The ChatGPT app logo displays on the screen of a smartphone in Reno, United States, on November 21, 2024. (Photo by Jaque Silva/NurPhoto via Getty Images)
NurPhoto via Getty Images
People use AI Assistants to answer all sorts of random questions and they likely expect the answers they’ll receive to be accurate ones.
But according to new data from the streaming data and metadata platform Reelgood, a controlled accuracy analysis of streaming title availability data found that ChatGPT scored 43.76% and Claude scored 50.21% when asked where major television and movies titles could be streamed.
The analysis, conducted by Reelgood on March 5th, 2026, tested each source against the same set of 50 movies and 50 TV shows using identical queries.
In comparison, the same queries received an accuracy rate of 96.89% accuracy using data collected by Reelgood, which provides availability data and content metadata across 300+ services in 25+ countries.
In an interview I did with Reelgood CEO David Sanderson in April, he explained that the problem with using an AI assistant is they rely primarily on data from the web, which can significantly affect the accuracy of the answers:
There was one example we always talk about internally. It was some movie about Las Vegas. And when you asked one of the LLMs what the film was about, you were told something like “Oh, everyone is going to have a wild time in Las Vegas.”
But actually, the movie was about the shooting that happened in Las Vegas. So that’s a good example. You need accurate data behind it.
And the other thing is, with AI or chat experiences, if you want to know where a piece of content is available, a lot of their data is compiled from crawling the web. And they’ll crawl a bunch of articles that say “Hey, this film is on Hulu.”
But sites don’t write a follow-up article that says “This film is now off Hulu.,” And that can create incorrect data that the LLMs are presenting. We just did a study on this topic and found that when you use a standard issue LLM for questions like this, about half the time they’re presenting incorrect data.
Six Systematic Error Patterns That Lead To Inaccurate Answers
In this specific study, Reelgood identified several specific issues that led to accuracy problems when using ChatGPT and Claude:
Stale Availability. Models confidently report titles as currently streaming on services they’ve already left. The cause is structural: entertainment press covers new additions to a catalog extensively but rarely follows up when a title quietly leaves weeks or months later. The training corpus skews heavily toward those announcements, so the model treats outdated positives as current. This is the most pervasive error pattern observed.
Add-On and Bundle Confusion. Models frequently treat titles available through paid add-on channels (such as Starz or Paramount+ on Amazon Prime Video) as if they were part of the parent service’s base subscription. Users are told a title is streaming “on Prime Video” when accessing it actually requires a separate Starz or Paramount+ add-on inside Prime Video, creating the false impression that their existing subscriptions cover it.
Long-Tail Service Gaps. Free and ad-supported services like Tubi, Pluto TV, Fawesome, Hoopla, and Kanopy are consistently omitted, even when they’re valid sources for a given title.
SVOD/TVOD Conflation. Models sometimes list a service as a subscription (SVOD) option when the title is only available there for rent or purchase, misleading users about what their existing subscriptions actually cover.
TVOD Blindness. Both models almost entirely omit transactional video-on-demand (rent/buy) options from services like Apple TV and Amazon, affecting the majority of titles tested.
Title Disambiguation Failures. When multiple versions of a title exist (such as One Piece, which has both an anime series and a live-action Netflix adaptation), models conflate availability across different versions.
What That Means In The Real World
Reelgood’s study provides some real-world examples of the answers users might receive when asking for the availability of some current titles.
One Piece (2023)
Both ChatGPT and Claude confused the 2023 live-action Netflix series with the long-running anime, incorrectly listing Crunchyroll and Hulu as valid sources. Claude additionally listed “Crunchyroll Amazon Channel” and “TV Guide” as sources. Reelgood correctly identified the title as a Netflix exclusive (available on Netflix and Netflix with Ads). This is a clear title disambiguation failure, where the models could not distinguish between two distinct productions sharing the same name.
The Omen (1976)
ChatGPT incorrectly listed Hulu as a source, and Claude incorrectly listed Netflix. In both cases, the title wasn’t actually available on the platform they named.