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Each year, I write about Bitmovin’s Video Developer Report because it’s one of the few recurring data points available to the streaming industry. It reports survey-based usage and planned usage for codecs, protocols, encoding, player development, QoE, advertising, CDN strategy, and more. I inevitably download it multiple times each year for referencing in some article or consulting project.
This year’s 10th edition is based on responses from 486 video professionals in 94 countries, up from a survey base spanning 49 countries in the 2025 edition. As always, readers should consider the methodology: the survey was open to all respondents and may be somewhat skewed toward Bitmovin’s customer base. It’s also broad-based, and includes streaming broadcasters, suppliers of streaming technology products and services, and many other streaming-related enterprises.
This year’s report is notably different from prior editions, with a stronger emphasis on using the survey data to support larger observations and predictions about where streaming is going. That makes this edition more ambitious than previous reports. It is both a survey of current practice and an editorial argument about where the market will go over the next 12 to 24 months.
Full disclosure: For the first time, I contributed to the report. I wrote the forewords to the AI Across the Video Stack chapter and the Low Latency, MOQ and the Future of Video Delivery chapter.
Contents
The four sections
Here are the four sections and their major discussion points.
AI across the video stack. This section examines where video organizations are applying AI and machine learning today, including workflow automation, metadata creation, transcription and localization, recommendations, personalization, content analysis, video-quality optimization, and generative media. It also looks at AI coding assistants, the barriers limiting their use, and the emerging role of MCP and agent-accessible APIs in connecting AI tools to video platforms, documentation, analytics, and operational workflows. Finally, it considers content authenticity, provenance, C2PA, and watermarking as AI-generated media becomes more prevalent.
Growing the ad business. This section focuses on how streaming services are monetizing through advertising. It measures the monetization models respondents use, the ad formats they have deployed, and the advertising architectures supporting them, including client-side, server-side, server-guided insertion, and dynamic ad replacement. It also discusses CTV delivery, ad playback quality, measurement, fill-rate visibility, new inventory formats such as pause ads and squeezebacks, and the operational challenges of addressable advertising at scale.
QoE, playback, and observability. This section covers the metrics teams use to measure video performance, the platforms and devices they support, the player codebases they maintain, the analytics and observability products they use, and how they access their QoE data. It also measures how long teams spend maintaining player and analytics systems and how long it takes to identify the root cause of streaming problems. The broader theme is the growing importance of player-side, session-level data for detecting, diagnosing, and responding to viewer-impacting failures.
Low latency, MOQ, and the future of video delivery. This section explores the protocols, formats, encoder types, CDN models, and latency targets used in live contribution and video distribution. It measures current and planned use of low-latency technologies and MOQ, as well as production and planned adoption of video codecs. It also examines the role of SRT and other contribution protocols, the continuing dominance of HTTP-based delivery, and the practical trade-offs among latency, device reach, scalability, cost, and delivery efficiency.
Charts worth reviewing
Several charts are particularly useful as quick-reference points throughout the year. These are the foundational, nuts-and-bolts topics I track from report to report because they show what streaming services care about and how streaming organizations are actually building, operating, and delivering their services.
Biggest challenges. This chart tracks the operational and business issues that respondents identify as most pressing, including live latency, cost control, monitoring and analytics, root-cause analysis, ad insertion, playback across devices, QoE, delivery, viewer engagement, testing, and content protection. It helps show which problems have risen or fallen in priority and how closely economics, reliability, monetization, and operational visibility are becoming linked.
Encoding types. The encoder chart breaks out the technologies used for live and VOD encoding, including commercial encoders, open-source encoders, and in-house solutions built on open-source software. It is a useful annual indicator of how organizations balance control, cost, support, reliability, and time to market, and whether those trade-offs differ between live and file-based workflows.
Distribution protocols. This chart tracks production use of the major video-distribution formats and protocols, including HLS, DASH, CMAF, and WebRTC. It provides a practical view of how quickly the delivery ecosystem is changing, whether established HTTP-based streaming formats remain dominant, and where lower-latency or real-time alternatives are gaining traction.
Contribution protocols. The live-contribution chart covers the protocols used to move feeds into streaming workflows, including SRT, HLS, RTMP, RTP, RIST, Zixi, and others. It is especially valuable because contribution is often where new transport technologies enter production first, before they appear broadly in consumer-facing distribution workflows.
Two charts are of particular interest to me. First is the report’s AI-use chart, which separates practical AI deployment from the generative-AI hype cycle (Figure 1).
As you can see, the leading applications are transcription, translation, recommendations, quality optimization, metadata, and scene or ad-placement detection. So, predictably, AI is currently winning where it can replace labor, improve discoverability, increase monetization opportunity, or improve operations at scale.
Codec Usage: Current and Planned
The codec chart is also a favorite, showing current and planned usage of video codecs (Figure 2).
H.264/AVC remains the production workhorse, at 85%, and HEVC remains substantial at 58%. AV1 is used in production by 19% of respondents but leads 12-month deployment plans at 35%. VVC is at only 5% in production, but 20% of respondents plan implementation.
The one thing I’m sure of is that next year’s survey won’t show 54% AV1 usage and 25% VVC usage. But the 12 month predictions gauge sentiment, and VVC’s is impressive. AV1’s is higher, of course, but, historically, AV1’s sentiment is always higher.
Bottom line
The 2026 Bitmovin Video Developer Report is useful because it combines longitudinal survey data with a more opinionated view of the market’s next phase. The survey findings show what teams are using today; the report narrative offers a view of where AI, advertising, observability, codecs, and delivery architecture may take them over the next year or two.
For anyone who works in streaming, the report is a resource worth keeping close. It offers one of the better annual snapshots of what the industry is using, what it is worried about, and what it expects to be working on next.
Click here to download your copy.
