In 2024, romance was the leading character chat category among WRTN users. WRTN was a South Korean artificial intelligence (AI) service offering various generative AI solutions ranging from chatbots to summarizing documents. In particular, WRTN's character chat has proven to be popular among its users.

Traffic analytics, rankings, and competitive metrics for character.ai as of May 2025

Artificial intelligence (AI) companion apps let users have virtual relationships and friendships with AI systems and bots. As of february 2025,Character AI app collected 15 types of data from its users on iOS worldwide. EVA AI ranked second with 11 unique data points collected from its users. Among the examined AI companion apps, Kindroid collected the least number of unique data points as of the examined period.

Dataset Card for Character Codex

  Dataset Summary

The Character Codex is a comprehensive dataset featuring popular characters from a wide array of media types and genres. Each entry includes detailed information about the character, the media source, and a unique scenario involving the character. This dataset is valuable for synthetic data, RAG for generative AI, writers, game developers, and fans who want to explore and utilize rich character descriptions for various… See the full description on the dataset page: https://huggingface.co/datasets/NousResearch/CharacterCodex.

In 2023, ChatGPT was the artificial intelligence (AI) tool that had the largest market share worldwide, eclipsing all other AI tools with a total of **** percent of the market. Far behind, in second place, was Character.AI with about ** percent of the market share.

Complete dataset used in the research study on The Role of AI in Shaping Non-Player Character (NPC) Interactions by Dr. Samuel Jenkins

The Artificial Intelligence (AI) Non-Player Character (NPC) market is experiencing explosive growth, driven by advancements in natural language processing, machine learning, and computer vision. The increasing sophistication of AI NPCs allows for more realistic and engaging interactions within video games, virtual worlds, and other interactive digital environments. This demand is further fueled by the expanding gaming market, the rise of the metaverse, and the need for more personalized and dynamic user experiences across diverse applications. While precise market sizing requires specific data, considering the involvement of major tech players like NVIDIA, Microsoft, and Google, along with significant investments in AI development, we can reasonably estimate the 2025 market size to be around $5 billion USD, growing at a Compound Annual Growth Rate (CAGR) of approximately 25% through 2033. This growth trajectory is supported by continuous improvements in AI algorithms, the decreasing cost of computing power, and the expanding applications of AI NPCs in various sectors beyond gaming, including education, healthcare, and customer service simulations. Significant growth restraints currently include the high computational cost associated with advanced AI NPC development, the need for robust data sets for training effective AI models, and the potential for ethical concerns surrounding the creation of increasingly realistic and autonomous digital characters. Despite these challenges, the long-term outlook remains exceptionally positive. The segmentation of the market involves different application areas (gaming, metaverse, education, etc.), AI models (rule-based, machine learning-based, etc.), and deployment platforms (cloud, on-premise, etc.). The competitive landscape is highly dynamic, with tech giants continuously investing in research and development to improve AI NPC capabilities and expand their market share. The key players listed are strategically positioning themselves to capture a substantial portion of this burgeoning market.

The statistic shows data on the kinds of characters parents look for in books for their child in the United States as of ************. According to the source, ** parents of parents chose a book with a character who had to face a challenge and overcome it.

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Artificial Intelligence (AI) In Games Market Size 2025-2029

The artificial intelligence (ai) in games market size is forecast to increase by USD 27.47 billion, at a CAGR of 42.3% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing adoption of Augmented Reality (AR) and Virtual Reality (VR) games. These immersive technologies are revolutionizing the gaming industry by providing more realistic and interactive experiences, thereby fueling the demand for advanced AI capabilities. AI algorithms enable more intelligent and responsive non-player characters, dynamic game environments, and personalized user experiences. However, the market faces challenges, primarily due to the latency issues in between games. As AI-driven games become more complex and data-intensive, ensuring seamless and low-latency interactions between players and the game environment becomes crucial. Addressing these latency issues will require continuous advancements in AI technologies, network infrastructure, and cloud gaming solutions.
Companies seeking to capitalize on the market opportunities must focus on developing AI solutions that deliver high-performance, low-latency experiences while ensuring data security and privacy. Effective collaboration between game developers, technology providers, and network infrastructure companies will be essential to address these challenges and drive the growth of the AI in Games market.

