How good is AI at teaching languages?

This might get philosophical and technical quickly, so let me be clear from the start: I'm by no means a neuroscientist, nor do I have a degree in philosophy. I'll try to keep things in layman's terms — and I fully expect the comment section to roast me for my shortcomings in those areas.

The great debate: is AI really Artificial Intelligence?

First of all: I'm not sure I would call what we commonly refer to as "Artificial Intelligence" actual artificial intelligence in the first place. This is of course subject to debate (and a lot of semantics), but what we're mostly dealing with today are Large Language Models (LLMs). LLMs don't feel, they don't desire, they are not "born" nor do they "die". Instead they are probabilistic language models that generate output based on "what would be the most probable next token for a given input". This is obviously an over-simplification of how these things work, but that's the basic idea.

So I used the word "probabilistic" above, which both implies there's something called "deterministic" and that I might need to explain both words to many readers. Let's start with "deterministic".

Deterministic vs. Probabilistic

Deterministic in computing means the output is strictly tied to the input. In arithmetic, 2 + 2 is always 4, no matter how many times you run the calculation. If you write a piece of code that checks whether a number is greater than 0 and does one thing if it is and another thing if it isn't — that's deterministic: same input, same result, every time.

LLMs don't use "if-then" rules. When you ask an LLM to write a poem, it calculates something like: after the word "The", the word "sky" might be far more probable than "dog", with "ocean" somewhere in between.

Because of a setting called temperature — which introduces a controlled amount of randomness so the AI doesn't sound like a repetitive robot — the model samples from those probabilities. This is why hitting "regenerate response" gives you a completely different answer to the exact same prompt.

The irony: because LLMs are probabilistic, they're surprisingly bad at deterministic tasks. This is why early LLMs famously struggled with basic arithmetic — they were predicting what an answer looked like based on patterns, rather than actually computing it. Today's AI models often bypass this by recognising when you've asked a maths question and routing it to a proper deterministic tool (like a Python interpreter or a calculator) to get the correct answer. It's a bit like a very well-read person who knows roughly what "47 × 83" should look like, but quietly reaches for a calculator just to be sure.

LLMs as language learning tools

If you choose an LLM that has been well trained across multiple languages, it does a terrific job at translation. If the model is also large enough to have "seen" a broad range of topics during training, it can generate impressively varied content on demand. This is what makes LLMs a genuinely useful foundation for language learning: they're not faking fluency — they've absorbed patterns from billions of words of human writing across dozens of languages.

The catch, as always, is that not all models are equal. Some handle Spanish or French beautifully; others struggle with less-represented languages. (Believe me, I've tested a few.)

So can AI actually learn a language?

Here's the thing: LLMs don't learn languages the way humans do. A child learning Spanish makes mistakes, gets corrected, feels embarrassed, laughs it off, and slowly internalises the rules. An LLM is trained on a vast corpus of text and freezes — it doesn't grow from the experience of being used.

But that doesn't make them useless as teaching tools. Quite the opposite. Because LLMs are so good at understanding and generating natural language, they can do something genuinely valuable: give you meaningful, nuanced feedback on your attempts to learn. They can explain why a sentence sounds unnatural, suggest a more idiomatic phrasing, or generate a hundred practice sentences on any topic you like.

So the answer to "is AI any good at learning languages?" is: AI doesn't learn languages — but it can be remarkably good at helping you learn one. And understanding a little about how these models work under the hood makes it easier to use them well, and to know where not to trust them.

Sources

Andrej Karpathy — Intro to Large Language Models (YouTube, 2023)
Stephen Wolfram — What Is ChatGPT Doing… and Why Does It Work? (2023)
CALICO Journal — Computer Assisted Language Instruction Consortium (for further reading on AI-assisted language learning research)

P.S. Roasting me about the above is both acceptable and encouraged — just keep it friendly. I'm here to learn too, after all.

-Juha