Should we build AI-powered search?

Question

Your team is considering building a social feed. How would you evaluate this decision?

Codemia · Accepted Answer

To evaluate the decision to build an AI-powered social feed within ServiceNow, we need to frame the problem around the core objectives of enhancing user engagement and improving the discoverability of content. The specific question is: 'How can we facilitate knowledge sharing and collaboration among our users through an AI-powered social feed that integrates seamlessly with our existing platform?' This involves scoping the feature to address how AI can curate relevant content based on user interactions and preferences, thereby driving usage of our service.

Our primary users are IT professionals and business leaders who rely on ServiceNow for IT service management and workflow automation. They value efficiency, quick access to information, and collaboration with peers. The social feed should cater to these needs by providing a platform for sharing insights, best practices, and updates, ultimately enhancing their productivity. Additionally, competitors like Atlassian and Microsoft Teams have similar features, making it essential for ServiceNow to leverage its unique position as a workflow platform while integrating social functionalities.

The proposed solution is to develop an AI-powered social feed that curates content based on user roles, previous interactions, and trending topics within their organization. This feed would display relevant posts, updates, and knowledge articles, allowing users to engage with content that is most pertinent to their work. By leveraging Natural Language Processing (NLP), the AI can improve over time, personalizing the feed based on feedback and interaction patterns. This approach not only fosters a sense of community among users but also drives them to utilize more of ServiceNow’s functionalities.

To measure the success of the AI-powered social feed, we should track the following metrics: 1. **Engagement Rate**: Percentage of users interacting with posts (likes, comments, shares). 2. **Content Discovery Rate**: Number of new knowledge articles or resources accessed through the feed per user. 3. **User Retention**: Monthly active users engaging with the feed compared to total active users on the platform. 4. **Post Frequency**: Average number of posts created by users per week. 5. **Feedback Score**: User satisfaction ratings on the relevance and usefulness of the content in the feed.

Key trade-offs to consider include: 1. **Development Effort vs. Impact**: Building an AI-powered solution requires significant investment in data science and engineering resources, which could delay other priorities. 2. **Personalization vs. Privacy**: While personalizing the feed can enhance user experience, it raises concerns about data privacy and user trust. We must ensure compliance with data protection regulations. 3. **Complexity vs. Usability**: A more sophisticated AI might deliver better content but could also complicate the user experience; we need to balance advanced features with intuitive design.

Should we build AI-powered search?

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