As interest in running grows, Google Search is making race preparation easier with AI tools. Searches for “Run club,” “how to choose running shoes” and “how to train for a marathon” have reached an all-time high this year. Users can create personalized plans that take local routes and their current fitness levels into account. By selecting Canvas from the “+” menu in Search’s AI Mode, users can prepare a training program; the tool also offers suggestions for conditioning exercises and strength development. They can also discover different approaches from websites and content creators. Those who connect their YouTube Music account to Search can create custom playlists to stay motivated during long runs. Search also helps with choosing running shoes and equipment. Users can search for specific needs, such as road shoes suitable for wide feet, lightweight hydration vests under $80, or anti-chafing clothing. Google’s Shopping Graph, which consists of more than 60 billion product listings, presents available options for comparison and shows local availability. This allows users, from beginners to experienced runners, to evaluate preparation and equipment options suited to their needs.
Why it matters
This approach turns Google Search from merely a place to find information into a tool that combines workout planning, content discovery, and shopping in a single process. Taking local conditions and personal fitness into account could reduce the need for runners, particularly those who do not know where to start, to switch between different sources. Presenting product options along with stock and local availability information also shifts equipment searches from general recommendations to purchasable options. This integration is relevant not only to beginners but also to experienced runners with specific training and equipment needs. However, the information shared does not explain the criteria used to assess the extent to which programs and recommendations prepared by artificial intelligence align with users’ goals.