Saturday, August 24, 2024

Corporate AI Application Service Procurement Survey and Analysis

1. Adapting Mindsets to Embrace AI Technology

When integrating artificial intelligence into products, companies need to fundamentally change the traditional product development mindset. Designing and developing AI products differs from traditional software; it requires reflection and adjustment in terms of technical feasibility and user experience. Initially, it is crucial to explore technology continuously and create prototypes to understand the potential and limitations of AI. Subsequently, integrating AI into critical parts of the product can deliver high-value user experiences. As tech entrepreneur Elad Gil states, deeply understanding and leveraging AI technology requires time and repeated experimentation.

2. Focusing on Solving Real Problems and Creating User Value

A successful AI product does not solely rely on advanced technology; it is more important to solve real problems and create user value. Building an eye-catching AI demo does not equate to having a popular and practical product. Joshua Xu, co-founder and CEO of HeyGen, emphasizes that understanding and segmenting user needs, especially considering different levels of technical acceptance, is crucial. This approach can prevent user attrition and convert skeptics into loyal users through proper messaging and education.

3. The Importance of Design and User Experience

Although AI technology is powerful, its full potential can only be realized by combining it with intuitive product design and user experience. Cameron Adams, co-founder and Chief Product Officer of Canva, shares their experience in designing AI tools, highlighting the importance of providing users with the right starting point and confidence. Reducing user confusion and offering guidance can significantly improve user satisfaction and engagement. Furthermore, as AI models continue to improve, designing suitable UI/UX can positively impact conversion rates.

4. The Critical Role of Data and Interfaces

In the future, having and licensing unique datasets will become a key advantage for companies in AI competition. Scott Belsky notes that data and interfaces will become more important than the models themselves, especially as models become commoditized and open-sourced. Companies should focus on leveraging proprietary data and designing superior interfaces to optimize workflows and user experiences. Designers will play a more significant role in this process, reimagining everyday work and life interfaces through innovative means.

5. Conscious Design of Initial Workflows

In the early stages of AI projects, companies should consciously design and optimize workflows to ensure effective integration and application of AI functionalities. This includes not only technical development but also user education and support, ensuring users fully understand and utilize AI technology. Through carefully designed workflows and continuous user education, companies can better realize the value of AI technology, driving innovation and business growth.

Integrating AI technology into corporate products is a complex and challenging task, requiring deep reflection and adjustment in several aspects, including mindset, user needs, product design, and data utilization. By fully understanding the potential and limitations of AI technology, focusing on solving real problems and creating user value, companies can stand out in a competitive market and successfully achieve the commercial value of AI technology.

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at August 24, 2024