In the first episode of AppLovin's 'Coffee & Creative' series, SparkLabs team members Jessica Dolan, Mike Cruz, and Jaden Cheng share their journey of integrating AI into ad production, from initial exploration to full adoption. They formed a task force of early adopters to test over 50 generative AI tools (e.g., ChatGPT, MidJourney, DALL-E) and found AI particularly useful for ideation, scriptwriting, and visual concepting. After successful AI-generated ad creation, they emphasized understanding tool syntax and leveraging online resources.
Crucially, SparkLabs fostered an AI-friendly culture by organizing team-wide testing events to reduce resistance and ensure smooth adoption. Despite AI's rapid evolution, they underscore that human creativity remains central. Key actionable insights for ad operations decision-makers include: (1) start with a dedicated task force to evaluate AI potential; (2) prioritize team-wide experimentation over individual efforts; (3) use AI for creative upfront tasks; and (4) maintain flexibility as tools evolve.
The webinar is available with Korean subtitles.
You Might Also Like
Liftoff(Vungle)Webinar Recap: Generative AI in Mobile Ad Creatives
Generative AI enhances mobile ad campaigns by enabling rapid creative ideation, testing, and optimization. Experts emphasize using AI for scalable testing, maintaining brand compliance, and leveraging quality data for better performance.
AppLovin広告クリエイティブはAIによって革新されたのか
Generative AI streamlines ad creation by automating tasks like copywriting and animation, reducing production time and costs. However, it complements rather than replaces human creativity, which remains essential for strategic thinking and emotional resonance. Brands should use AI to enhance efficiency while maintaining originality and ethical oversight.
Liftoff(Vungle)AI and ML in Ad Tech: Understanding the Key Differences
AI mimics human intelligence while ML uses data for pattern recognition. In ad tech, AI enables real-time decisions and creative generation, ML optimizes targeting through data analysis. Understanding both is key for effective ad budget allocation.
GoogleAds creativity and performance at scale with Google AI
Google Marketing Live introduces generative AI for ad creative, enabling brand-aligned asset generation, immersive shopping ads, visual storytelling on YouTube, and AI Overviews in Search. These tools scale production, boost conversions, and improve consumer confidence.
SensorTowerState of Web 2026: How AI Is Reshaping the Internet
AI assistants like ChatGPT, Gemini, and DeepSeek are reshaping web discovery, with traffic surging 86% YoY. Mobile now accounts for over half of global visits, yet desktop dominates engagement. Search and social remain dominant discovery channels, but AI users convert at higher rates (e.g., Amazon Rufus shoppers convert nearly 2x). For ad ops, optimizing for AI-driven traffic and cross-platform user behavior is critical.
AppsFlyerHow Gaming, Finance, and E-Commerce Marketers Use Claude and AppsFlyer MCP
AppsFlyer MCP connects Claude directly to live attribution data, replacing manual reporting and CSV exports. Gaming teams catch budget anomalies overnight, finance teams compress multi-hour analysis into minutes, and e-commerce teams close the gap between measurement and spend decisions. Setup takes under 60 seconds, enabling real-time queries on channels, cohorts, and ROAS. The key insight is that AI-powered analysis requires live data connections, not stale exports.
AdjustWWDC26: Siri AI, Foundation models, updates for mobile marketers | Adjust
WWDC26 focused on AI, with minimal changes to iOS attribution. Apple introduced Foundation Models, Core AI, and App Intents updates, but no significant AdAttributionKit or SKAN updates. For ad ops, this means continuity in measurement strategies. Key AI announcements include Siri AI, Xcode 27 agentic coding, and cross-developer subscription bundles. The lack of attribution changes provides stability for teams optimizing existing iOS measurement approaches.
AppsFlyerThe Signal Economy Goes Live: Takeaways from MAU Vegas 2026
At MAU 2026, the industry agreed that attention, not production, is the bottleneck. Cross-platform web-to-app attribution is now achievable with AppsFlyer's mobile-grade measurement extending to web, giving ad ops a unified view. AI is in production, with Square's team shipping six live workflows. Web-to-app is the most efficient top-of-funnel for app businesses, and retention overtakes acquisition. Ad ops must prioritize clean signal layers and incrementality testing over single-metric attribution.
More from AppLovin
Why pursue TikTok? A vision for economic expansion
The blog highlights the strategic rationale for a TikTok merger, emphasizing the performance advertising gap where TikTo...
Examination of e-commerce data practices
The article examines how identifiers like those from Google and Facebook flow across e-commerce sites via standard integ...
Performance Advertising: How we drive value and handle data
AppLovin explains its AI-driven advertising platform, Axon 2, which has quadrupled ad spend to a ~$10B run rate. The eng...
A Note from Our CEO: Discussing Web Advertising Opportunity and Unpacking Pixels
AppLovin CEO Adam Foroughi refutes a short report questioning its e-commerce ad business and pixel practices. He highlig...
10 tips for user acquisition on a budget
User acquisition on a budget is achievable through a mix of organic and low-cost paid strategies. Key tactics include op...
How app technical health impacts LTV—and what to do about it
Performance issues like crashes and slow load times directly reduce user retention and LTV. With 60% of users uninstalli...