How is Artificial Intelligence (AI) In Gaming Changing The Market?

Like artificial intelligence (AI), the gaming industry is built on fun, creativity, and engagement. Since the inception of computers as we know them, video games have changed a lot.

From old-school Super Mario to Dota and Cyberpunk 2077, it has been a very steep rise. Even the expected new games like GTA 6 are expected to be even more intriguing and complex. So, it is going to be quite a ride, especially with the Generative AI maturing as we move forward.

Amidst all this, the main question is; what is the future of gaming?

By 2025, the ever expanding market is expected to grow into a ~$503 billion one. And there is surely no doubt, AI will be a very important factor in making games more realistic.

I’ll even go a step further and say probably, we might see for the first time a practical implementation of metverse.

This transformation is going to be fueled by various factors, such as rising gamers’ appetite for enthralling metaverse adventures, popularity of fantasy sports, increasing competition amongst developers, and adoption of emerging technologies like Artificial Intelligence (AI).

But how will the AI in gaming market impact the industry exactly? What will this new generation of games have in store for games? This article will explore these questions in-depth. 

AI in gaming market.

The little flashback of the AI in games

Games back in the day might not have been that interesting or immersive. But those definitely had a different experience. To be honest, nothing matches that even right now. 

This brings me back to the first ever game to implement AI in practice.

Pac-Man was one of the first games to use AI. It’s a classic known to most millennials but perhaps less familiar to Gen Z. So, let’s do a little intro.

It’s a maze game featuring a yellow circle (Pac-Man) as the player’s character. The main task was to eat the dots while dodging four colorful ghosts, each with its own personality—thanks to AI.

Blinky aggressively pursues Pac-Man. On the other hand, Pinky takes a more passive approach, Inky tries to cut off your path, and Clyde roams randomly. Sounds fun, right? Trust me it was actually fun and thrilling.

While the graphics and sound effects are dated compared to modern games, Pac-Man’s AI-driven pathfinding wasa game changer, making it a hit. You can even play it today via Google’s Pac-Man doodle.

Given the vast advancements in AI since Pac-Man’s era, how does the AI in gaming market look like?

Pac-Man was the first game to implement AI.

Examples of artificial intelligence in video games

Games continue to utilize AI in exciting ways, including allowing for more interactivity and realistic graphics. Here’s a look.

NPCs (non-player characters)

The extra characters we see in a game who act as if they are controlled by other humans are called non-player characters or NPCs. For example, the side characters in GTA Vice City. This is where the gaming industry uses the majority of AI.

If you notice all these characters have their behaviors and actions determined by AI algorithms and a set of rules provided by the developers. Do you remember the certain way the old lady used to walk in Vice City? 

Now, the use of AI for NPCs makes a game more interactive and opens up new ways to interact between players and non-players. At the end of the day, it is all about giving a more immersive experience and a human-like NPC, but AI achieves exactly that.

A popular game where NPCs are predominantly important is GTA’s franchise. It’s an open-world game where players are free to do almost anything they want, but what they do has consequences.

Without the NPCs, the game won’t have much to offer, which is precisely the reason for its popularity.

NPCs in GTA Vice City.

Image Enhancements and AI Upscaling

Another remarkable application of AI in gaming is to improve visuals via “AI Upscaling.” The core idea behind  is to transform a low-resolution image into a higher-resolution one with a similar appearance.

This technique not only breathes new life into classic games but also enables players to enjoy realistic visuals and resolutions, even on older hardware.

NVIDIA’s DLSS technology is just the right example of AI in image enhancements. NVIDIA researchers use AI-driven upscaling in games like “Cyberpunk 2077” and “Control,” to deliver higher-resolution graphics and improved frame rates, allowing players to alter a scene.

AI in gaming market.

Procedural Content Generation (PCG)

Video games come with multitudes of 3-D objects, characters, clothing, props, music, graphics, levels, quests, maps, and more. But giving you all this is not easy, if you look at it from a developers end – It’s complex, time-consuming, and surely requires tons of investment.

AI can be a game-changer here. By using AI in PCG, game developers can craft richer, more diverse worlds, simplifying these game asset generation at an accelerated rate to meet users’ demands.

Moreover, AI can also generate interactive narratives based on past storylines. For example, AI Dungeon 2, an innovative text-based adventure game, uses OpenAI’s GPT-3 language model to offer infinite adventures and possibilities.

In AI Dungeon 2, gamers can progress through the game by giving the relevant prompts and directing AI to create unique storylines for their characters to interact with.

