Forrester's Q2 2026 report on bot and agent trust management highlights the growing need for streaming platforms to distinguish between human users and automated AI agents. The research emphasizes that security teams must now collaborate with digital and e-commerce stakeholders to manage inbound agentic traffic and mitigate risks like LLM scraping and account fraud.
The rise of agentic AI requires streaming providers to move beyond simple bot blocking toward sophisticated traffic orchestration. As LLMs increasingly scrape video metadata and user interfaces, platforms must implement controls that verify the intent and origin of every inbound request to protect proprietary content. This shift forces a technical evolution where security stacks must integrate with digital experience tools to maintain platform integrity without blocking legitimate automated services. The broader ecosystem will likely see a surge in demand for vendors that offer real-time model tuning to minimize false positives during high-traffic events. Watch for streaming platforms to update their threat modeling programs specifically to address AI agent provenance by late 2026.
Forrester's Q2 2026 Wave on bot and agent trust management arrives as streaming platforms face a measurable surge in automated traffic. In its annual Video Developer Report published in September 2026, Bitmovin found that 98 percent of video professionals now use AI or ML in their workflows, with 46 percent employing AI tools daily, a figure that underscores how much agentic activity is already touching video infrastructure. That same report identified ad insertion and root-cause analysis of streaming issues as top challenges, both areas where automated agents increasingly interact with platform APIs and content delivery layers.
On the vendor side, the competitive landscape for managing that agentic traffic is consolidating around platforms that combine video delivery with built-in AI orchestration. Mux launched its Robots product in early 2026, which runs AI analysis jobs natively inside the Mux platform next to the video asset, eliminating the need for developers to manage separate provider API keys. The product evolved from an open-source TypeScript toolkit called @mux/ai, released in December 2025, into a first-party API with webhook-based job completion and automatic provider selection. Mux also introduced Robots Directives for multi-step workflow orchestration, signaling that managed video platforms are embedding agent coordination directly into their stacks rather than leaving trust decisions to external security tools.
Independent comparisons of the managed video API market confirm that AI capabilities have become a primary differentiator among encoding and delivery vendors. A 2026 build-and-buy analysis of five major platforms found that Mux ships Claude-powered auto-chaptering, semantic search, and an MCP server alongside GenAI clip generation planned for Q3 2026, while Cloudflare Stream offers per-title AI encoding and Hive moderation, and AWS IVS pairs Bedrock and Rekognition for low-latency interactive use cases. For streaming security teams evaluating Forrester's recommendations, the practical implication is that agent trust decisions are increasingly made inside the video platform layer itself, not solely at the WAF or CDN edge. Buyers assessing bot and agent trust management software will need to account for how these platform-native AI features interact with external trust-management tools, particularly around content scraping detection and account-fraud prevention.
A new Forrester report identifies AI agent trust management as a critical priority for streaming platforms. As automated traffic surges, providers must distinguish between human users and malicious bots to prevent account fraud and LLM scraping. This shift requires integrating security controls directly into video platforms to protect proprietary content.
It is essential for distinguishing between human users and automated bots, helping platforms mitigate risks like account fraud and unauthorized LLM scraping of video metadata and interfaces.
Account fraud remains the primary use case for trust management software, followed closely by web and LLM scraping.
Platforms are increasingly embedding agent coordination directly into their stacks, with some vendors like Mux offering native AI analysis tools to manage workflows without relying solely on external security tools.
Buyers are prioritizing vendors with dedicated threat research teams to counter rapidly evolving bot techniques and those that offer real-time model tuning to minimize false positives.
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