AV1 adoption to hit 57% as AI moves into core encoding pipelines
This report from NETINT surveys video encoding professionals on current and future trends including the adoption of AV1, the shift toward hybrid infrastructure, and growing integration of machine learning. The data highlights a transition away from GPU-only hardware and emphasizes that budget and capacity constraints remain the primary barriers to adoption for most organizations.
Key Takeaways
- AV1 production deployment is projected to rise from 17% today to 57% by year-end 2026.
- Hardware evaluation intent for VPUs (51.5%) has reached near-parity with GPUs (53.6%) for the first time.
- AI-driven content-aware ladder generation is growing at a rate of 77%, signaling a shift into core infrastructure.
- Budget and team capacity are the primary bottlenecks, with 49% of video teams consisting of five or fewer people.
- Hybrid infrastructure adoption jumps to 45% among large-scale operators, while hardware-only approaches drop to 16%.
Why It Matters
The transition to AV1 and VPU-native infrastructure represents a structural shift for high-volume streamers seeking to decouple from GPU-only dependency. As AI migrates from experimental metadata tasks to real-time bitrate optimization, the competitive gap will widen between those using automated content-aware pipelines and those limited by small team sizes. For the ecosystem, this creates an 18-month window where vendors must simplify complex codec deployments into headcount-neutral, turnkey solutions to capture the 'Methodical Evaluator' segment. Watch for whether AV1's 231% growth rate translates into a significant reduction in egress spend across major CDNs by mid-2027.
Additional Context
The acceleration of AV1 adoption highlighted in the NETINT report aligns with broader technical shifts across the streaming landscape. Per Ateme (January 2026), the completion of major device-side support gaps—including Apple's M3 and iPhone 15 Pro hardware—has established AV1 as the 'gravitational center' for next-gen compression. This maturity is critical as operators face rising cloud costs; per Devoncroft Partners (July 2026), top-quartile broadcast teams utilizing cloud-native encoding and adaptive bitrate tools have already achieved 31-36% lower content delivery costs compared to those on legacy hardware. While HEVC retains a 65% production share, the expiration of the HEVC Advance rate increase deadline in June 2026 has added fresh pressure to move toward royalty-free alternatives like AV1.
Simultaneously, the competitive pressure on hardware incumbents is intensifying. While NVIDIA maintained an estimated 86% share of the AI GPU market in 2025, per Companies History (May 2026), the rise of custom ASICs and specialized Video Processing Units (VPUs) is expected to capture a larger portion of data center inference and transcoding workloads. Market research from IMARC Group (June 2026) projects the video transcoding market to reach $6.9 billion by 2034, driven by this hardware diversification. The shift toward hybrid models is now a standard, with Interra Systems noting in December 2025 that hybrid architectures have become the default for live and linear operations, balancing the low latency of edge hardware with the elasticity of the public cloud.
Read full article at netint.com
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