AI Characters in Games: How NPCs You Can Talk To Work

In the game, the blacksmith will tell you for the fiftieth time how hard it is to find good steel. Dialogue trees have worked the same way for decades: writers write all the lines, actors record them, and the player chooses from a few options. Generative AI is attempting to break this mold. Characters should understand what you tell them, respond in their own words, and remember previous conversations. How does this work, and what aspects of it are already a reality?

How a conversation with an AI character works

Instead of choosing from a menu, the player speaks into a microphone and the character responds. Behind the scenes is a chain of several technologies that must all happen in a fraction of a second.

From Voice to Response

First, a speech recognition program transcribes the player’s voice into text. This text is fed into a language model for which the developers have predefined the character’s role: personality, knowledge of the world, and goals. The model generates a response, which speech synthesis converts into voice, and the facial animation system adjusts the character’s lip movements accordingly. This principle is also described in technical documentation for developers of game AI tools.

Why These Models Are Smaller

Game AI characters do not use massive universal models, but rather small language models tailored for role-playing and working with data about the game world. They are smaller, so they can run directly on the player’s computer alongside the graphics.

Character memory and how games handle it

A language model doesn’t remember anything on its own between conversations. Therefore, the game must provide it with relevant information. The common approach is to store records of conversations and events in a database, retrieve those relevant to the current situation, and add them to the prompt for the model. Technically, this is called searching using vector representations of text.

Thanks to this, a character can react to what you told them chapters ago and, ideally, call you out on a contradiction in what you’re saying. Similarly, information could “spread” among characters, so that behavior in one settlement influences how the character is received in another. However, this is still an ambition that some new titles are experimenting with—not yet the standard.

Will my computer be powerful enough?

Running the model on your own device makes sense for two reasons. It eliminates the need to wait for a response from a remote server, and developers avoid ongoing operational costs for each player. The trade-off is performance: the model consumes memory and processing power that would otherwise go toward graphics.

Practical experience confirms this. The first widely discussed game featuring characters powered by a small local language model was released in March 2025 as a life simulation, and the AI character add-on only worked on GeForce RTX graphics cards. So it’s not something that would run on just any computer.

What Doesn’t Work Yet

Despite the enthusiastic headlines, the technology is still in its infancy. According to available reports from 2026, there are only a few released games in which characters actually behave this way, and some major publishers currently have only prototypes.

• Cost. Running a language model for every player is expensive, especially with cloud-based solutions.
• Model errors. A character might say something that contradicts the game’s world or is uncomfortable for the publisher, so studios need testing and restrictions.
• Story control. Screenwriters lose the certainty that the player will see exactly what they wrote.
• Voice and voice actors. Synthetic voices raise questions about the work of voice actors and licensing.

What This Might Mean for Players

Most likely, AI characters won’t replace entire written stories. It’s more realistic to expect them to appear where free-form dialogue makes sense: in life simulations, in detective games involving interrogations, with voice-controlled teammates, or as supporting characters. More important than the technology itself will be how studios combine it with a high-quality script.

Conclusion

The technical foundations are clear: speech recognition, a small language model, search within conversation transcripts, and voice synthesis with animation. For now, however, they are held back by cost, hardware requirements, and the unreliability of the models. Until games emerge in which words carry as much weight as a sword, it’s important to distinguish between trade show demos and what you can actually buy and play.