- Primary Subject: ARC Raiders
- Key Update: Embark confirms machine learning is only used for movement, not combat adaptation
- Status: Confirmed (Developer clarification)
- Last Verified: February 20, 2026
- Quick Answer: No, ARC enemies aren’t evolving or studying players. Machine learning only improves navigation and movement, not combat behavior or targeting.
For several months, a theory has been making the rounds in the ARC Raiders community suggesting that the game’s robotic enemies are analyzing player behavior.
According to the theory, the ARC are supposedly analyzing movement patterns, identifying favorite hiding spots, and gradually evolving to counter specific habits.
Clips of suspiciously accurate Rocketeer shots or Leapers squeezing into tight corners have only strengthened that belief. To some players, it feels as though the machines are adapting in real time.
However, Embark Studios has since responded to those claims, and the truth is much less sensational. The confusion largely stems from earlier discussions about the studio’s use of machine learning.
What Does Embark Actually Use Machine Learning For?
In a recent interview with PC Gamer, ARC Raiders design director Virgil Watkins clarified exactly how machine learning is used in the game.
According to Watkins, ML is strictly limited to improving enemy locomotion — essentially teaching certain robotic units how to walk, traverse terrain, and navigate complex environments more smoothly.
It does not control their combat decisions, attack patterns, targeting logic, or tactical behavior. If a Bastion seems well-positioned or a Rocketeer fires at the worst possible moment, that isn’t because it has studied your past matches.
It’s because those behaviors were deliberately authored by designers and AI engineers. Watkins emphasized that what players interpret as evolving intelligence is simply the result of careful development work. The ARC feel smart because they were built to feel smart from day one.
The difference is especially important now that ARC Raiders operates as a PvPvE game; although it began as a PvE-centric project, its development pivot means players now have to manage threats from both aggressive robots and other players.
That compounded tension can make ordinary AI behavior feel deliberate, especially when you’re already expecting human opponents to strike.
Have Updates Made the ARC Smarter?
As patches refined pathfinding and addressed navigation issues, enemies such as the Leaper, Queen, and Matriarch began moving more fluidly compared to their launch state.
However, smoother movement does not mean the AI is becoming more intelligent, as its core behavior patterns remain unchanged.
The ARC do not adjust their strategies on the fly or react differently to individual players, though their effectiveness can create that impression.
Strong aggro logic, precise projectile timing, and environmental awareness can create moments that feel almost predictive.
A Tick latching onto you at exactly the wrong second or a Rocketeer anticipating your dodge can seem uncanny.
But the encounters feel reactive because of established behavior scripts meeting player choices, not because the AI is learning you.
In the end, Embark has clarified that ARC Raiders does not rely on machine learning to study or counter player behavior.
The technology is limited to navigation and movement, while combat behavior, aggression levels, and attack patterns are deliberately designed by developers using traditional AI systems. The ARC can absolutely feel terrifyingly intelligent.
They can punish careless movement, capitalize on exposed angles, and overwhelm players who underestimate them.
But they are not building profiles, tracking your tendencies, or learning from previous matches. They aren’t evolving. They’re simply well-designed.
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