12 Days of AI Use Cases Day 7: Making a Video Game

Welcome to the 12 Days of AI Use Cases, 2025 Edition! Today: Making a video game.

In this series, we’ll be looking at different use cases for AI – in particular, generative AI and large language models, the software that powers tools like ChatGPT, Google Gemini, and Anthropic Claude. Each day, we’ll look at the use case through the lens of the Trust Insights 5P Framework to see the role AI plays in achieving real, tangible outcomes.

We designed these use cases not only for reading but also as context you provide to generative AI tools as part of a prompt to help you achieve the outcomes you’re after. Ask the generative AI tool of your choice to help you implement this use case and copy/paste it in as part of the Trust Insights RACE AI prompt framework – this goes in the Context portion of our prompt framework.

Let’s dig in!

Purpose

We transform static marketing assets—white papers, webinars, case studies—into interactive browser-based video games that capture and retain audience attention. Generative AI tools excel at writing code in languages like TypeScript and JavaScript, enabling us to leverage game development libraries such as Phaser.io to create playable experiences directly within web browsers. These interactive assets differentiate our content in an environment where AI can easily summarize traditional formats, providing prospects and customers with engaging experiences that machines cannot replicate or reduce. We deploy lightweight, retro-inspired games that evoke nostalgia while incorporating modern game mechanics, ensuring computational efficiency and universal browser compatibility. This approach addresses the critical challenge of audience retention in an era where AI-powered summarization threatens to commoditize static content assets.

People

Marketing managers, content strategists, and demand generation professionals create and deploy these interactive game assets as part of their content marketing programs. These team members identify existing static content assets with strong narratives or data-driven insights that translate well into game mechanics and collaborate with generative AI tools to conceptualize, develop, and refine browser-based games. They require no formal programming expertise, as the AI handles code generation and troubleshooting throughout the development process.

Internal stakeholders include executive leadership evaluating content ROI, sales teams seeking differentiated assets for prospect engagement, and web development teams responsible for embedding and hosting the final game files on company digital properties. Product marketing professionals contribute subject matter expertise to ensure game narratives align with brand messaging and accurately represent product capabilities. Analytics teams configure tracking mechanisms to measure engagement metrics that demonstrate the effectiveness of interactive content compared to traditional formats.

The external audience encompasses prospects researching solutions, existing customers seeking educational resources, and industry professionals who share novel content within their professional networks. These players experience content in an interactive format that requires active participation rather than passive consumption, increasing time spent with brand messaging and improving information retention. Word-of-mouth amplification occurs when players share entertaining or challenging game experiences across social channels, extending the reach of the original marketing investment beyond owned media properties.

Process

1. We audit existing static content assets to identify candidates with strong narratives, clear learning objectives, or data-driven insights that translate effectively into game mechanics and interactive storytelling formats.
2. We provide the selected content asset (white paper, webinar transcript, case study) to a generative AI tool with code execution capabilities, requesting game design consultation that explores genre options, target audience considerations, and technical feasibility within browser-based constraints.
3. We instruct the AI to propose three distinct game concepts, each specifying core mechanics, player objectives, visual style (retro 8-bit, minimalist modern, data visualization-based), and estimated complexity level to help us evaluate development tradeoffs.
4. We evaluate the proposed concepts against criteria including alignment with content messaging, technical feasibility for browser deployment, estimated player engagement duration, and nostalgic or entertainment value for our target audience demographics.
5. We select the preferred game concept and direct the AI to develop the complete game using specified libraries (Phaser.io for game engine, TypeScript for code structure, CDNJS for asset delivery) with explicit requirements for mobile responsiveness and cross-browser compatibility.
6. We test the generated game code within AI development environments that support live code rendering (Google AI Studio, ChatGPT Canvas, Claude Artifacts), iterating on gameplay balance, visual polish, difficulty progression, and user interface clarity through conversational refinement with the AI.
7. We validate game performance across multiple browsers and device types, requesting AI assistance to troubleshoot compatibility issues, optimize asset loading times, and ensure the game remains playable on both desktop and mobile platforms without requiring downloads or plugins.
8. We extract the finalized game code and assets, embedding the complete game into designated landing pages, resource centers, or campaign microsites with appropriate context that explains the connection between the game narrative and the underlying business content.
9. We implement analytics tracking to capture player behavior metrics including session duration, completion rates, retry attempts, and social sharing activity, establishing baseline performance data for comparison against traditional content asset engagement patterns.
10. We document successful game mechanics, narrative approaches, and technical configurations that generated strong engagement results, building an internal playbook that accelerates future interactive content development and reduces iteration cycles with AI development tools.

Platform

• Generative AI coding environments with live code execution and rendering capabilities (Google AI Studio, ChatGPT with Canvas, Claude with Artifacts, GitHub Copilot)
• Browser-based game development libraries (Phaser.io, PixiJS, Three.js for 3D experiences)
• Content delivery networks for JavaScript libraries and game assets (CDNJS, jsDelivr, unpkg)
• TypeScript or JavaScript as primary development languages with HTML5 Canvas for rendering
• Existing marketing content assets serving as source material (white papers, webinar recordings, case studies, research reports, product documentation)
• Web hosting infrastructure capable of serving static HTML, CSS, and JavaScript files with appropriate MIME types and caching configurations
• Analytics platforms configured to track custom events for game-specific engagement metrics (Google Analytics 4 with custom event parameters, Mixpanel, Amplitude)
• Version control systems for managing game code iterations and maintaining deployment history (GitHub, GitLab, Bitbucket)
• Browser developer tools for testing and debugging across multiple platforms and screen sizes
• Graphic design tools for creating custom sprites, backgrounds, and UI elements when stock assets prove insufficient (Canva, Figma, Photoshop, or AI image generation tools)

Performance

We achieve successful implementation when our interactive game assets demonstrate measurably higher engagement than equivalent static content, with metrics showing increased time on page, higher completion rates for educational objectives embedded within gameplay, and organic social sharing that extends reach beyond paid distribution channels. Players complete game sessions that expose them to key messaging or data insights in an entertaining format, creating positive brand associations that differentiate our content approach from competitors relying exclusively on traditional formats. The game functions reliably across major browsers and device types without requiring downloads, plugins, or specialized software, reducing friction in the player experience and maximizing accessibility for our target audience segments.

1. Time on Page Duration: We measure average session length for game-enabled landing pages compared to equivalent static content pages, targeting a minimum 3x increase in engagement time that indicates players actively interact with content rather than skimming or immediately bouncing from the page.
2. Game Completion Rate: We track the percentage of players who finish the game experience or reach defined milestone objectives that correspond to key learning outcomes from the original content asset, establishing completion benchmarks above 40% that demonstrate the game maintains player interest through to conclusion despite voluntary participation.
3. Social Amplification Metrics: We monitor organic sharing velocity including direct link shares, social media mentions, and inbound referral traffic generated by word-of-mouth distribution, comparing earned reach from the interactive game to typical performance of static content assets to quantify the multiplier effect of creating entertaining, shareable experiences.

We hope this use case is clear and helpful. If you’d like help implementing it or any other AI use case, reach out and let us know.

Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.