Changing the Industry: AI Insights in Game Development

Euro 2024 is dominating the summer headlines as events in Germany take centre stage in the sporting world – occupying the thoughts of fans and punters assessing the best sign up betting offers. One of the standout aspects of the tournament has been excellent refereeing. 

Aided by the latest AI technology, the VAR and ball tracking systems have performed almost flawlessly – leading some to predict that AI may replace referees entirely within 30 years. That may sound far-fetched, but the impact of AI in other industries suggests the idea may not be so fanciful.

Elsewhere in the entertainment business, the use of AI has grown exponentially in the realm of computer game design. In many ways, computer games are a natural bedfellow for AI. Nevertheless, the Artificial Intelligence-led improvements to the gameplay experience have been impressive.

Personalization

One of the primary uses of AI insights is to create a more personal gaming experience. AI algorithms analyse player data to tailor experiences to individual preferences. For instance, AI can use a player’s skill level to adjust game difficulty in real time.

An AI “Director” can dynamically alter the game environment and enemy toughness based on player performance and behavior. These aspects keep the gameplay experience fresh and engaging- providing a challenge for experienced gamers and decreasing the chances of novice players becoming frustrated.

Dynamic Content Generation

Procedural content generation, powered by AI, can create expansive and varied game worlds without requiring extensive manual input from developers.

In games like “Fallout” and “Skyrim,” vast, unique landscapes are generated algorithmically – saving development time and ensuring that each experience is unique. In the modern gaming era, the boundaries of a sandbox-style game have been all but blown away.

Player Behaviour Analysis

Understanding player behaviour is crucial for creating engaging gameplay experiences. AI and machine learning models analyse vast amounts of data to identify patterns and what individual players want from their gaming sessions.

This information can predict future behaviour, allowing developers to proactively adjust game features or introduce new content that aligns with player interests.

For example, AI can identify if players are struggling with a certain level or mission. Developers can then modify the game’s design to improve the flow – making things a little easier if necessary.

Enhancing NPCs and Opponent AI

Non-playable characters (NPCs) and opponent AI are essential elements of many games. AI insights allow developers to create more realistic and challenging NPCs that can adapt to player actions. Advanced AI techniques enable NPCs to learn from player behaviour and adjust their strategies accordingly.

This results in more unpredictable and engaging interactions. For instance, in strategy games, opponent AI can change tactics based on the player’s strategy, providing a more competitive and replayable experience.

Game Testing and Quality Assurance

AI also plays a pivotal role in game testing and quality assurance. Traditional game testing is a time-consuming and labour-intensive process. AI-driven testing tools can simulate thousands of gameplay hours in a fraction of the time it would take human testers.

These tools can identify bugs, glitches, and balance issues. By analysing gameplay data, AI can also help developers understand how players interact with the game and identify areas for improvement.

Enhancing Storytelling and Narrative Design

Narrative-driven games benefit from AI by creating branching storylines that adapt to player choices. AI can analyse player decisions and preferences to influence the narrative direction, ensuring that each playthrough is distinctive.

Games like “Detroit: Become Human” use complex decision trees and AI to offer multiple endings and varied story paths based on player choices. This dynamic storytelling keeps players invested, as their choices have a meaningful impact on the game’s outcome.

Real-time Feedback and Updates

AI enables real-time feedback and updates, ensuring that games remain relevant long after their initial release. By continuously monitoring player behaviour and feedback, developers can quickly address issues and introduce new content that resonates with the community.

This approach is evident in live service games like “Fortnite” and “Apex Legends,” where frequent updates and events keep the player base active and engaged.