CreatorIQ has expanded its partnership with YouTube by integrating the YouTube Creator Partnership API, bringing first-party viewership data directly into its AI-powered Discovery platform. The integration, announced at the YouTube NewFront, allows brands to evaluate creators based on actual viewer demographics and interests rather than surface-level metrics like follower counts. The integration embeds platform-native insights into creator discovery workflows, enabling brands to identify suitable partners, compare audience performance and measure impact across organic and paid campaigns. CreatorIQ is among the first to offer this capability to customers. CreatorIQ's Creator Graph processes over 123 million social posts daily across 15 million creators worldwide. More than 1,300 organisations, including Delta Air Lines, Google, LVMH and Sephora, use the platform to manage their creator programmes.

Two landmark jury verdicts against Meta and YouTube have imposed $381 million in combined financial penalties, marking a potential shift in how social media companies are held accountable for child safety. Meta faces a $375 million fine in New Mexico for knowingly harming children's mental health and concealing child sexual exploitation, whilst Meta and YouTube must pay at least $6 million in damages to a California woman who became addicted to social media as a child. The verdicts precede thousands of pending lawsuits, with attorneys general in over 40 states suing Meta over youth mental health concerns. However, the immediate business impact appears limited—Meta reported $201 billion in sales last year, and its stock closed higher following the verdicts. A second trial phase in New Mexico could mandate platform changes, whilst the California case serves as a bellwether for hundreds of similar lawsuits.

YouTube has expanded its likeness-detection tool to include politicians, journalists and government officials, marking the most significant platform-level deepfake defence deployed to date. The system works similarly to Content ID: enrolled individuals submit identity verification, YouTube builds a reference profile, and uploads are scanned against it. The deployment demonstrates that detection at scale is technically feasible and commercially viable, potentially shifting liability expectations for organisations handling audio or video evidence. Once such capability exists publicly, it becomes harder to argue no reasonable implementation path existed. However, YouTube's approach requires a known reference to compare against, which most enterprise environments lack. The system also only detects faces, not voices, and the enrollment data could theoretically be compromised. These limitations highlight challenges for organisations building detection systems from scratch.