The global language learning market is undergoing major transformation, driven by the adoption of AI. Traditional curriculum-based approaches are being replaced by personalised, context-aware tools that adapt to individual learning goals and pace.
Key developments include:
- The shift to tailored, AI-enabled pathways that teach the right words at the right time and in the right context.
- More efficient and scalable content creation, enabling faster rollouts across multiple languages.
- The emergence of conversation bots and pronunciation tools that allow users to practise in realistic scenarios, without the need for human tutors.
- Early steps towards AI tutors that try to replicate the experience of personalised, one-to-one teaching.
- A reordering of the competitive landscape, as companies that embrace AI-first strategies move ahead of slower adopters.
- Renewed focus on immersive/in-person aspects of language learning in the context of more AI-enabled learning.
Contextualising language learning
The global language learning market is valued at $50–70bn and is growing at roughly 10% per year. At this pace, it is on track to exceed $80–110bn by 2030.
English remains the dominant language studied. In 2024, Duolingo found that English was the top choice in 134 of 193 countries. Motivations for studying vary, from career advancement to cultural curiosity, and differ by end language. For example, English learners are more likely to be career- or education-focused than those learning other languages.
The impact of AI on language learning
Historically, language learning has been shaped by standardised curricula. This approach has often failed to reflect the personal and practical reasons behind language learning. For example, many learners want to acquire specific vocabulary relevant to travel, work, or relationships.
A 2023 Pearson survey of English learners highlighted three consistent challenges with traditional learning:
- Overemphasis on grammar.
- Not enough real-life speaking practice.
- Limited use of the target language in classroom settings.
Personalised, context-aware learning
AI has enabled a move away from uniform learning paths. Platforms can now tailor content based on a learner’s goals, interests, and progression. For example, a user preparing for a holiday in France can focus on restaurant and transport vocabulary, rather than general grammar exercises.
This approach enhances both relevance and retention, and marks a significant improvement on one-size-fits-all learning.
Faster and more flexible content creation
AI allows providers to scale at speed. Duolingo notes, for example, that it took 12 years to build its first 100 courses. After adopting OpenAI tools in 2023, it created another 148 in just one year.
Beyond speed, AI also helps identify and surface content that fits a user’s personal learning journey. Video content, for instance, can be automatically transcribed, tagged, and recommended based on vocabulary or themes that match a learner’s needs.
Conversation tools and pronunciation buddies
AI-powered tools now allow users to simulate real-life conversations with responsive bots. These tools adapt to the learner’s level, increasing in complexity as vocabulary expands.
Crucially, these interactions provide exposure to native pronunciation and speech patterns, helping to develop both comprehension and confidence. Compared to human tutoring, these tools offer 24/7 availability and lower costs, without sacrificing relevance or fluency.
Continued focus on immersive experiences
In the context of increasing use of AI-enabled language learning tools, there is a renewed focus on the importance of immersive experiences alongside online learning. These can include: travel abroad, cultural experiences and sightseeing and will often enable learners to study another interest alongside a language – e.g. English with business skills, English with AI skills, etc. These experiences bring the concept of language learning to life and are expected to continue in an AI-adapted world.
What’s next: the rise of the AI tutor?
The next frontier for online learning is AI tutors that try to replicate the best aspects of human teaching – tailored learning plans, nuanced feedback, and real-time responsiveness.
Speak.com, for example, is developing what it claims is the world’s most advanced AI tutor. Leveraging OpenAI’s real-time API and multimodal audio tech, the platform aims to deliver natural, open-ended interactions that adjust to learner tone, intent, and pronunciation.
The challenge lies in going beyond transcription to interpretation, understanding why a learner says something, and responding appropriately. Future AI tutors may be able to design curricula, track performance, and adjust strategies much like a human teacher would.
However, these systems may struggle with learner accountability, a key benefit of real-life tutoring. Emotional intelligence and empathy will also remain difficult to replicate fully. Human tutors are unlikely to disappear but the balance of roles in the language learning ecosystem will shift.
Strategic implications
AI is changing the rules of engagement in the language learning market, which provides new opportunities for provider innovation and investor opportunities, though with important risks to monitor to ensure the proposition remains relevant. These include:
1. From ‘technology-first’ to ‘AI-first’
Firms that simply layer AI tools onto existing products may fall behind. The leaders are those adopting AI-first approaches that reshape the entire learning journey.
For example, using AI for content development, interactive learning features, and internal productivity. The result is a seamless integration of pedagogy, engineering, and design.
2. B2C traditional tutoring models under pressure
One-to-one tutoring providers have long relied on personal interaction as their core value proposition. As AI tools improve, this advantage could be eroded, without proposition evolution. Learners can now access AI tutors that offer similar levels of responsiveness and personalization without the cost, scheduling, or variability of human tutors.
3. The role of big tech
Large platforms are beginning to integrate language tools into broader applications. Google, for instance, is rolling out live translation for TV and video calls (enabling language learning more ‘in the flow’ of everyday life). These moves could reshape how language learning is delivered – but big tech’s appetite to build the depth of optionality, functionality and personalisation offered by the language learning specialists remains unclear.
4. Risk from universal translation
There is also a longer-term question over whether improvements in translation tools might reduce the need to learn languages at all. While this remains a distant prospect, it’s a topic worth monitoring as real-time translation becomes more accessible.
Immersive language learning
While immersive language learning providers may be partly protected from the implications of AI (instead focusing on the value of study abroad), there will likely still be a need to adopt AI to drive efficiencies in areas like content development and as part of hybrid learning programmes. For example, using AI to provide feedback on written tasks that are embedded throughout a lesson, thereby enabling teachers to focus on other areas, with the role of the teacher evolving to be more akin to a coach.
CIL continues to monitor trends and activity in the language learning space. If you would like to discuss key developments or strategic opportunities, please get in touch.
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