The Economic Potential of Generative AI and Strategies for User Adoption


Hatched by Glasp

Sep 12, 2023

3 min read


The Economic Potential of Generative AI and Strategies for User Adoption


Generative AI, with its potential to revolutionize various industries, holds immense economic value. According to recent research, the integration of generative AI across 63 use cases could contribute $2.6 trillion to $4.4 trillion annually to the global economy. This estimate becomes even more staggering when considering the inclusion of generative AI in existing software. Four key areas - customer operations, marketing and sales, software engineering, and R&D - account for 75% of the potential value of generative AI. For instance, the banking industry alone could benefit from an additional $200 billion to $340 billion annually through the implementation of generative AI use cases. Similarly, retail and consumer packaged goods could witness a significant impact of $400 billion to $660 billion per year. The potential of generative AI is truly remarkable.

Connecting Generative AI's Economic Potential and User Adoption:

While generative AI offers tremendous economic prospects, user adoption plays a crucial role in realizing its full potential. Understanding why users are drawn to a product, their initial expectations, and the factors that lead them to become active users is essential for fostering adoption. By analyzing the stories of users who have successfully adopted a product, we can identify patterns that can guide us in improving messaging, user experience, and overall product performance.

Key Questions for Understanding User Adoption:

To gain insights into user adoption, it is vital to address four key questions:

1) What prompted users to sign up and try our product initially?

2) What aspects of the product did not meet their expectations or prove challenging to comprehend?

3) Why did users decide to give the product another chance after an initial setback?

4) What strategies or features led users to become active and engaged with the product?

By focusing on these questions, we can revise messaging and user experience to cater to user expectations and preferences. Ignoring benchmarks and instead identifying the motivations and experiences of users who have embraced the product can drive its success.

Actionable Advice for User Adoption:

1. Revamp Messaging to Highlight Value:

Based on user feedback, revamp your messaging to emphasize the aspects that brought users back and generated their interest. By aligning your messaging with the factors that resonate with users, you can attract a larger user base. For example, Twitter successfully revised its messaging to focus on finding and following the right people, resulting in increased user activation.

2. Simplify Onboarding Process:

An intuitive and streamlined onboarding process is crucial for user adoption. Analyze the actions users took during their second interaction with the product, and update the onboarding process to simplify and replicate those actions. By reducing complexity and ensuring a smooth onboarding experience, you can enhance user engagement and retention.

3. Continuously Improve Product Performance:

Regularly update and improve your product based on user feedback and evolving market trends. By addressing the gaps between user expectations and product performance, you can enhance user satisfaction and drive long-term adoption. This iterative process will allow you to build a core user base that deeply engages with your product.


Generative AI holds immense economic potential, with estimates suggesting that it could add trillions of dollars to the global economy. However, realizing this potential requires a focus on user adoption. By understanding the motivations, expectations, and behaviors of users who have successfully adopted the product, businesses can refine their messaging, improve user experience, and foster long-term engagement. By revamping messaging, simplifying onboarding, and continuously improving product performance, businesses can drive user adoption and maximize the benefits of generative AI.

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