Of everything mentioned in the Fall 2025 “This Season on Zwift” Press Release, Zwift’s planned release of personalized recommendations carries the most potential as a game-changing feature. Launching this November, the promise of these AI-powered recommendations is that your fitness data and preferences can be used to serve up a recommended activity, any time you ask.
Let’s dive deeper into this, Zwift’s first public use of AI, and discuss planned features and future potential.
The Challenge: Maximizing Training and Fun for Everyone
Veteran Zwifters like myself are always asking for more. More roads, new features, fresh events. But do we consider what Zwift is like for someone new to the game and/or new to cycling?
It must be overwhelming.
There are thousands of events each week. Hundreds of routes you can ride and workouts to choose from. Thousands of riders milling about, around the clock.
In addition to all that content, numerous metrics are floating around that new cyclists don’t understand. What is FTP? Why does Companion say I’m “overreaching,” and how is that tied to my Training Score and Stress Score? What is XP, what are Drops, and do I care? What’s a good weekly goal? What’s an ideal cadence? Is my heart rate too high? How does Zwift Racing Score work? And let’s not even talk about zMAP and zFTP…
On top of all this, consider that, while every Zwifter wants to maximize their training results, everyone is targeting different results. Some are training for a particular outdoor event. Some want to lose weight. Some are just looking to maintain fitness until they can head outside again, while others are dedicated indoor riders training to win Zwift races. And fitness levels vary: while one rider might consider a full hour on the trainer to be a max effort, another may need two hours before it qualifies as a challenge.
A New Solution?
Zwift has built an ecosystem that can be leveraged to build cycling fitness efficiently and effectively, but many customers need help figuring out how to make that happen.
In the past, Zwifters who wanted to train with intentionality may have paid a cycling coach for a training plan, or dug in and done their own research, or perhaps asked a knowledgeable friend for advice. Zwift’s personalized recommendation engine will soon be the new option on this list. And it will be front and center in the game and Companion, a flagship feature continuously improving thanks to the constant influx of fresh data.
How It Works
No, I’m not going to dive into the depths of LLMs and other AI tech. But let’s talk about how Zwift’s personalized recommendations will work from the perspective of a common Zwifter.
Here’s the first screenshot Zwift shared, showing the beta personalized recommendation block at the top-left of the homescreen:
A few things to note here:
- The interface is very simple. If you want to take Zwift’s recommendation, just click “Start Ride” and go.
- The card explains why this activity was recommended: “This ride fits within your typical weekly activity duration and will help maintain your current fitness level.”
- It also notes the estimated activity duration, distance, and elevation.
If you want to do something different from what Zwift recommends, there’s a shiny “Tune” button, which takes you here:
The Tune screen gives you access to a vast array of recommendations, but through a very simple interface. There are just two things you can tune:
- Activity Type: choose between riding a route, a workout, an event, or hopping into a RoboPacer group
- Activity Length: click an arrow to generate a recommendation that is longer or shorter than what you’re currently seeing
The secret sauce, of course, is the recommendation engine at work behind the scenes. Since it is constantly learning from your activities and feedback, the recommendations it puts forth – regardless of the tuning options you choose – will be tailored to you. That means:
- Routes you like to ride, and perhaps routes whose badges you haven’t yet earned, especially if they’re the type of route you typically ride
- Workouts that help you improve a particular weakness, or work toward a fitness goal
- Events you’ve enjoyed in the past, or similar events
- Robopacer groups riding at the pace you would typically ride
Already working through a training plan, or working with a coach? No problem. Zwift tells me that, if you’re using a third-party workout provider like TrainerRoad, their workout of the day will take preference as the recommendation.
Companion and Game
Zwift says, “Personalized Recommendations will display both in the home screen in the main Zwift App and also in Zwift Companion.” That’s a very good thing, and I’m hoping the tuning tool is also available in Companion, so we can dial in our next activity before hopping on the bike.
Related New Features: Outdoor Connections and Goal Auto-Adjust
Zwift announced two features/changes rolling out in September that will work in tandem with personalized recommendations.
First, an improved onboarding experience will help more Zwifters hook up connections to Wahoo, Garmin, and Hammerhead so their outdoor rides are automatically brought into Zwift and included in key fitness metrics. Outdoor connections launched back in April 2025, and Zwift knows that if riders do significant training outdoors, Zwift needs to see those activities before providing helpful day-to-day recommendations.
Second, Zwift is rolling out the option to have your weekly goal auto-adjust. Instead of having a static goal to hit a particular number for kilojoules, stress points, calories, distance, or time, Zwift will use your recent activities to “adjust your upcoming weekly target goal, helping to support your continual development.”
When?
Zwift says personalized recommendations will launch in November 2025.
Of course, the launch of this feature doesn’t mean the end of its development. That’s not how AI works! I’ve already heard many positive things from Zwift staffers who use the tool internally, and they’re promising that the recommendation engine will continue to improve as it receives feedback from an increasing number of users.
(You can improve an engine like this by changing the parameters used to make decisions, but you can also improve it by feeding in post-activity feedback, such as a star rating scale asking something like, “How well did this activity help you work toward your fitness goals?” Zwift will be doing both.)
What About Other Activities?
Ever since Zwift launched their Fitness Metrics in April, some Zwifters have been asking when running and other workout types will be included. This has been the only consistent complaint about Zwift’s fitness metrics, in fact.
It’s a fair question… because lots of Zwift riders don’t just ride. Many run, lift, ski, hike, swim… you get the picture.
For these athletes, Zwift’s Fitness Metrics, and therefore their personalized recommendations, may not prove useful until Zwift begins to support a wider variety of activities. And there are lots of activity types! As one reader commented recently, “After all, cycling is represented by about 8 of the ~180 activity profiles on a regular Garmin watch. In Strava, I believe cycling is 5-6 out of the 48 available activity types (but lots of activities there are logged under a false flag since the actual activity type is missing).”
Zwift has said they will support running in their Fitness Metrics, but they haven’t given an ETA. Hopefully they’ll figure out a way to do it sooner rather than later, and hopefully they’ll also figure out how to easily include other activity types.
Wrapping It Up
There are things about AI that concern me, such as search engines presenting AI-generated answers to questions and stealing traffic from actual content creators. (This impacts my bank account directly.) The unknowns of AI are even more concerning. Where will it all take us? What are the unintended consequences?
But using AI to deliver personalized recommendations? That’s a use case I can get behind. It’s been discussed for years, and some training platforms have actually done it. But if it can be done well by Zwift, in a way that leverages their massive community and content library, it will enhance the training of tens (hundreds?) of thousands of riders worldwide.
And that’s a big deal.
Your Thoughts
What do you think of Zwift’s plans to offer personalized recommendations? Share your thoughts below!
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