What Makes a Consumer AI Product Stick? | Josh Elman

Josh Elman discusses the critical challenges of consumer retention in AI products, emphasizing that while capturing attention is relatively straightforward, maintaining user engagement is significantly more complex. He asserts that successful AI products typically excel at a specific function before evolving into habitual use, with trust being a vital factor for deeper integration into consumers' daily lives.

Elman highlights the transformative impact of AI on task management and information access, noting that advancements in AI models are enhancing their capabilities. He anticipates exciting developments in AI over the next year but cautions that consumers may not be prepared for the rapid changes these advancements could bring. Companies are encouraged to guide consumers gradually in understanding AI's potential.

Personal AI agents are positioned as valuable tools for assisting with daily activities, such as scheduling and health monitoring, while also streamlining shopping experiences by acting in the consumer's best interest. Elman points out the emerging trend of AI micro-dramas in interactive media, which enrich storytelling and entertainment. The podcast team has initiated an AI micro-drama project with Plot Party, showcasing innovative storytelling possibilities.

Elman stresses the importance for creators to build their own products and foster relationships with their audiences, especially in a saturated social media landscape. He notes the rising popularity of group chats and suggests that integrating AI into these interactions could create new social dynamics. AI has the potential to enhance social interactions by connecting people, with the ideal AI assistant managing social calendars and promoting real-world engagement.

Voice technology is predicted to become a significant communication medium, although Elman acknowledges its current limitations as a lossy medium. He emphasizes that new consumer AI products must earn trust by excelling at a limited set of tasks, using Siri as a successful example. A step-by-step development approach is advocated over attempting to deliver comprehensive solutions all at once.

Elman also discusses the trend of consumer apps offering products for free to attract attention, while recognizing the challenge of monetizing AI tools without sacrificing accessibility. He observes that consumers are increasingly willing to pay for digital products and predicts a decrease in the cost of building AI products, aligning with this willingness to pay.

To encourage adoption, a product must provide clear value, with retention being crucial for long-term success. Elman points out that network effects can enhance user engagement, making it less likely for users to switch platforms once they have invested time in a product. He underscores the importance of capturing consumer attention and performing exceptionally well from the outset to encourage users to abandon competing options.

Building a durable AI platform requires meaningful connections with customers, and Elman believes that understanding local culture is essential for creating consumer products that resonate with mainstream users. Reflecting on his experience at Twitter, he emphasizes the importance of listening to users and engaging them in the product development process to drive growth and retention.