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HomeColumnsAIコンサルIn the Age of Competing for Attention: Advertising Technology in the AI Era
AIコンサル

In the Age of Competing for Attention: Advertising Technology in the AI Era

Published2026-01-21Ryuta Hamamoto
CommunityBASEAIMarketingData Analysis

A practical guide to In the Age of Competing for Attention: Advertising Technology in the AI Era. Topics include Community, BASE, AI.

In the Age of Competing for Attention: Advertising Technology in the AI Era
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Modern Society Is Caught Between Information and Attention Capitalism

Modern society is caught between an explosion of information and a new economic model called "attention capitalism," driven by the rapid evolution of AI and advertising technology. Digital platforms such as smartphones, social media, and group chats have facilitated the distribution of diverse content, transforming people's "attention" into a constantly contested marketplace. In this context, debate is intensifying about the quality of AI-generated content and the impacts of information overload. The advertising industry is moving to collect user behavioral data at an unprecedented scale and optimize ad delivery strategies. This is not merely a matter of technological innovation — it is a critical theme directly relevant to corporate management and marketing strategy. This article focuses on the evolution of advertising technology and attention capitalism, the quality problems of AI-generated content, and the restructuring of digital communities, presenting the latest discussions and future predictions.

The Evolution of Advertising Technology and Attention Capitalism — The New Paradigm That AI Brings The Flood of AI-Generated Content and Quality Problems — The Possibility of Fusing Human Creativity with Algorithms The Future of Community and Personalization — Restructuring Group Chats and Networks Summary

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The Evolution of Advertising Technology and Attention Capitalism — The New Paradigm That AI Brings

Modern advertising technology has evolved from simple "novelty" to a complex, meticulous "competition for attention." Since the 2000s, platforms like Facebook Ads have grown explosively, transforming into a massive marketing ecosystem that generates enormous advertising revenue today. Behind this lies the introduction of AI and algorithms, with systems that analyze users' behavior, preferences, and even subtle behavioral data in real time to optimize advertising.

A frequently raised point in these discussions is how AI extracts users' "attention" and converts it into revenue. For example, AI can analyze which content users respond to and at what level, and when they engage — in ways that were previously unmeasurable by conventional media advertising. In this process, a gap can emerge between the "content" users want and the content that delivers the "attention" advertisers seek. Simply put, while AI provides you with content optimized for your preferences, there is a risk of diverging from the information you truly want and the aspects of your own interests.

What's particularly interesting is the perspective that AI-driven advertising optimization is producing a vast amount of "spam-like" content. As text, images, and video are displayed in loops before users' eyes, the phenomenon of low-quality content spreading mechanically has become something like a new "garbage problem" in digital society. What was once a concern about junk mail, phone solicitation, and unwanted advertising has entered a completely different phase in terms of scale and quality in the modern era — driven by AI auto-generated content.

Also particularly noteworthy is the duality of "acquisition" and "retention" in advertising. Advertisers focus on "acquisition" — drawing attention and aiming for short-term effect — but are simultaneously required to retain that attention and extract long-term value. However, the content AI generates in vast quantities automatically may momentarily catch users' "gaze," but ultimately poses the problem of inducing boredom and distrust. On platforms like TikTok, for example, short videos flow continuously, drawing momentary viewer interest — but simultaneously, there are reports of the phenomenon where this creates a kind of "nervous addiction," making it difficult for consumers to connect of their own free will.

Furthermore, in the context of attention capitalism, we can't overlook that users themselves are in a state of being "constantly observed" in their digital lives. In the past, being noticed by someone in a public space was a temporary thing, and individuals' privacy was protected to some degree. But modern digital platforms have created a trend where individuals behave like celebrities, always trying to attract attention on social media. As a result, companies are forced to seek methods of "retention" — users continuing to engage voluntarily — not just "short-term attention."

Additionally, the evolution of advertising technology is deeply connected to changes in revenue models. Traditional mass advertising centered on television and newspapers, with appeals in limited media spaces as the basic approach. But in the digital age, personalized advertising targeted at each individual user has become mainstream, and advertisers have come to track even casual user behavior using vast amounts of data.

AI-powered advertising optimization holds the potential to increase profitability on one hand, but also carries the risk of damaging the user experience. Many users feel "bored" or "frustrated" with low-quality ads and auto-generated content, and ultimately this can lead to them leaving the platform.

The current state of advertising technology and attention capitalism is not merely a matter of technological evolution — it's a theme with major impacts on the foundations of business, consumer behavior, and the information environment of society as a whole. Marketing professionals and executives are thus required to analyze consumer behavior more deeply, going beyond simple click counts and conversion rates.

The Flood of AI-Generated Content and Quality Problems — The Possibility of Fusing Human Creativity with Algorithms

In digital content generation, the introduction of AI has reached a historic turning point. What was once content that creators produced by hand is now generated in large quantities through AI automated processes in short periods. Conversational AI can automatically generate text, images, and even video according to users' requests — expanding in a liquid-like way. But amid this rapid transformation, many debates have arisen.

