Artificial intelligence may be the most patient Spanish conversation partner ever created.
You can ask it to repeat an explanation five times, invent a dialogue for an airport or a business meeting, correct an email, simplify a newspaper article or practise the same verb tense until midnight. It never becomes impatient, and there is no embarrassment when you forget a basic word that you learned months ago.
For adults fitting Spanish around work and family life, this convenience has genuine value. A short conversation with an AI tool during a lunch break is certainly more useful than waiting for the perfect moment to study and doing nothing at all.
Some of the claims made about AI language learning, however, go much further. They suggest that regular conversations, personalised exercises and instant corrections can provide something close to a private tutor. Once an app can speak to us, respond naturally and explain grammar, it is tempting to assume that the teacher has become optional.
The difficulty is that producing language practice and directing somebody’s learning are very different tasks.
AI gives you somewhere to practise
One of the most useful qualities of AI is its availability. Finding opportunities to speak Spanish can be difficult, particularly for learners who live outside a Spanish-speaking country or feel self-conscious when speaking to another person.
An AI conversation creates a low-pressure environment in which it is possible to experiment. A learner can ask the tool to play the role of a hotel receptionist, an interviewer or a new colleague. If the conversation becomes too difficult, it can be slowed down or restarted. If a phrase is unclear, an explanation is immediately available.
Research supports some of these advantages. A recent systematic review examined 57 studies involving voice-based AI chatbots and language learners. The studies reported benefits including greater willingness to communicate, increased motivation and, in some cases, reduced anxiety when speaking. They also found recurring problems with speech recognition, unnatural interactions and insufficient corrective feedback. The researchers concluded that chatbots have considerable potential, while emphasising the need for guidance, scaffolding and carefully designed conversational activities. The full review is available through Cambridge University Press.
This seems a sensible way to understand their role. AI can provide a place to practise. The more difficult question is what should be practised, at what level and in what order.
A useful activity is not necessarily the right next activity
Suppose an adult learner asks an AI tool for a Spanish lesson about meetings at work. Within seconds, it can produce vocabulary, model sentences, a role-play and a short quiz. The result may look perfectly convincing.
That does not tell us whether the learner is ready for it.
Perhaps the role-play depends on conditional forms that the learner cannot yet use. Perhaps they studied the relevant expressions three months ago and need to retrieve them before beginning a spontaneous conversation. Perhaps their main difficulty is following fast speech, while the activity concentrates almost entirely on speaking. There may also be persistent problems from earlier stages which now prevent them from expressing more complex ideas clearly.
To make a good decision, someone needs to understand the learner’s present knowledge and their previous learning. The activity must also serve a wider purpose beyond filling the next twenty minutes.
This is where AI often appears more competent than it really is. It can generate an impressive response to almost any instruction, although it does not independently know whether the instruction itself makes pedagogical sense.
Research into AI-generated language lesson plans has found this same problem. In one study, identical prompts sometimes produced plans that followed current teaching principles and sometimes produced plans influenced by outdated practices. Adding more detail to a prompt did not consistently improve the result. Some responses covered more than 90 per cent of the researchers’ criteria, while others generated from the same prompt missed more than a quarter of them. The study explores this variability in detail.
A learner using AI independently faces an awkward situation: to obtain a well-designed course, they need to give the system the kind of instructions that usually require some knowledge of language teaching.
A correct correction can still be unhelpful
Instant feedback is one of the strongest attractions of AI language tools. A learner writes or says something, receives a corrected version and continues with the conversation.
Many of these corrections will be accurate. Yet accuracy is only one part of useful feedback.
Consider a learner who makes six mistakes while describing a recent project. Correcting all six may overwhelm them and interrupt their attempt to communicate. A tutor might instead select one recurring error connected to material studied previously, explain it briefly and create another opportunity to use the corrected form. Two other errors may be recorded for a future lesson, while the remaining ones are ignored for the moment because they have little effect on communication.
The decision requires judgement. How important is the mistake? Is it recurring? Does the learner possess the knowledge needed to understand the correction? Will addressing it now help, or merely add another piece of information that will soon be forgotten?
A 2025 study comparing feedback from ChatGPT with feedback from language teachers illustrates this distinction. The study examined 117 pieces of writing by learners of English. Around 88 per cent of the AI feedback was judged correct, appropriate and useful, which is an impressive result. However, some corrections were inaccurate and others were technically correct but unnecessary or too advanced for the learner. The AI’s feedback coincided with the teachers’ choices only 56 per cent of the time, with much stronger agreement on surface matters such as spelling and grammar than on content and organisation. The results were published in Language Teaching.
This study concerned written English in a particular educational setting, so its percentages should not be applied directly to every use of AI in Spanish learning. It nevertheless highlights an important principle: identifying a possible correction and deciding that it deserves the learner’s attention are separate judgements.
AI sees a sentence; a tutor sees a pattern
An AI tool responds very effectively to the material placed in front of it. A tutor working with the same learner over time sees something broader.
