The Expensive Promise of AI: An In-Depth Look at the Duolingo Case – Growth, Profitability, and Strategic Foresight

Duolingo’s practice shows that the value of AI goes far beyond short-term cost reductions, but is a strategic investment for the future. Its AI-driven product innovation, business monetization, and data accumulation are reshaping the future value curve, even if it means paying a “leader tax” on short-term profit margins.

At present, artificial intelligence (AI) is almost equated with “reducing costs and increasing efficiency”. However, when we look at the financial statements of Duolingo, one of the world’s most successful edtech applications, a striking paradox emerges: while the company’s user size and revenue continue to soar, its core gross profit margin is under significant pressure due to the deep application of AI.

This seemingly contradictory phenomenon forces us to think deeply: when business managers eagerly embrace AI, what kind of value are they seeking?

“Retail Observation” believes that for innovative companies committed to creating the future, the value of AI goes far beyond simple cost reduction. It is even more concernedstrategic growth, core competition wall solidification and future value curve reshapingof active investment. The fluctuation of gross profit margin and profit margin in the short term is actually a “leader tax” paid for longer-term and more fundamental business success.

A strategic perspective on AI value: a chess game that goes beyond short-term gains

To understand Duolingo’s AI strategy, we must move beyond the single framework of “reducing costs and increasing efficiency” and place the value of AI in a three-dimensional and interconnected strategic value quadrant:

First, improve operational efficiency (reduce costs and increase efficiency):

This is the most intuitive value of AI. Duolingo CEO Louis von An once made it clear: “It took about 12 years to develop our first 100 courses, and now, with the power of AI, we are able to create and launch nearly 150 new courses in about a year.” ”

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This leap in efficiency has directly led to the company cutting about 10% of its contract translators from late 2023 to early 2024. In addition, Duolingo also uses machine learning models to optimize advertising strategies, and by introducing the XGBoost model, it can achieve tens of millions of dollars in additional revenue growth every year, which is also an example of AI improving operational efficiency and indirectly increasing revenue.

Second, product innovation (experience upgrade):

AI can create unprecedented user experiences and fundamentally enhance the core value of products. Duolingo recognized this early on. From the early “half-life regression” (HLR) model to the “BirdBrain” system, the core goal of these in-house AI applications is not to reduce costs, but to increase users’ daily activity by 12% through deep personalized learning, significantly optimize learning effects and consolidate user stickiness – this is a strategic investment in the user’s long-term asset.

Third, increase revenue and profit (commercial realization):

AI-powered new features or products that can open up new revenue streams or increase average revenue per user (ARPU). The launch of Duolingo Max is the most direct commercialization embodiment of Duolingo’s AI strategy. Rather than a simple optimization of the existing free model, it creates a new, higher-value tier of paid products by integrating GPT-4-powered features like “explain my answer,” “roleplay,” and “video call with Lily,” clearly pointing towards revenue growth.

Fourth, strategic moat (building barriers):

AI and data accumulation can form unique advantages that are difficult for competitors to replicate. Through continuous investment in AI and the accumulation of massive user data, Duolingo is building an insurmountable technical and data barrier to ensure its long-term leadership in the market.

This grand AI transformation is also accompanied by “soft costs” and “soft returns” that are difficult to quantify directly but are crucial.

In terms of soft costs, the pain of organizational change caused by the “AI first” strategy, the public opinion turmoil caused by the reduction of artificial positions, and the quality controversy that may be brought about by AI-generated content are all hidden costs that must be borne in the transformation process. CEO Louis von An’s all-staff letter has sparked a strong reaction, with a large number of users expressing their dissatisfaction on social media, and this potential damage to the brand’s reputation is real.

However, soft returns are equally important: the company’s brand image as an “AI education leader”, its strong attraction to the world’s top AI talents, and the premium of “AI concept stocks” in the capital market are strategic intangible assets that cannot be easily estimated. Therefore, the CEO’s decision is far from being based solely on cold financial figures, but on a complex strategic trade-off that encompasses hard metrics and soft factors.

The Duolingo Paradox: How AI Inputs Can Lead to Strategic Sacrifices in Short-Term Profit Margins

This multi-dimensional value consideration finally reflects a unique “song of ice and fire” in Duolingo’s financial statements.

The flame of users and revenue growth is remarkable: in the first quarter of 2025, Duolingo’s daily active users (DAU) surged 49% year-on-year to 46.6 million; Monthly active users (MAU) increased by 33% to 130.2 million; The number of paying users exceeded the 10 million mark for the first time, reaching 10.3 million, a year-on-year increase of 40%. Total revenue reached $230.7 million, up 38% year-over-year. This report card undoubtedly depicts its soaring trend in the market.

However, at the same time, the statement showed an eye-catching “coldness” – gross profit margin fell to 71.1% from 73.0% in the same period last year. The company clearly pointed out that this decline is mainly due to the rising cost of generative AI associated with Duolingo Max, which has an impact of about 150-170 basis points.

Tracing back to the core source of this cost, we can find a very strategic decision by Duolingo: choosing to cooperate with OpenAI to deeply integrate the most advanced, capable, but also expensive GPT-4 model on the market at the time into its Duolingo Max product. Although this is a technical helplessness, it is actually a sober strategic choice. To achieve the ultimate approach to the immersive experience of live tutoring pursued by features like “Explain My Answer” and “Video Call with Lily”, you must use the most cutting-edge AI capabilities.

This choice of top technology directly leads to an increase in variable costs. Every time a Max subscriber interacts with the AI in depth, such as requesting a detailed explanation of a grammatical error or engaging in a verbal conversation with an AI character, an API call is triggered, incurring real costs. According to the company, Max subscribers account for 7% of the total subscribers, and every high-frequency interaction they have is adding new overhead to Duolingo’s server bills.

