AI is not just for chatbots and self-driving cars anymore. It now powers tools that claim to let humans talk to plants and helps people turn their smart TVs into 'dumb' ones by blocking ads and tracking. These unconventional applications pose a direct question for investors: are these novel uses just curiosities, or do they represent new, profitable markets for AI technology?
Consider Electric Plant, a startup that built an AI-powered translator. The company says plants 'speak' using electricity, and their AI model helps humans understand this language. Their pitch is a new tool for growers and researchers to monitor plant health and needs. This is a very specific application of AI, far removed from the general-purpose large language models (LLMs) that dominate headlines.
On the other side, some frustrated consumers are using AI agents to strip away bloatware from their smart TVs. These users are fed up with intrusive ads, constant data tracking, and sluggish interfaces that come bundled with modern smart televisions. They are leveraging AI to take back control, making their smart TVs 'dumb' again, focusing on core functionality without the unwanted digital baggage.
This type of AI application is driven by consumer frustration and a desire for privacy and simplicity. It is a reaction to the business model of many smart TV manufacturers, who increasingly rely on advertising revenue and data collection to subsidize hardware costs. If enough people adopt these AI tools, it could cut into a revenue stream for TV makers and content providers.
The problem for Electric Plant is scale. While the concept of talking to plants is fascinating, the addressable market for a plant language translator is likely small, primarily limited to commercial agriculture, specialized research, or very dedicated hobbyists. The revenue potential, while possibly high per customer, might not justify the investment required to develop and maintain a complex AI system. For the smart TV AI, the challenge is monetization. These agents are often open-source or DIY, making it hard for any single company to capture significant value beyond offering premium 'de-bloating' services.
For investors, the immediate winners in these niche AI applications are the underlying infrastructure providers: the cloud computing companies like Amazon Web Services or Microsoft Azure that host these AI models, and the chip manufacturers like Nvidia that provide the processing power. These companies sell shovels in a gold rush, regardless of whether the gold is found in talking plants or ad-free TVs. The losers are potentially the smart TV manufacturers who lose ad revenue, and any startup that invests heavily in a niche AI application without a clear, scalable path to profitability. While individual users might save money by blocking ads, the collective impact on the multi-billion dollar TV advertising market could be substantial if this trend grows.
In Brazil, we say 'a necessidade é a mãe da invenção' (necessity is the mother of invention), and these AI uses certainly fit that bill, born from specific needs or frustrations. But the business of AI is not just about invention; it is about viable business models. The smart TV scenario, for example, highlights a battle between user experience and corporate monetization strategies. Companies that rely on ad-supported services will need to adapt if AI agents become widespread tools for ad blocking.
What to watch next: Keep an eye on how these niche AI applications attempt to monetize. Will Electric Plant find a way to license its technology broadly, or will it remain a boutique tool? Will companies emerge that offer subscription services for AI-powered ad blocking on TVs, transforming a DIY solution into a structured business? The future of AI might be less about grand pronouncements and more about these small, targeted battles for user control and value.