AI Dungeon 2.


Going back to Pac-Man, how do the ghosts locate and chase the player?

The game’s AI uses algorithms like A* and Dijkstra’s to go from point A to point B in the game world. These algorithms help the AI to find the most efficient route along with avoiding obstacles and traps to reach the goal.

This feature can generally be seen in enemy characters or bosses as they assess a player’s location and find ways to interact or attack.


Procedural generation

Minecraft, which regained its popularity around 2019, is a classic example of a game that uses procedural generation to offer its fanbase unlimited varieties of worlds. It employs mathematics and AI algorithms to generate new content every time a new world is created.

Today, the gaming industry uses procedural generation to generate entire new areas as the player progresses, providing a much more immersive and unique experience.

It doesn’t take a genius to figure out that without artificial intelligence, creating such massive open-world maps manually would add months, if not years, to the game development process.


Player-Experience Modeling (PEM)

PEM is one of the most popular AI trends in gaming that mathematically models gamers’ experience and anticipates their preference for liking or disliking a game.

AI in player experience modeling analyzes the users’ competence and emotional status to adjust the gaming mechanism accordingly.

As per the gamers’ skill level, AI can increase or decrease the game’s complexity in real-time, making it more interactive and adaptive as per users’ interests.

Narration and dialogues

Words and expressions give life to a character. A well-thought-out story with succinct narration makes the game so much more captivating.

Voice actors are the primary source of dialogue for a game’s characters but the gaming industry is now dabbling in the use of synthetic voices.

Although the use of synthetic voiceover is still not widely used in games, I see it a rising adoption in the future.

Storytelling in games.

What are other key use cases of AI in gaming?

Here are some other use cases:

Data-Mining and Real-Time Analytics

The 2.5 billion global gamers generate approximately 50 terabytes of data every day, making it a big challenge for companies to monitor this data and take proactive actions before opportunities leave the door and players exit the game.

It is why gaming businesses increasingly use AI and machine learning in live streams for data mining and extracting actionable insights.

DemonWare, an online multiplayer game, is the best example of AI in gaming that uses real-time AI data analytics.

Player Sentiment Analysis

One of the most significant applications of AI in gaming is player sentiment analysis, which involves analyzing players’ feedback, reviews, and other data to gain valuable insights into their preferences for game levels, menu elements, or opponents.

By using AI sentiment analysis, game developers scrutinize player feedback to understand what aspects of games resonate most with them.

For instance, League of Legends, one of the most popular Riot Games, uses AI sentiment analysis to monitor player discussions across various platforms.

Based on this data, Riot Games developers can make informed decisions about game updates and improvements to enhance the gaming experience.

Increased interactivity

The biggest advantage of AI is that it can learn and grow as time goes on. Imagine the storytelling if the in-game characters could learn how individual players play the game, study their patterns, and tailor responses for a more unique and satisfying experience!

The best example of this is the Nemesis System in the Middle Earth series. Wherein the enemy orc hordes have hierarchies and the individual orcs have their own strengths, weaknesses, and relations to the horde members. 

Cheat Detection in Multiplayer Games

Cheating has been a big challenge in multiplayer games that negatively impacts the player experience and causes serious repercussions for gaming platforms.

Due to the growing risks of cheating in games, players worldwide find themselves insecure against their opponents who play evil tactics to gain unfair advantages.

So, there is a pressing need to use AI to analyze the players’ movement patterns and detect whether a user is cheating.

Many popular online games like PUBG already use AI to analyze the players’ patterns and prevent cheating. In fact, the game has made several headlines in the past to ban even professional players who cheat in PUBG.

Testing and Debugging

AI-driven testing and debugging tools can efficiently handle thousands of complex test cases at a much faster pace than humans can do. The automated tools can scan vast amounts of code to detect errors, identify bugs, and suggest fixes.

Automating these labor-intensive tasks will allow developers to spot all the little things that should be removed from the game structure and perform their jobs more efficiently, making game testing much faster and smoother. 

Testing and debugging with AI in gaming.

Future of AI in gaming

Video games are evolving fast. This is the reason why most multiplayer games only last a year or two without regular updates because new content and fascinating gameplay are two of the most essential features that users demand.

And there’s no way to create such dynamic gaming experiences without using artificial intelligence.

AI will eventually change video games across all platforms, from consoles to mobile phones. However, such a transition will not be easy for game developers. Still, considering the common interest in the domain, there will definitely be big breakthroughs in the near future.