If a student says soy trabajando instead of estoy trabajando, the correction is straightforward. The more significant question is why the error has appeared. It may be a momentary slip, confusion between ser and estar, interference from English or evidence that the learner never consolidated the Spanish progressive form.
Each explanation calls for a different response.
A tutor can also notice patterns that extend beyond grammar. An adult learner may speak confidently about familiar personal topics but become hesitant as soon as a professional conversation requires precision. Another may understand sophisticated texts yet rely on very basic vocabulary when speaking. Someone else may produce good Spanish in controlled activities and lose accuracy when required to react quickly.
These patterns develop across lessons. They influence the choice of materials, the pace of progression and the kind of practice that will be most productive. AI can use a record of previous interactions if one is available, although interpreting a learner’s development remains far more demanding than remembering what was discussed last week.
Successful conversations can give a misleading impression
AI is remarkably good at keeping an exchange alive. It can infer the intended meaning of an unusual sentence, overlook ambiguity and adjust its response instantly. This creates smooth conversations, even when the learner’s Spanish would cause greater difficulty with a real person.
That experience can build confidence, and confidence matters. It can also conceal gaps.
The real test of learning comes later. Can the learner retrieve the same language without suggestions? Can they understand a different voice at a natural speed? Can they respond when the conversation takes an unexpected direction? Can they communicate with someone who does not automatically reconstruct an incomplete or inaccurate sentence?
A productive AI conversation is therefore useful practice, although it is not proof that the language used during it has become independent knowledge. This is closely connected to a wider problem I discussed in Why Speaking More Is Not Enough to Learn Spanish: opportunities to produce language are most effective when they are supported by carefully selected vocabulary, grammar and previous guided practice.
How AI can support a professionally focused Spanish course
The best use of AI becomes clearer when it is given a defined role within a structured course.
Imagine that a learner needs Spanish for meetings with clients. Before attempting a full simulation, they may need to work on:
- introducing a point clearly;
- expressing partial agreement;
- asking for clarification;
- correcting a misunderstanding politely;
- using the conditional to make proposals;
- referring to deadlines and recent progress;
- gaining a few seconds to think without abandoning Spanish.
A tutor can identify which of these areas matter most, introduce the necessary language and design activities that require the learner to retrieve it repeatedly. Once the foundation is secure, AI becomes an excellent source of additional practice.
It can play the role of a demanding client, introduce an unexpected objection or generate several versions of the same situation. The learner can repeat the task between lessons and bring difficult moments back to the tutor. In the following lesson, the teacher can examine what happened, address recurring problems and decide what should come next.
Here, AI expands the learning process without being expected to manage it.
It can also be useful for adults in several other ways:
- rehearsing familiar situations before a trip or meeting;
- creating short vocabulary quizzes from recently studied material;
- providing extra examples of a grammatical structure;
- simplifying authentic texts for a learner’s current level;
- practising pronunciation without the pressure of an audience;
- generating variations of an activity already introduced in a lesson;
- reviewing a first draft before receiving more selective feedback from a tutor.
These uses take advantage of the technology’s speed and flexibility while preserving a coherent direction.
The learner should not have to become the course designer
Motivated adults often take considerable responsibility for their learning. They read independently, listen to podcasts, keep vocabulary records and look for opportunities to use Spanish between lessons. This autonomy is valuable, and AI provides more resources for it than learners have ever had before.
Responsibility for studying, however, is different from responsibility for designing the entire learning process.
Most learners cannot be expected to diagnose the precise reasons for their own difficulties, decide which errors require attention, construct a suitable progression and evaluate whether an AI-generated activity follows sound teaching principles. These are specialised decisions. Leaving them entirely to the learner can produce a great deal of activity without a corresponding sense of direction.
The British Council’s research into AI and language education reached a similarly measured conclusion. Teachers surveyed across 118 countries and territories already used AI for creating materials, providing practice, planning lessons and correcting language. At the same time, respondents raised concerns about limited capabilities, technical problems and linguistic bias, while the majority view among the report’s expert contributors was that AI would not remove the need for human teachers. The British Council report provides an overview of these findings.
AI is becoming a normal part of language learning. The important decision is no longer whether it should be used, but how.
A strong combination: tutor-directed, AI-supported learning
AI can explain grammar, correct sentences and sustain surprisingly natural conversations. It gives adults affordable, convenient and almost unlimited opportunities to practise. Used thoughtfully, it can make the time between lessons much more productive.
A tutor contributes something different: knowledge of the learner, informed selection, continuity and responsibility for the direction of the course. After more than twelve years of teaching languages, I have found that progress often depends less on finding another possible activity and more on identifying the activity that this particular learner needs now.
This principle shapes my one-to-one Spanish lessons for adults and professionals. I build each course around the learner’s existing knowledge, objectives and professional or personal needs, connecting new material with previous learning and deciding which difficulties deserve attention. AI can then provide additional repetition, experimentation and practice between lessons whenever the learner has time.
An AI tool can always generate another exercise. Good teaching ensures that the exercise has a purpose—and that it leads somewhere.
