems combine sensor data with software capable of analyzing heart rate, ECG, speed, locomotion, and recovery during training. Arioneo says its AI models are trained on billions of equine data points and can automatically interpret sessions, recognize exercise types, and benchmark a horse against comparable data.

This matters because trainers already collect a great deal of information.

The problem is turning it into something useful.

A horse might record a particular speed during morning work, but speed alone says very little. How hard was the cardiovascular effort required to produce it? How quickly did the horse recover? Did stride frequency change? Was the work more demanding than a similar session three weeks earlier?

Arioneo's platform is designed to put those signals together rather than treating each number separately. The company now also offers an AI-based vision app that tracks 31 key points on a horse from ordinary video and estimates locomotor asymmetry.

AI Could Also Make Heart Monitoring More Practical

Cardiac data is another promising area.

Arioneo's newer racing system is designed to collect ECG and locomotion data while horses are actually competing rather than only during controlled training. Its software can automatically screen recordings for arrhythmias and generate reports for trainers, veterinarians, and racing institutions.

That is a significant change.

Traditionally, gathering high-quality ECG data during maximum-intensity racing has been technically difficult. A horse galloping flat out under race conditions is not exactly volunteering for a relaxed cardiology appointment.

Software capable of processing those recordings at scale could help researchers understand what happens to the equine heart during genuine racing effort rather than relying entirely on laboratory or training conditions.

AI Could Change Breeding Too, but This Is Where Caution Matters

Breeding is another area where machine learning will inevitably attract attention.
The industry already has enormous databases containing pedigrees, race records, surfaces, distances, and performance histories.

In theory, AI could identify combinations of bloodlines associated with particular racing traits or compare prospective matings across far more variables than a human could comfortably process.

Final Thoughts

The sport is already changing, and with this fast rate of advancements in the world of AI, things are changing really quickly. The good news is that AI is currently centering on safety and analytics, but soon the tech will touch things like experience, convenience, and many other segments.