Live sound engineering has traditionally been one of the most hands-on, experience-dependent skills in the music industry. A good live sound engineer can walk into an unfamiliar room, assess the acoustics, and dial in a mix that sounds great within minutes. It takes years of practice and thousands of shows to develop that ability.

Now AI is entering the live sound space, and the reaction from working engineers ranges from cautious interest to outright hostility. I’ve talked to sound engineers, venue operators, and technology developers to understand what’s actually happening.

What’s Currently Available

Automated Room Correction

The most practical and widely adopted AI application in live sound is automated room correction. Systems like the L-Acoustics LA-RAK II and d&b ArrayProcessing use measurement microphones and processing algorithms to analyse a room’s acoustic characteristics and apply corrective EQ to the PA system.

These systems don’t replace the engineer — they handle the physics of the room so the engineer can focus on the artistic mix. A venue with problematic acoustics (low-frequency buildup, harsh reflections) can be corrected in minutes rather than the hours it might take a human engineer working alone.

Several Australian venues have installed these systems, and the feedback from engineers is generally positive. “It takes care of the boring part,” one Melbourne-based engineer told me. “I don’t want to spend thirty minutes fighting room modes. I want to spend that time making the band sound great.”

Intelligent Mixing Assistants

Products like the Waves SuperRack and Allen & Heath’s dLive platform have introduced AI-assisted features that suggest channel processing settings based on audio analysis. Feed the system a vocal signal, and it suggests EQ, compression, and de-essing settings as a starting point.

These suggestions are starting points, not final mixes. Every engineer I spoke to who uses these tools modifies the suggestions significantly. But having a reasonable starting point can speed up soundcheck, particularly in situations where time is limited (festival changeovers, short support sets).

Feedback Detection and Suppression

Automated feedback detection and suppression has been available for years (the Shure AXT Digital system, for example), but AI-enhanced versions are more precise and faster. They identify and notch out feedback frequencies before they become audible to the audience, with less impact on the overall sound than older systems.

This is particularly useful in challenging acoustic environments — churches, gymnasiums, open-air venues with unusual reflections — where feedback management is a constant battle.

What’s Being Tested

Automated Monitor Mixing

Monitor mixing (the sound musicians hear on stage) is one of the most demanding aspects of live sound. Each performer has different preferences, the stage volume interacts with the PA, and changes need to happen in real time during the performance.

Some systems are being tested that use AI to adjust monitor mixes based on real-time analysis of stage sound and performer preferences. A drummer who consistently asks for more kick drum in their monitor could have that preference learned and applied automatically.

This technology is in early stages, and most engineers I spoke to are sceptical about its practical viability. “Monitor mixing is about communication with the musician,” one said. “An AI can’t read the bassist’s facial expression when they’re struggling to hear themselves.”

Predictive System Optimisation

AI systems that predict how a PA will perform in a specific venue configuration, based on architectural data and previous performance records, are being developed. The goal is to optimise speaker placement and system tuning before the first note is played.

For touring productions that visit dozens of venues, this could significantly reduce setup time and improve consistency. But the technology requires extensive venue data that doesn’t yet exist for most Australian rooms.

The Engineer’s Perspective

I surveyed fifteen Australian live sound engineers about AI in their field. The responses clustered around a few themes.

Useful for physics, not for art. Engineers generally welcome tools that handle acoustic correction, feedback suppression, and system optimisation. These are technical tasks that benefit from computational speed and precision. What engineers push back on is anything that tries to make artistic mixing decisions — balancing instruments, creating a sonic atmosphere, matching the energy of the room.

Concerns about deskilling. Several engineers worry that AI tools will reduce the demand for skilled engineers, particularly at smaller venues where a basic AI-mixed show might be “good enough” for venue operators who can’t afford a professional engineer.

“I’ve already seen venues that use an automated mixing system for their regular shows and only hire a human engineer for bigger events,” one engineer told me. “The AI mix is acceptable but not good. If venues get used to ‘acceptable,’ the demand for ‘good’ shrinks.”

Training implications. New engineers develop their skills by doing — mixing hundreds of small shows in small rooms. If those shows are increasingly handled by AI systems, the pathway to developing expertise narrows.

The Venue Operator’s Perspective

Venue operators are more pragmatic. A Melbourne venue owner told me: “I pay an engineer $250-400 per night. If an AI system can handle Tuesday and Wednesday nights competently, that saves me $500 a week. I still hire a human for Friday and Saturday.”

This economic logic is hard to argue with, but it has implications for the profession. Engineers need Tuesday night gigs to build experience for Friday night gigs.

Working with AI agent builders who develop automation tools, the pattern is consistent across industries: AI handles routine tasks, humans handle complex and creative tasks, and the boundary between the two keeps shifting.

Where I Think This Goes

AI will become standard in live sound for technical tasks — room correction, feedback suppression, system optimisation. These tools make shows sound better and save time. That’s unambiguously positive.

AI mixing assistants will improve and become more common for routine events — corporate functions, wedding bands, venue background music. Human engineers will remain essential for anything that requires artistic judgement — concerts, festivals, recording sessions.

The transition will create tension. Engineers who resist all AI tools will be at a disadvantage. Engineers who rely entirely on AI tools will produce mediocre results. The ones who thrive will be those who use AI for what it does well and apply their own skill and taste to everything else.

The technology is coming. The question is how the Australian live music community integrates it in a way that improves the experience without hollowing out the profession.