--- title: "AI Mastering vs a Mastering Engineer: When to Use Each" description: "AI mastering vs a human engineer: what blind tests found, what software still can't do, and how to decide which one fits your song and your budget." canonical: https://tunr.studio/guide/ai-mastering-vs-mastering-engineer markdown: https://tunr.studio/guide/ai-mastering-vs-mastering-engineer.md last-updated: 2026-11-02 site: Tunr (https://tunr.studio) version: 0.5.0 --- # AI mastering vs a mastering engineer: when each one makes sense Choose a mastering engineer when a release matters and you want judgement and feedback on the mix. Choose automated mastering when you need speed, low cost or many versions. In published blind tests, human engineers tended to rank higher, but listeners couldn't reliably pick them out and results varied by genre. ## Short answer The evidence is thinner than either side claims. A 2022 Audio Engineering Society paper found listeners couldn't consistently identify human masters, and preferred them in jazz but not in rock. A 2024 blind test by Benn Jordan, with 472 listeners and one song, ranked two human engineers first and second, with an open-source tool third. So software can be good enough for many songs, and a skilled engineer can still beat it. The bigger difference is what happens around the audio. An engineer can tell you the vocal is too quiet and send the mix back. Automated tools work with the file you give them. Use software for demos, singles on a budget and early checks, and use an engineer for the album you've spent a year on. ## What the listening tests found This article is for independent artists deciding where to spend a small budget. Two tests are worth knowing. In the [Audio Engineering Society paper by Elliott and Chon (2022)](https://aes.org/publications/elibrary-page/?id=21888), two human engineers were compared with two automatic services. Listeners couldn't consistently identify the human masters. They preferred them in jazz excerpts but not in rock, and the authors called that partial support for the claim that human mastering is better. The larger test isn't peer reviewed. [MusicTech reported in October 2024](https://musictech.com/news/gear/benn-jordan-ai-mastering-study) that producer Benn Jordan sent one 2017 track to plugins, online platforms and professional engineers, then had 472 listeners rate the results in a double-blind study. Max Hosinger and Ed the Soundman, both human engineers, placed first and second. The open-source tool Matchering 2.0 placed third, and LANDR was disqualified before the final round. Neither test settles the question. One used a small set of services and engineers, and the other used a single song. Neither included Tunr, so they say nothing about how we would have scored. ## What an engineer does that software doesn't The audio is only part of what you pay an engineer for. They listen in a treated room you probably don't have, and they tell you when the problem is in the mix. Sending a mix back with a note about a harsh vocal can do more for a song than any setting. They also understand intent. A deliberately lo-fi record or an unusually quiet intro can look like a mistake to anything working from measurements. An engineer can ask you. They can also shape an album as one piece, setting the level of each song against the next, which is where track-at-a-time processing gets harder. ## What software does better Speed and repetition. You can try five versions of a chorus in the time it takes to write an email, and hear what mastering will do to the mix while you can still change the mix. Plenty of songs never justify a paid master, such as demos, pitches and a release you are still testing. Software also never tires, so a batch of tracks gets the same treatment from the first to the last. The main weakness of most automated tools is that you get an answer with no explanation, so you can't learn from it or disagree with part of it. That is what we tried to fix in Tunr. It shows what it measured and gives a plain-language reason for each stage it proposes, and every stage can be bypassed or adjusted. It also runs offline, so unreleased music stays on your computer. ## How to decide: a simple comparison Most artists don't need one answer for everything. Use software to get a song close and to find out whether the mix is ready, then spend money where a second opinion has real value. | Situation | Better fit | Why | | --- | --- | --- | | Demo or work in progress | Software | Cheap, instant, repeatable | | Single with no budget | Software, carefully checked | A good result is possible with care | | Album you've spent a year on | Engineer | Sequencing and feedback on the mix | | Vinyl release | Engineer | Cutting has its own constraints | | Unusual or deliberately rough sound | Engineer | Intent is hard to measure | | Testing whether a mix is ready | Software first | Shows problems before you pay | | Unreleased music you can't upload | Offline software | The audio stays on your computer | ## If you use software, check these three things First, compare at matched loudness. A master that is simply louder will usually sound better for a few seconds, and that is how a lot of poor masters get approved. Tunr's A/B Mixer has a loudness match and a blind test for this. Second, listen on the speakers your audience uses, including a phone. Third, read the numbers. Check the loudness and true peak of the exported file against [your platform's target](https://tunr.studio/guide/lufs-targets-how-loud-should-master-be), since every other judgement depends on the delivered file being right. If you end up hiring an engineer anyway, the time wasn't wasted. A mix [prepared properly](https://tunr.studio/guide/prepare-mix-for-mastering) and a software master that shows what you are aiming for both make the session better. ## Frequently asked ### Is AI mastering as good as a human engineer? Sometimes, on some material. A 2022 paper found listeners couldn't consistently pick human masters, while a 2024 blind test of one song ranked two engineers above every automated tool. A skilled engineer can still win, especially on unusual material, but software can give a usable result for many ordinary songs. ### Can listeners hear the difference between AI and human mastering? Not reliably, according to the 2022 Audio Engineering Society paper by Elliott and Chon, which found listeners couldn't consistently identify human-mastered samples. They did prefer the human versions in jazz excerpts, though not in rock. The study was small, using two engineers and two automatic services, so treat this as a limited finding. ### Is Tunr AI mastering? Tunr is automated mastering software that runs offline on your computer. It measures your track, proposes a chain of ten possible stages and gives a plain-language reason for each, and you can bypass or adjust any of them. It isn't a substitute for an engineer's feedback, but it costs nothing to try. ## Sources - [Elliott and Chon, Audio Engineering Society, 2022: human and automatic mastering compared](https://aes.org/publications/elibrary-page/?id=21888) - [MusicTech: Benn Jordan's blind test of AI and human mastering (October 2024)](https://musictech.com/news/gear/benn-jordan-ai-mastering-study) ## Related guides - [LANDR alternatives: free, offline mastering in 2026](https://tunr.studio/guide/landr-alternatives) - [What is audio mastering, and how is it different from mixing?](https://tunr.studio/guide/what-is-audio-mastering) - [How to prepare a mix for mastering: a 7-point checklist](https://tunr.studio/guide/prepare-mix-for-mastering) --- Source: https://tunr.studio/guide/ai-mastering-vs-mastering-engineer · Site index for agents: https://tunr.studio/llms.txt · Ask a question: POST https://tunr.studio/ask · MCP docs server: https://tunr.studio/mcp