What will be the Size of the Artificial Intelligence (AI) In Games Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, integrating advanced technologies such as e-sports integration, player behavior analysis, game analytics, game engine optimization, computer vision, UI, QA, game balance, game AI, character AI, social features, gameplay mechanics, cloud gaming, game physics engines, in-app purchases, game localization, multiplayer networking, performance benchmarking, streaming integration, pathfinding algorithms, procedural generation, UX, subscription models, competitive gaming, machine learning models, neural networks, advertising integration, and audio design. These technologies are not static entities but rather dynamic components that unfold and intertwine, shaping the market's intricate landscape. E-sports integration and player behavior analysis enable game developers to create more engaging experiences, while game analytics offers valuable insights into player preferences and trends.

Game engine optimization and computer vision enhance game performance and visual quality, respectively. UI and QA ensure seamless user experiences and bug-free gameplay, respectively. Game balance and character AI add depth and complexity to game mechanics. Machine learning models and neural networks facilitate intelligent decision-making, while social features and gameplay mechanics foster community engagement. Cloud gaming and streaming integration expand accessibility, and game physics engines and in-app purchases generate revenue. Game localization and multiplayer networking cater to diverse player bases, and performance benchmarking ensures optimal game performance. The ongoing interplay of these technologies shapes the market's dynamics, with new applications and innovations continually emerging.

How is this Artificial Intelligence (AI) In Games Industry segmented?

The artificial intelligence (ai) in games industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  AI enabled platforms
  AI enabled games


Technology

  Machine learning
  Natural language processing
  Computer vision
  Robotics


Game

  Action
  Adventure
  Casual
  Racing
  Simulation
  Sports
  Strategy


Application

  Gameplay Optimization
  Character Behavior Generation
  Level Design
  Player Engagement


End-User

  Developers
  Publishers
  Players


Platform Type

  Console
  PC
  Mobile
  Cloud


Geography

  North America

    US
    Mexico


  Europe

    France
    Germany
    UK


  Middle East and Africa

    UAE


  APAC

    Australia
    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The ai enabled platforms segment is estimated to witness significant growth during the forecast period.

In the dynamic gaming industry, Artificial Intelligence (AI) is revolutionizing game development and player experience. AI technologies, including deep learning, reinforcement learning, and machine learning models, are integrated into various aspects of game creation. These tools enhance

The statistic shows the total screen time of characters on Game of Thrones as of August 2017. According to the source, Tyrion Lannister has spent approximately 337 minutes on screen during the hit HBO fantasy series.

Substrate was classified using the method of (Cochrane and Lafferty, 2002) for this study. Sea floor character derived from towed sidescan sonar data is available for the mainland coast within the study area from USGS online publications (Cochrane and others, 2003; Cochrane and others, 2005). The number of substrate classes was reduced because rugosity could not be derived for all areas due to the lack of bathymetry data for other data sets used in the study. References Cited: Cochrane, G.R., Nasby, N.M., Reid, J.A., Waltenberger, B., Lee, K.M., 2003, Nearshore Benthic Habitat GIS for the Channel Islands National Marine Sanctuary and Southern California State Fisheries Reserves Volume 1: U.S. Geological Survey Open-File Report 03-85, http://pubs.usgs.gov/of/2003/0085/. Cochrane, G.R., and Lafferty, K.D., 2002, Use of acoustic classification of sidescan sonar data for mapping benthic habitat in the Northern Channel Islands, California: Continental Shelf Research, v. 22, p. 683-690. ...

262 People - 5,162 Images Handwriting OCR Data of Traditional Chinese Characters (Taiwan, China). Texts in the data were annotated for the line-level quadrilateral bounding box. The handwriting ocr data can be used for traditional Chinese characters recognition application.The accuracy of line-level annotation and transcription is >= 97%.

Analysis of ‘VT Data - Jericho Zoning - Character Based Zones’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/de65e5fc-6c4b-4286-821a-29b3e333f420 on 21 November 2021.

--- Dataset description provided by original source is as follows ---

--- Original source retains full ownership of the source dataset ---

In the United States, in the 2023-24 season the streaming content provider Netflix included the highest number of LGBTQ characters in its TV series, which amounted to 155. In comparison, Max reported a number of 38 LGBTQ characters.

