Market analysts are increasingly applying 1960s media theory to evaluate generative AI investments. By viewing AI platforms as new communication environments rather than simple tools, investors can better distinguish between temporary hype and sustainable, long-term business models. This framework offers a different lens to assess where future value will likely be created in the digital economy.
As billions of dollars flow into generative artificial intelligence, traditional financial metrics often fail to capture the long-term value of these companies. A growing number of analysts are turning to 1960s media theory to better understand the AI landscape. This perspective encourages investors to treat AI platforms not just as computational tools, but as new communication environments that will fundamentally change human behavior.
Moving Beyond the Hype Cycle
Many investors currently value AI companies based on technical benchmarks, such as model parameter counts or processing power. However, historical media trends suggest that early-stage adoption often follows an imitation phase. Just as the printing press initially copied religious texts and early television mimicked theater, generative AI is currently being used to produce traditional content like text and music. From an investment standpoint, this suggests that the companies winning today are not necessarily those that will define the market of tomorrow. Investors are instead being encouraged to look for firms that are developing 'AI-native' formats—innovations that create entirely new experiences which could not exist without these specific technologies.
The Economics of Human Attention
Applying the ideas of theorist Guy Debord, who wrote about the 'Society of the Spectacle,' provides a way to look at how AI companies might monetize user behavior. If social media platforms successfully colonized interpersonal connections, AI is uniquely positioned to commodify other parts of daily life, such as entertainment and physical habits. Companies that can bridge the gap between real-world experiences and digital mediation are likely to capture significant user attention. For an investor, the strategic question shifts from 'What technical task can this AI perform?' to 'How effectively does this AI capture and retain human time and attention?'
Assessing Investment Risks
While this theoretical approach offers a new way to analyze the market, it is important to note that academic frameworks do not guarantee financial returns. Applying media theory is an analytical exercise, not a substitute for standard financial due diligence. The AI sector remains subject to high volatility, regulatory uncertainty, and intense competition. Investors should be cautious of the risk that companies may prioritize 'recursive digital engagement'—keeping users glued to screens through AI—at the cost of sustainable utility or long-term profitability.
What Investors Should Monitor
For those observing the sector, the key will be distinguishing between companies building temporary engagement loops and those creating genuine, long-term business advantages. Monitoring a company’s ability to move beyond basic machine-assisted content toward original, AI-native products will be essential. Additionally, as regulatory bodies and markets continue to evaluate the societal impact of AI, observing how companies balance attention-capture strategies with actual economic utility will be a primary indicator of their long-term viability.