Posted by
-
Summer Research Internship Program (SRIP)
-
Summer Internship Program
-
SLRI
-
SEE Learning
-
Pre-Placement Offer (PPO)
-
phd
-
pgdm bda
-
Opportunities
-
nova sbe
-
MDP
-
Marketing
-
IDA
-
Goa Institute of Management
-
GiveGoa
-
GIM Alumni
-
fpm non residential
-
Fpm
-
Executive fpm
-
Event
-
Dual Degree Programmes
-
Dual Country
-
Dr. Hanish Rajpal
-
Doctoral
-
CPPG
-
Convocation
-
Conference
-
Campus Placement
-
Alumni Success Stories
-
Alumni Reunions
-
Alumni Relations
-
Alumni Office
-
Alumni Impact
-
Alumni Events
-
Alumni Engagement
-
Alumni
-
Admissions
-
achievement
Date
What Games Teach Us About Building Better AI Products
Share this blog
Most AI products fail because the users don’t stick. You have to craft experiences that they want to play.
Neetika Kataria
Consultant- Product Management, Visiting Faculty- GIM
Ever wondered why you’ll grind for hours to beat a game level, but abandon most apps in less than 5 minutes? Games keep us hooked. But I have been curious- how? So, I spent time exploring and extensively researching gamification- understanding the core drives of human motivation.
As a Product Leader, I’ve experienced firsthand how understanding this is the key to elevate products from being “useful” to “truly loved”.
Modern AI Products That Feel Like Games
The evolution of the customer has accelerated over the past 5 years. The lock-down was the tipping point. It opened doors to limitless knowledge, awareness and unlocked expectations that the market is still adapting to meet. The 4-dimensional customer is more informed, more empowered, more impatient and more demanding. They walk in knowing options, pricing, and reviews, often better than the sales teams. They control the journey and expect choice without friction. They don’t like to wait. For them, speed is not an added bonus. It is hygiene. They are willing to pay a higher price, but they demand outcomes, not mere brand promises.
How to serve, delight and retain this 4D Customer
That is the million-dollar question. But the solution is not as complex or arduous as it seems initially. Build an effortless experience that minimizes the work customers must do to achieve their goal. Make it easy, fast and hassle-free for them to work with you. When brands reduce customer effort, it drives loyalty, lowers cost, and outperforms other delight tactics in service interactions. There is a clear metric for this as well – the Customer Effort Score.
-
ChatGPT (OpenAI):
Triggers Creativity & Curiosity
What works?
Users experiment endlessly with prompts, testing AI responses. The unpredictability of output keeps people engaged in its playful exploration. People turn it into role-playing, creative storytelling and productivity hacks.
PM lens:
ChatGPT succeeds because it gives users control, creativity, and surprise, essential for long-term engagement.
-
Replika:
Triggers Social Influence & Relatedness
What works?
AI companion that users “train” through conversation. Unlocks emotional bonds and attachment, combines it with social reward and personalization. Gamified elements: moods, conversation streaks, levels of intimacy.
PM lens:
Emotional engagement combined with personalized AI drives retention more than just the features.
-
Notion AI:
Triggers Accomplishment + Creativity
What works?
Users turn mundane tasks into playful productivity challenges. AI-powered suggestions + progress tracking = micro-wins. Users “level up” their knowledge systems while completing daily workflows.
PM lens:
AI becomes more than a tool, it becomes a playground for mastery, increasing adoption and retention.
-
Duolingo:
Triggers Development & Accomplishment
What works?
AI adapts lessons to skill level; gamification adds streaks, XP, and leaderboards. Micro-feedback ensures constant motivation
PM lens:
Habit formation happens when progress is visible and rewarding.
Fact (not fun):
Most AI Products fail
Here’s the uncomfortable truth that many product teams avoid: Most AI products fail. They don’t fail because the models aren’t accurate enough or the technology isn’t cutting-edge. They fail because users don’t stick. And my take on why they don’t stick is there’s simply no motivation.
What Can We Learn?
- Tay (Microsoft):
AI chatbot that learned from users spiraled into harmful outputs. Engagement mechanics without safeguards destroy trust.
- Early Foursquare: Hollow Progression
Badges and mayorships initially motivated users but lost meaning over time. Gamification must reinforce meaningful achievement.
Takeaways for Product Builders
Our role isn’t to obsess over the model’s accuracy. Our role is to ask:
- Why would a user want to use this daily?
- How do we make feedback rewarding, not tedious?
- How do users feel this belongs to them?
- What do users risk losing if they drop off?
- How do we turn adoption into a status symbol?
Every AI roadmap should have two parallel tracks:
1. Model Performance (accuracy, latency, robustness).
2. Motivation Architecture (gamification, adoption, stickiness).
If you neglect the second, and you’re shipping research papers, not products. Design journeys for emotion, not just function: craft experiences users want to play.