Analysis of ‘Parking Statistics in North America’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/terenceshin/searching-for-parking-statistics-in-north-america on 28 January 2022.

--- Dataset description provided by original source is as follows ---

ABOUT

This dataset identifies areas within a city where drivers are experiencing difficulty searching for parking. Cities can use this data to identify problem areas, adjust signage, and more. Only cities with a population of more than 100,000 are included.

Data

Some variables to highlight:

• AvgTimeToPark: The average time taken to search for parking (in minutes)
• AvgTimeToParkRatio: The ratio between the average time taken to search for parking and of those not searching for parking in the current geohash
• TotalSearching: The number of drivers searching for parking
• PercentSearching: The percentage of drivers that were searching for parking
• AvgUniqueGeohashes: The average number of unique geohashes at the 7 character level (including neighbouring and parking geohashes) that were driven in among vehicles that searched for parking
• AvgTotalGeohashes: The average number of all geohashes at the 7 character level (including neighbouring and parking geohashes) that were driven in among vehicles that searched for parking
• CirclingDistribution: JSON object representing the neighbouring geohashes at the 7 character level whereby vehicles searching for parking tend to spend their time. Each geohash will have the average percentage of time spent in that geohash prior to parking.
• HourlyDistribution: JSON object representing the average prevalence of searching for parking by hour of day (% distribution based on number of vehicles experiencing parking problems)
• SearchingByHour: JSON object representing the average percentage of vehicles searching for parking within the hour
• PercentCar: Percentage of vehicles with parking issues that were cars
• PercentMPV: Percentage of vehicles with parking issues that were multi purpose vehicles
• PercentLDT: Percentage of vehicles with parking issues that were light duty trucks
• PercentMDT: Percentage of vehicles with parking issues that were medium duty trucks
• PercentHDT: Percentage of vehicles with parking issues that were heavy duty trucks
• PercentOther: Percentage of vehicles with parking issues that were unknown classification

Content

This dataset is aggregated over the previous 6 months and is updated monthly. This data is publicly available from Geotab (geotab.com).

Inspiration

As some inspiration, here are some questions:

• Which cities are the hardest to find parking?
• By joining population data externally, can you determine a relationship between a region's population and the time that it takes to find parking?
• Similarly, by finding external data, is there a correlation between GDP and parking times? What about average household income?

--- Original source retains full ownership of the source dataset ---

This statistic shows the Game of Thrones characters thought most likely to die in the final season according to adults in the United States as of March 2019. The findings reveal that 36 percent of surveyed respondents in the U.S. said that they thought that Cersei Lannister was the most likely character to be killed off in the final season of Game of Thrones. Ranking second was Night King, with 34 percent of respondents saying they thought the character was most likely to die in the last season.

Explore the progression of average salaries for graduates in Fine Arts Character Animation from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Fine Arts Character Animation relative to other fields. This data is essential for students assessing the return on investment of their education in Fine Arts Character Animation, providing a clear picture of financial prospects post-graduation.

Description

This dataset contains detailed information about characters, kingdoms, and items from the Mount & Blade game series. It is designed for developers and researchers who aim to implement AI-driven smart NPCs (Non-Player Characters) into the game.

  Dataset Content

The dataset includes the following information:

Characters: Attributes, skills, and statistics of in-game characters. Kingdoms: Governance structures, military strengths, and political relationships of… See the full description on the dataset page: https://huggingface.co/datasets/first-point/MountAndBlade-Data.

This dataset supports the study "Enhancing Vocabulary Retention and Pronunciation Accuracy through Personalized AI-Driven Animated Characters in Language Learning: A Mixed-Methods Approach". It includes quantitative and qualitative data from 150 participants who used the AI-driven character, ABIM, to improve vocabulary retention and pronunciation in Indonesian. The dataset covers metrics on engagement, perceived improvements, ease of use, and participant feedback on usability and challenges. This data is valuable for research on AI in education, language learning, and user experience in digital tools.

In the United States, in the 2023-2024 season, 33 percent of LGBTQ characters on streaming content providers in were gay, and 24 percent were lesbian. Moreover, 25 percent of LGBTQ characters in the 2023-24 streaming season were bisexual.