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X is Moving to a Customizable AI-Powered Algorithm

09/21/25
Source: Social Media Today – Latest News by Andrew Hutchinson. Read the original article

TL;DR Summary of X’s Shift to AI-Powered Algorithms for Personalized Feeds

X is transitioning to a fully AI-driven algorithm aimed at delivering more personalized content based on users’ interests. The platform plans to let users dynamically adjust their feeds via explicit prompts to the AI assistant, Grok. While this approach offers enhanced customization, real-world adoption may be limited as users tend to prefer automated, effortless content discovery. Additionally, AI-powered user engagement bots could become a strategy to boost interaction without manual input.

Optimixed’s Overview: How AI is Reshaping User Engagement and Content Customization on Social Platforms

Introduction to AI-Powered Personalization on X

X is evolving its content delivery by integrating an AI-powered algorithm designed to better align users’ timelines with their unique interests. The goal is to move beyond mainstream, generic content and foster niche communities where users see posts relevant to their preferences.

Key Features and User Control

  • Dynamic Feed Adjustment: Users will soon be able to instruct the AI assistant, Grok, to modify their content feed in real time, requesting more or less of certain topics.
  • Open Source Algorithm: X plans to open source its AI algorithm updates biweekly, allowing transparency and iterative improvements.
  • Interest-Based Communities: The AI aims to connect like-minded users to encourage relevant interactions rather than exposure to unrelated or mainstream content.

Challenges and User Behavior Insights

Despite the innovative approach, there are notable challenges:

  • Low User Engagement: With 80% of X users rarely engaging beyond passive consumption, expecting active feed customization may be optimistic.
  • Preference for Automation: Users typically favor effortless content curation, as seen on platforms like TikTok, where implicit signals guide recommendations without manual input.
  • Historical User Behavior: Past events, such as the Cambridge Analytica scandal, show that users often prioritize convenience over privacy or control settings, suggesting limited manual tuning of feeds.

Future Outlook and Potential Strategies

Looking ahead, platforms may explore alternative methods to boost engagement:

  • AI-Generated User Interactions: Deploying AI-powered bots to simulate active audiences could increase perceived engagement and user satisfaction.
  • Balancing Automation and Customization: The challenge remains to offer meaningful user control without sacrificing the seamless experience users expect.

Overall, while AI promises more tailored social media experiences, the success of such features depends heavily on user willingness to engage proactively with customization tools versus relying on automated algorithms.

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