But it is this high AI investment that directly translates into a powerful engine that drives revenue growth. The core value proposition of Duolingo Max is precisely because of these differentiated features powered by cutting-edge AI that cannot be compared to the regular version. Max subscribers have played a positive role in driving the growth of bookings for high-priced packages, clearly confirming that users are willing to pay a premium for a premium AI experience.

Therefore, the case of Duolingo clearly reveals a core logic:High AI investment (cost) and new AI-driven revenue streams (increased revenue) are two sides of the same coin. In the early stages of strategy implementation, especially when embracing cutting-edge technologies, costs may temporarily exceed the direct revenue contribution they bring, inevitably leading to short-term pressure on profit margins. This is an active strategic trade-off.

Sacrificing profit margins for moats: strategic investments in the age of AI

If the sacrifice of short-term profit margins is the “price” paid by Duolingo, what it expects to “buy” is a strategic moat that will be difficult to shake in the next decade.

In today’s increasingly popular general AI tools such as ChatGPT, any language learning application faces the potential threat of being “replaced for free”. Duolingo’s response is not to circumvent AI, but to adopt itDeep integration and contextualizationCome to build their defensive fortresses. Instead of simply cramming AI into a product as an isolated chatbot, it seamlessly embeds it into its full-fledged learning paths and gamified experiences.

For example, the “explain my answer” feature is valuable not only because it provides grammatical explanations, but also because it appears in the most intellectually curious person who has just made a mistakeGolden Scenarioprovides immediate, personalized, and pain-point answers. This AI experience, which is deeply integrated and seamlessly integrated with the learning process, is difficult for any general AI tool to provide.

To build and be the first to deliver this unique experience, Duolingo must be the first “crab eater” to be the first to apply cutting-edge LLMs to consumer-grade educational products at scale. This first-mover advantage allowed Duolingo to quickly seize the minds of users and shape its brand image as an “AI education leader” in the eyes of users. However, being a pioneer also means bearing higher costs of technology exploration and market education. This additional investment in staying ahead of the industry can be seen as a strategic “leader tax.”

The more far-reaching significance is that this AI investment is being effectively “capitalized”.Every interaction, every question, every conversation of Duolingo Max users is constantly providing Duolingo with unique, massive, high-quality data on “how to teach effectively through AI”.This proprietary data will continue to feed back its future AI models (whether it is optimizing third-party models or developing self-developed capabilities), making its personalization engine more and more accurate, thus forming a powerful data flywheel, which constitutes a competitive barrier that is difficult for latecomers to reach.

At the same time, successful AI applications have also upgraded Duolingo’s brand image from “a fun language learning game” to “a cutting-edge AI-driven education company”, which has played a pivotal role in attracting top talent and winning the trust of investors.

Long-term focus: the “return of value” road to AI costs

So for enterprises: when will this expensive strategic AI investment usher in an inflection point in its value return?

An encouraging sign is that the cost of AI calls is following a downward trajectory similar to Moore’s Law. Duolingo CEO Louis von An made it clear in a recent interview: “The cost of querying large language models is decreasing every month. ”

This is the technology trend of the entire AI industry, and with the maturity of the underlying technology, the optimization of model architecture and the intensification of market competition, the reduction of the unit cost of AI is an inevitable trend. Duolingo’s current investment is betting that this cost curve will come as scheduled, laying the foundation for its long-term development.

In addition, in the longer term,Duolingo is also expected to gradually transform from a “tenant” of AI technology to a “homeowner”。 With its vast amounts of data and engineering experience, it is entirely possible for companies to develop or fine-tune smaller, more focused, and lower-cost proprietary models for specific teaching tasks, reducing reliance on expensive generic models. This is a mature path that many technology giants have taken in their exploration in the field of AI, and it is also a potential direction for Duolingo to reduce long-term operating costs.

When the trend of declining AI costs intersects with the trend of increasing Duolingo Max subscription penetration, Duolingo’s profit margins will usher in a decisive “value return” inflection point. At that time, the high costs paid in the early days to seize market opportunities and polish product experience will begin to release huge financial returns. Therefore, the “sacrifice” of Duolingo’s current gross profit margin is essentially a forward-looking strategyDelayed gratification。 It is using today’s profits to invest in a future with a higher barrier to entry and more room for profit.

Conclusion: AI Must-Answer Questions for Leaders – What the Truth Are You Buying?

Duolingo’s practice provides a profound and guiding enlightenment for all enterprises in the AI wave: simply equating the value of AI with “reducing costs and increasing efficiency” is undoubtedly a strategic short-sightedness.

For every business leader looking to succeed in the AI era, the first question to answer when investing huge amounts of money in AI deployment should never just be, “How much will it save me?” It should be “What do I hope to ‘buy’ for my business with this investment?”

Should we buy short-term operational efficiency improvements, or long-term user loyalty and lifetime value? Buy an automation tool that can be easily replicated by competitors, or buy an insurmountable competitive moat built by proprietary data and unique experiences? Is it to buy a temporarily beautiful profit figure on the current financial statements, or a ticket to absolute market leadership in the future?

Duolingo bought it with temporary gross margin fluctuationsAccelerators for growth, revolutionary leaps in experience, and leadership in the markets of the future。 As CEO Louis von Ahn said: “We can’t wait for technology to be 100% perfect. We would rather maintain a sense of urgency and occasionally risk quality than procrastinate and miss opportunities. ”

In the AI era, the real winners may not be the companies that are best at using AI to “save money”, but those that know how to use AI to “invest” strategically. This is the most profound and expensive business truth of the AI era that Duolingo, with its real business practices, has revealed to all of us.