AI in Golf: How Smart Tech Is Changing Golf Coaching

 In golf, “AI” usually isn’t one single thing. It’s a stack of techniques working together: 

Put simply: AI compresses the time between seeing a swing and knowing what to do next.

1) Swing Analysis on Everyday Video 

This is the category most golfers notice first because it removes friction. Instead of “book a lesson” or “rent a bay,” a golfer can record a swing and get structured feedback quickly. 

Modern systems typically do things like: 

The big unlock here is accessibility: the best analysis is the one you’ll actually use repeatedly.
 
2) Launch Monitors + AI Layering
 
Launch monitors have been around for a while, but AI makes them more than just numbers. Systems like TrackMan and Foresight Sports can pair measured ball/club data with pattern recognition, gapping logic, and smarter practice planning—especially when combined with repeated sessions over time.
 
3) On-Course Strategy and “Strokes Gained for Humans”
 
AI also shows up in shot tracking and caddie-style guidance:
 

Examples in this world include Arccos, Shot Scope, and Garmin—each approaching the same goal: better decisions with fewer guesses.
 
4) Fitting, Equipment Optimization, and Personalization
 
AI can help connect swing characteristics to equipment choices. In the simplest form it’s clustering: “players like you tend to benefit from X.” In more advanced setups it becomes a recommendation engine that blends:
 

AI won’t replace a good fitter, but it can make fittings more efficient—and can help golfers maintain consistency when something changes (fitness, speed, injury, seasonality).
 
5) Coaching Workflows at Scale
 
AI is also changing how coaching is delivered:
 

Platforms like Skillest and training businesses like GOLFTEC benefit from AI-driven organization even when a human coach remains the core.
 
 
The Hard Part: Turning “Data” Into “Next Step”
 
Golfers don’t want more numbers—they want clarity:
 

Great golf AI does three things well:
 

That’s the difference between a novelty app and something golfers keep using.
 

DeepSwing fits into the “mobile swing analysis + feedback loop” category—but the real value is in how it tries to reduce friction between capture → understand → compare → share. 

Here are the parts that matter from an AI-in-golf standpoint: 

Fast feedback from phone video 

The core promise is that a golfer can use a normal camera workflow and still get structured insights. This matters because most golfers don’t practice in a lab—they practice on a range, in a net, or in a simulator setting where convenience wins. 

Scoring + progress mindset 

A scoring dashboard approach is important because improvement in golf is rarely linear. If the app can consistently score key checkpoints (even imperfectly), it gives golfers a way to: 

Side-by-side comparison that’s actually useful
 
Comparing two synced videos—your swing vs your previous swing, or your swing vs a model—solves a real pain: it’s hard to see change when you’re emotionally attached to the “feel” of the swing.
 
Drawing + coaching-style annotation
 
Golf feedback is visual. Being able to draw lines, paths, and checkpoints turns abstract advice into something you can replay and understand. That also makes remote coaching and sharing much more effective.
 
Export with anonymity (blur/emoji)
 
This is a small feature that supports a big behavior: sharing. Golfers post swings to friends, coaches, or communities. If anonymity is easy, more people will share—meaning more feedback, faster learning, and more organic growth.
 
Device-to-device streaming (“Mirrorvision” concept)
 
A feature that lets you move the experience between devices can reduce session friction: phone for capture, bigger screen for review. Anything that makes the loop smoother increases practice consistency—which is ultimately what gets results.
 
 
Trust, Privacy, and What Golfers Should Watch For
 
As golf AI gets more personal, a few things matter a lot:
 

The next wave is likely to be less about “more metrics” and more about “more guidance”: 

In other words: AI becomes the “always-on assistant” while humans stay the “meaning and strategy” layer.