As per the latest report issued by technology market research firm Counterpoint Research, the global consumer expenditure on generative artificial intelligence (AI) is projected to surge from $225 billion in 2023 to $699 billion by 2030, marking a compound annual growth rate (CAGR) of 21%. From a sectoral standpoint, AI conversational platforms represent the fastest-growing segment, with personal assistant AI and content generation tools also poised for substantial expansion. By 2030, the monthly active users (MAUs) for global AI conversational platforms are anticipated to exceed 5 billion.

This report underscores that consumer spending on AI will persist in a steady upward trajectory over the forthcoming five years. For every participant in this field, the AI sector still harbors significant untapped potential. Similarly, for each individual, AI is poised to become the "utilities" of production and daily existence, seamlessly integrating with the scenarios and industries now within our grasp, akin to the internet's past impact.

Despite the considerable growth prospects in AI development, as people's comprehension of AI gradually deepens, particularly when AI transitions from being a "game-changer" for early adopters to the "utilities" for every enterprise and industry, our perception and approach to AI are undergoing a novel transformation and upgrade. Through this report, we not only witness the massive scale of consumer spending generated by the AI market itself but also glean new insights behind such a vast scale.

AI is Evolving from a "Game-Changer" to "Infrastructure"

Typically, the term "game-changer" is employed to depict a unique skill that "you possess, but others lack." In an era when AI's utility was not widely acknowledged, especially when AI was not perceived as a definitive development direction, it was often viewed as a unique entity. This is evident in the transformation of large models from a standout feature to a ubiquitous phenomenon.

Whether it was the early AI conversational applications or the initial large models, they almost universally reflected this phenomenon. At that juncture, players who were the first to launch their AI applications or large models almost invariably garnered market attention, be it from the capital market or the user market.

With the groundbreaking emergence of DeepSeek, particularly as it began to be applied across diverse industries and scenarios, AI transitioned from a niche existence to a mainstream one. Now, virtually all industries and scenarios are intertwined with AI, and nearly every facet of our lives is linked to it. In this context, AI is no longer the "game-changer" for a select few but has evolved into an "infrastructure" accessible to all.

In this scenario, we observe that "AI+" has commenced replacing "Internet+" as a new development trend. Counterpoint Research's report directly mirrors this phenomenon. As AI transforms into "infrastructure," we will witness more scenarios and industries undergoing transformation. Consequently, the consumer spending generated by AI is destined to experience even greater growth, as indicated in the report.

AI is Transitioning from "Investment-Driven" to "Business-Driven"

Reflecting on AI's development, it is apparent that it was primarily capital-driven. In this process, players with capital could realize their AI布局 (layout) through self-investment, while those lacking capital relied more on institutional investments. Whether self-invested or externally funded, AI's past development was largely propelled by capital. This resulted in players whose products resonated with capital almost universally achieving rapid development and securing a foothold in the first wave of AI development.

As the AI investment boom wanes, particularly as investment in the AI sector becomes increasingly saturated, merely continuing with the previous development model and relying solely on capital has begun to encounter more and more difficulties and challenges. The current scenario, where early players are completing their financing and ultimately listing on larger capital markets, and where investment institutions are showing a preference for more commercially oriented projects, directly reflects this phenomenon.

If we were to summarize and define AI's current development, we would find that AI is no longer primarily "investment-driven" but has become "business-driven." In this new phase, what truly tests players is no longer their ability to raise capital or win favor in the capital market but rather their ability to commercialize.

In this context, we observe players with rich application scenarios beginning to integrate their AI into their business scenarios, and more players deploying their AI in end-side AI, which is closer to commercialization. Now, AI is gradually entering a new cycle driven by "business." For any player aiming to make a mark in this phase, continuously seeking connections between their AI products and commercialization and achieving commercialization for their AI is pivotal to ensuring success in this new stage.

AI is Moving from the "Lab" into Everyday Life

One of the key reasons for the significant growth potential in consumer spending on AI is its transition from a highly specialized, expensive, and high-threshold existence to a more universal, affordable, and low-threshold one. Wang Xingxing, the founder of Unitree, has candidly pointed out that when robots truly become practical, their prices are expected to further decline and may even become "free."

In the past, AI was more akin to a lab-based existence, primarily targeting professional audiences, scenarios, and functions. With AI applications like DeepSeek breaking this status quo, AI is no longer confined to the lab but is now being implemented in specific scenarios, industries, and businesses, achieving comprehensive and deep connections with various sectors.

As AI becomes more popularized and integrated into daily life, particularly as technological barriers are dismantled, the previous high-cost and specialized nature of AI will be disrupted. At this juncture, AI will no longer be exclusive to a few labs but will become an indispensable part of people's daily lives. When AI achieves comprehensive and deep connections with a broad user base and full integration with businesses, the consumer spending it generates is expected to further escalate.

One of the key reasons why Counterpoint Research's report is so optimistic about future AI consumer spending is the increase in consumption scale brought about by the popularization and daily integration of AI. This is akin to the development logic of the internet. One of the reasons why the internet has been able to unleash such enormous potential is that it has become popularized and integrated into daily life, truly transforming into a new lifestyle for ordinary people to meet their daily needs. If AI truly becomes accessible to the general public, the growth it brings may be even more imaginative than what we have witnessed with the internet thus far.

Conclusion

As per the latest report issued by technology market research firm Counterpoint Research, the global consumer expenditure on generative artificial intelligence (AI) is projected to surge from $225 billion in 2023 to $699 billion by 2030, marking a compound annual growth rate (CAGR) of 21%. Through this report, we can discern that consumer spending on AI will continue to experience certain growth. One of the key reasons for this growth is that AI is beginning to permeate various industries, its development logic is evolving, and it is becoming more popularized and integrated into daily life. The development of AI is entering a new cycle, and in this new phase, we need to find truly suitable development paths for ourselves to truly capitalize on this new cycle.