First, the risk is pointed out that AI-generated content "slop" — low-quality, unimaginative, formulaic content — circulates in enormous quantities. This could cause users to drift away from the high-quality information and deep insights they truly seek, becoming exhausted by content whose only purpose is "attention capture."

Compared to existing creators, AI is suited to "mass production," which risks diluting the creative elements and individuality unique to humans. When a social media feed contains a mix of fresh, handcrafted ideas and a vast quantity of automated content produced as routine work, it's clear which one users will find genuine value in. Past creators pursued unique expressions within limited time and resources. But AI can produce content in near-inexhaustible quantities, bringing the paradox of "quality" versus "quantity" to the surface.

In this situation, companies and advertisers face the challenge of how to capture users' "attention" and maintain user trust. On platforms like TikTok and Instagram, algorithms constantly suggest auto-generated videos and content to users — but among them, obviously mechanical patterns often give viewers a sense of being fed up. Users may have an "immersive experience" that makes them lose track of time once drawn in, but afterward increasingly fall into the feeling of "what was that?" — meaning AI-auto-generated slop content may succeed at temporarily driving clicks but doesn't necessarily lead to long-term user engagement or trust.

Furthermore, while technology advances, content "uniqueness" and "originality" are becoming diluted. In advertising and marketing, companies often devise ways to build unique stories and brand images. But if AI has the ability to mimic any pattern, differentiation becomes more difficult — leading to a situation where content from countless creators using AI proliferates, and what was once a unique market becomes homogenized with an overflow of "something similar."

Addressing this quality problem requires companies to reconsider how they use AI tools and how to achieve fusion with human creativity. Companies need to position AI as a supplementary tool and adopt a hybrid process where ultimate creative judgment is made by humans. This allows them to combine AI's overwhelming productivity with humans' unique perspectives and sensibilities to provide high-quality content.

The Future of Community and Personalization — Restructuring Group Chats and Networks

The rapid evolution of the digital age brings about major transformations not just in advertising quality and information distribution, but in the way people communicate and form communities. Today, while everyone behaves like a celebrity on social media, private group chats and closed networks are attracting attention as new means of community formation.

Group chats play an important role not just as a means of message exchange, but in building trust and solidarity among users. In business settings as well, internal communication using chat tools enables faster and more efficient information sharing compared to conventional email and meetings. Meanwhile, in personal social media use, it's also becoming clear that interaction among a limited set of members — rather than open posts — serves to cultivate a genuine sense of "community."

Such private networks also serve as safe "refuges" that free users from the feeling of being constantly monitored. Large-scale social media and public spaces often function for users as a kind of "digital panopticon," generating anxiety that behavior and statements are always being recorded. Group chats, by contrast, allow sharing information only among trusted companions, potentially becoming a place where one can truly express oneself.

Furthermore, with the flood of information and increasingly sophisticated advertising technology, the information received by individuals is extremely personalized. As a result, communication and networks in digital spaces are transforming into entirely new forms, no longer bound by conventional geographic and cultural distinctions.

In this context of change, companies are also pressed to reassess their brand and marketing strategies. Companies are shifting toward strategies that go beyond simply distributing advertising indiscriminately to a wide audience — seeking deeper engagement by leveraging opinion exchange and natural word-of-mouth within trusted communities.

On the other hand, such personalized communication, while appearing to protect privacy and give users a sense of security, also creates other problems. For example, with only like-minded people gathering, opportunities to encounter different opinions decrease — making the "echo chamber phenomenon" where one's own views become increasingly extreme more likely to occur.

Against this background, future communities are predicted to serve not only as places for exchanging information, but as important venues for forming and sharing users' identities and values. Companies need to accurately grasp these trends and — going beyond one-way traditional advertising strategies — build two-way communication environments in which users themselves participate. Furthermore, companies will be required to build stronger relationships of trust by advancing co-creation with users as members of the community themselves.

Also readOnline Event Landing Page Creation Guide | TIMEWELL

Summary

This article has explored the complex challenges and future vision of modern digital society from the perspectives of the evolution of advertising technology and the current state of attention capitalism, quality problems of AI-generated content, and the restructuring of group chats and networks. Companies are attempting to maximize users' "attention" using AI's powerful data analysis capabilities, while simultaneously facing risks of low-quality content proliferation and information homogenization. As users explore self-expression in both public spaces and private communities, companies' need to develop appropriate communication strategies in each context is growing.

In the future business environment, success will depend on seeking not just technological innovation, but also ethics, trust, and sustainable growth models. Both companies and individuals are called upon to find the value of "attention" in the digital age and build a rich future of co-creation together.

Reference: https://www.youtube.com/watch?v=2qOdhmmpveA


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