Updated on April 14, 2026
My observation says that — current AV industry = mostly software AI (cloud / PC / server-based).But the shift to hardware-based AI in AV has already started, just not fully visible yet.
Let’s break this properly from an AV-engineering perspective.
1. Reality Today (2024–2026)
AV is NOT purely software AI anymore
We already have early hardware AI inside AV components, but it's:
Hidden inside DSPs / chipsets
Limited to specific functions
Not marketed as “AI hardware AV” yet
Examples:
AI noise reduction in DSPs (Shure, Biamp, QSC)
Auto-framing cameras (Crestron 1Beyond, Poly, Cisco)
Beamforming mics with tracking
These are running on embedded DSP + AI accelerators, not cloudModern DSP chips already include neural engines + ML accelerators
2. Why AV still feels “Software AI”
Because of 3 main limitations:
1. Compute Requirement
AI (vision, speech) needs heavy processing (GPU/NPU)
Traditional AV hardware = low-power DSP focused
2. Cost vs Market
AV hardware must be:
Reliable
Long lifecycle (7–10 years)
Cost-sensitive
AI chips increase BOM significantly
3. Flexibility
Software AI (cloud) = easy updates
Hardware AI = fixed capability (unless reprogrammable)
3. What is Changing NOW
We are entering the Edge AI era
Meaning: AI runs inside the device (hardware) instead of cloud
Key technologies enabling this:
Edge SoCs (System-on-Chip)
NPUs (Neural Processing Units)
AI DSPs
FPGA-based AI (like adaptive compute platforms)
These chips are designed for real-time, low-latency AI at device level
4. Where Hardware AI is Already Coming in AV
A) Audio
AI DSP chips (echo cancellation + voice isolation)
Context-aware audio (speaker tracking, noise classification)
Already happening (automotive & pro AV crossover)
B) Video
AI cameras with:
Auto framing
Speaker tracking
Gesture recognition
Runs on edge AI chips which is not included in the designs.
C) Control Systems
Predictive AV systems
Self-healing rooms
Usage-based automation
Will require embedded AI processors
D) AV-over-IP + AI
AI embedded in endpoints:
Encoders/Decoders
Switches (yes!)
Streaming nodes
5. Timeline — When Full Hardware AI AV Will Happen
Now (2024–2026)
Hybrid systems (DSP + partial AI hardware)
AI mostly “feature-level”
6. What Future AV Hardware Will Look Like
Think of this:
A DSP won’t just process audio
It will: Understand speech context, identify speakers, Optimize acoustics dynamically
A camera won’t just capture
It will: Understand meeting intent, Track engagement, Adjust framing intelligently
A control system won’t just triggerIt will: Predict user behavior, Auto-configure rooms
7. Key Insight
AV is moving from: Signal Processing → Intelligence Processing
Traditional DSP: EQ, compression, routing
Future AI Hardware: Understanding + decision-making + adaptation
8. Why Should we Care about this?
This shift will redefine roles:
Today: AV Programmer / DSP Designer
Tomorrow:
AV + AI System Architect
Edge AI integrator
Data-driven AV designer
Final Conclusion for this discussion I can say that...
"Hardware-based AI in AV is already starting, but Mainstream adoption = next 3–5 years (2026–2030)"
And after that: AV systems won’t just “work” — they will think
Share